diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/#layer_composition.txt# b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/#layer_composition.txt#
new file mode 100644
index 0000000000000000000000000000000000000000..10692997a90e4490a91ad3d0e6e04285754144fd
--- /dev/null
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/#layer_composition.txt#
@@ -0,0 +1,83 @@
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+pool
+dense add
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/#layers.txt# b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/#layers.txt#
new file mode 100644
index 0000000000000000000000000000000000000000..0bd2b554374c10d748a652f52e5427c716be0084
--- /dev/null
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/#layers.txt#
@@ -0,0 +1,83 @@
+Conv1,10000,3,32,32,32,3,3,3
+#tensorBatchNorm1
+#tensorRelu1
+#tensorDepthwiseConv1
+#tensorBatchNorm2
+#tensorRelu2
+Conv2,10000,32,32,32,64,32,1,1
+#tensorBatchNorm3
+#tensorRelu3
+#tensorDepthwiseConv2
+#tensorBatchNorm4
+#tensorRelu4
+Conv3,10000,64,16,16,128,64,1,1
+#tensorBatchNorm5
+#tensorRelu5
+#tensorDepthwiseConv3
+#tensorBatchNorm6
+#tensorRelu6
+Conv4,10000,128,16,16,128,128,1,1
+#tensorBatchNorm7
+#tensorRelu7
+#tensorDepthwiseConv4
+#tensorBatchNorm8
+#tensorRelu8
+Conv5,10000,128,8,8,256,128,1,1
+#tensorBatchNorm9
+#tensorRelu9
+#tensorDepthwiseConv5
+#tensorBatchNorm10
+#tensorRelu10
+Conv6,10000,256,8,8,256,256,1,1
+#tensorBatchNorm11
+#tensorRelu11
+#tensorDepthwiseConv6
+#tensorBatchNorm12
+#tensorRelu12
+Conv7,10000,256,4,4,512,256,1,1
+#tensorBatchNorm13
+#tensorRelu13
+#tensorDepthwiseConv7
+#tensorBatchNorm14
+#tensorRelu14
+Conv8,10000,512,4,4,512,512,1,1
+#tensorBatchNorm15
+#tensorRelu15
+#tensorDepthwiseConv8
+#tensorBatchNorm16
+#tensorRelu16
+Conv9,10000,512,4,4,512,512,1,1
+#tensorBatchNorm17
+#tensorRelu17
+#tensorDepthwiseConv9
+#tensorBatchNorm18
+#tensorRelu18
+Conv10,10000,512,4,4,512,512,1,1
+#tensorBatchNorm19
+#tensorRelu19
+#tensorDepthwiseConv10
+#tensorBatchNorm20
+#tensorRelu20
+Conv11,10000,512,4,4,512,512,1,1
+#tensorBatchNorm21
+#tensorRelu21
+#tensorDepthwiseConv11
+#tensorBatchNorm22
+#tensorRelu22
+Conv12,10000,512,4,4,512,512,1,1
+#tensorBatchNorm23
+#tensorRelu23
+#tensorDepthwiseConv12
+#tensorBatchNorm24
+#tensorRelu24
+Conv13,10000,512,2,2,1024,512,1,1
+#tensorBatchNorm25
+#tensorRelu25
+#tensorDepthwiseConv13
+#tensorBatchNorm26
+#tensorRelu26
+Conv14,10000,1024,2,2,1024,1024,1,1
+#tensorBatchNorm27
+#tensorRelu27
+#tensorPooling1
+FC1,10000,1024,1024,10
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/approxhpvm_src.cc b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/approxhpvm_src.cc
new file mode 100644
index 0000000000000000000000000000000000000000..5089eb912bcb5335c96c04f6d98f5d17ab761c72
--- /dev/null
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/approxhpvm_src.cc
@@ -0,0 +1,2400 @@
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <unistd.h>
+#include <fcntl.h>
+#include <sys/stat.h>
+#include <cstring>
+#include <visc.h>
+#include <tensorTypes.h>
+#include <tensorUtils.h>
+
+void var_0_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 1, 1, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_1_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_2_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_3_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 32);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_4_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_5_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_6_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_7_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_8_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_9_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 2, 2, 1, 64);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_10_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_11_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_12_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_13_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_14_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_15_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 128);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_16_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_17_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_18_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_19_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_20_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_21_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 2, 2, 1, 128);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_22_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_23_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_24_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_25_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_26_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_27_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 256);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_28_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_29_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_30_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_31_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_32_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_33_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 2, 2, 1, 256);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_34_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_35_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_36_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_37_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_38_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_39_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 512);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_40_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_41_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_42_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_43_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_44_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_45_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 512);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_46_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_47_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_48_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_49_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_50_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_51_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 512);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_52_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_53_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_54_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_55_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_56_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_57_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 512);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_58_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_59_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_60_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_61_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_62_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_63_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 512);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_64_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_65_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_66_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_67_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_68_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_69_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 2, 2, 1, 512);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_70_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_71_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_72_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_73_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_74_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_75_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 1024);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_76_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_77_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_78_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_79_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_80_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_81_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_pool_avg(t1, 2, 2, 0, 0, 2, 2);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_82_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_mul(t1, t2);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_83_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_add(t1, t2);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_84_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_softmax(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void root(void* input, size_t input_bytes,
+ void* conv2d_1_w, size_t conv2d_1_w_bytes,
+ void* batch_normalization_1_gamma, size_t batch_normalization_1_gamma_bytes,
+ void* batch_normalization_1_beta, size_t batch_normalization_1_beta_bytes,
+ void* batch_normalization_1_mean, size_t batch_normalization_1_mean_bytes,
+ void* batch_normalization_1_variance, size_t batch_normalization_1_variance_bytes,
+ void* depthwise_conv2d_1_w, size_t depthwise_conv2d_1_w_bytes,
+ void* batch_normalization_2_gamma, size_t batch_normalization_2_gamma_bytes,
+ void* batch_normalization_2_beta, size_t batch_normalization_2_beta_bytes,
+ void* batch_normalization_2_mean, size_t batch_normalization_2_mean_bytes,
+ void* batch_normalization_2_variance, size_t batch_normalization_2_variance_bytes,
+ void* conv2d_2_w, size_t conv2d_2_w_bytes,
+ void* batch_normalization_3_gamma, size_t batch_normalization_3_gamma_bytes,
+ void* batch_normalization_3_beta, size_t batch_normalization_3_beta_bytes,
+ void* batch_normalization_3_mean, size_t batch_normalization_3_mean_bytes,
+ void* batch_normalization_3_variance, size_t batch_normalization_3_variance_bytes,
+ void* depthwise_conv2d_2_w, size_t depthwise_conv2d_2_w_bytes,
+ void* batch_normalization_4_gamma, size_t batch_normalization_4_gamma_bytes,
+ void* batch_normalization_4_beta, size_t batch_normalization_4_beta_bytes,
+ void* batch_normalization_4_mean, size_t batch_normalization_4_mean_bytes,
+ void* batch_normalization_4_variance, size_t batch_normalization_4_variance_bytes,
+ void* conv2d_3_w, size_t conv2d_3_w_bytes,
+ void* batch_normalization_5_gamma, size_t batch_normalization_5_gamma_bytes,
+ void* batch_normalization_5_beta, size_t batch_normalization_5_beta_bytes,
+ void* batch_normalization_5_mean, size_t batch_normalization_5_mean_bytes,
+ void* batch_normalization_5_variance, size_t batch_normalization_5_variance_bytes,
+ void* depthwise_conv2d_3_w, size_t depthwise_conv2d_3_w_bytes,
+ void* batch_normalization_6_gamma, size_t batch_normalization_6_gamma_bytes,
+ void* batch_normalization_6_beta, size_t batch_normalization_6_beta_bytes,
+ void* batch_normalization_6_mean, size_t batch_normalization_6_mean_bytes,
+ void* batch_normalization_6_variance, size_t batch_normalization_6_variance_bytes,
+ void* conv2d_4_w, size_t conv2d_4_w_bytes,
+ void* batch_normalization_7_gamma, size_t batch_normalization_7_gamma_bytes,
+ void* batch_normalization_7_beta, size_t batch_normalization_7_beta_bytes,
+ void* batch_normalization_7_mean, size_t batch_normalization_7_mean_bytes,
+ void* batch_normalization_7_variance, size_t batch_normalization_7_variance_bytes,
+ void* depthwise_conv2d_4_w, size_t depthwise_conv2d_4_w_bytes,
+ void* batch_normalization_8_gamma, size_t batch_normalization_8_gamma_bytes,
+ void* batch_normalization_8_beta, size_t batch_normalization_8_beta_bytes,
+ void* batch_normalization_8_mean, size_t batch_normalization_8_mean_bytes,
+ void* batch_normalization_8_variance, size_t batch_normalization_8_variance_bytes,
+ void* conv2d_5_w, size_t conv2d_5_w_bytes,
+ void* batch_normalization_9_gamma, size_t batch_normalization_9_gamma_bytes,
+ void* batch_normalization_9_beta, size_t batch_normalization_9_beta_bytes,
+ void* batch_normalization_9_mean, size_t batch_normalization_9_mean_bytes,
+ void* batch_normalization_9_variance, size_t batch_normalization_9_variance_bytes,
+ void* depthwise_conv2d_5_w, size_t depthwise_conv2d_5_w_bytes,
+ void* batch_normalization_10_gamma, size_t batch_normalization_10_gamma_bytes,
+ void* batch_normalization_10_beta, size_t batch_normalization_10_beta_bytes,
+ void* batch_normalization_10_mean, size_t batch_normalization_10_mean_bytes,
+ void* batch_normalization_10_variance, size_t batch_normalization_10_variance_bytes,
+ void* conv2d_6_w, size_t conv2d_6_w_bytes,
+ void* batch_normalization_11_gamma, size_t batch_normalization_11_gamma_bytes,
+ void* batch_normalization_11_beta, size_t batch_normalization_11_beta_bytes,
+ void* batch_normalization_11_mean, size_t batch_normalization_11_mean_bytes,
+ void* batch_normalization_11_variance, size_t batch_normalization_11_variance_bytes,
+ void* depthwise_conv2d_6_w, size_t depthwise_conv2d_6_w_bytes,
+ void* batch_normalization_12_gamma, size_t batch_normalization_12_gamma_bytes,
+ void* batch_normalization_12_beta, size_t batch_normalization_12_beta_bytes,
+ void* batch_normalization_12_mean, size_t batch_normalization_12_mean_bytes,
+ void* batch_normalization_12_variance, size_t batch_normalization_12_variance_bytes,
+ void* conv2d_7_w, size_t conv2d_7_w_bytes,
+ void* batch_normalization_13_gamma, size_t batch_normalization_13_gamma_bytes,
+ void* batch_normalization_13_beta, size_t batch_normalization_13_beta_bytes,
+ void* batch_normalization_13_mean, size_t batch_normalization_13_mean_bytes,
+ void* batch_normalization_13_variance, size_t batch_normalization_13_variance_bytes,
+ void* depthwise_conv2d_7_w, size_t depthwise_conv2d_7_w_bytes,
+ void* batch_normalization_14_gamma, size_t batch_normalization_14_gamma_bytes,
+ void* batch_normalization_14_beta, size_t batch_normalization_14_beta_bytes,
+ void* batch_normalization_14_mean, size_t batch_normalization_14_mean_bytes,
+ void* batch_normalization_14_variance, size_t batch_normalization_14_variance_bytes,
+ void* conv2d_8_w, size_t conv2d_8_w_bytes,
+ void* batch_normalization_15_gamma, size_t batch_normalization_15_gamma_bytes,
+ void* batch_normalization_15_beta, size_t batch_normalization_15_beta_bytes,
+ void* batch_normalization_15_mean, size_t batch_normalization_15_mean_bytes,
+ void* batch_normalization_15_variance, size_t batch_normalization_15_variance_bytes,
+ void* depthwise_conv2d_8_w, size_t depthwise_conv2d_8_w_bytes,
+ void* batch_normalization_16_gamma, size_t batch_normalization_16_gamma_bytes,
+ void* batch_normalization_16_beta, size_t batch_normalization_16_beta_bytes,
+ void* batch_normalization_16_mean, size_t batch_normalization_16_mean_bytes,
+ void* batch_normalization_16_variance, size_t batch_normalization_16_variance_bytes,
+ void* conv2d_9_w, size_t conv2d_9_w_bytes,
+ void* batch_normalization_17_gamma, size_t batch_normalization_17_gamma_bytes,
+ void* batch_normalization_17_beta, size_t batch_normalization_17_beta_bytes,
+ void* batch_normalization_17_mean, size_t batch_normalization_17_mean_bytes,
+ void* batch_normalization_17_variance, size_t batch_normalization_17_variance_bytes,
+ void* depthwise_conv2d_9_w, size_t depthwise_conv2d_9_w_bytes,
+ void* batch_normalization_18_gamma, size_t batch_normalization_18_gamma_bytes,
+ void* batch_normalization_18_beta, size_t batch_normalization_18_beta_bytes,
+ void* batch_normalization_18_mean, size_t batch_normalization_18_mean_bytes,
+ void* batch_normalization_18_variance, size_t batch_normalization_18_variance_bytes,
+ void* conv2d_10_w, size_t conv2d_10_w_bytes,
+ void* batch_normalization_19_gamma, size_t batch_normalization_19_gamma_bytes,
+ void* batch_normalization_19_beta, size_t batch_normalization_19_beta_bytes,
+ void* batch_normalization_19_mean, size_t batch_normalization_19_mean_bytes,
+ void* batch_normalization_19_variance, size_t batch_normalization_19_variance_bytes,
+ void* depthwise_conv2d_10_w, size_t depthwise_conv2d_10_w_bytes,
+ void* batch_normalization_20_gamma, size_t batch_normalization_20_gamma_bytes,
+ void* batch_normalization_20_beta, size_t batch_normalization_20_beta_bytes,
+ void* batch_normalization_20_mean, size_t batch_normalization_20_mean_bytes,
+ void* batch_normalization_20_variance, size_t batch_normalization_20_variance_bytes,
+ void* conv2d_11_w, size_t conv2d_11_w_bytes,
+ void* batch_normalization_21_gamma, size_t batch_normalization_21_gamma_bytes,
+ void* batch_normalization_21_beta, size_t batch_normalization_21_beta_bytes,
+ void* batch_normalization_21_mean, size_t batch_normalization_21_mean_bytes,
+ void* batch_normalization_21_variance, size_t batch_normalization_21_variance_bytes,
+ void* depthwise_conv2d_11_w, size_t depthwise_conv2d_11_w_bytes,
+ void* batch_normalization_22_gamma, size_t batch_normalization_22_gamma_bytes,
+ void* batch_normalization_22_beta, size_t batch_normalization_22_beta_bytes,
+ void* batch_normalization_22_mean, size_t batch_normalization_22_mean_bytes,
+ void* batch_normalization_22_variance, size_t batch_normalization_22_variance_bytes,
+ void* conv2d_12_w, size_t conv2d_12_w_bytes,
+ void* batch_normalization_23_gamma, size_t batch_normalization_23_gamma_bytes,
+ void* batch_normalization_23_beta, size_t batch_normalization_23_beta_bytes,
+ void* batch_normalization_23_mean, size_t batch_normalization_23_mean_bytes,
+ void* batch_normalization_23_variance, size_t batch_normalization_23_variance_bytes,
+ void* depthwise_conv2d_12_w, size_t depthwise_conv2d_12_w_bytes,
+ void* batch_normalization_24_gamma, size_t batch_normalization_24_gamma_bytes,
+ void* batch_normalization_24_beta, size_t batch_normalization_24_beta_bytes,
+ void* batch_normalization_24_mean, size_t batch_normalization_24_mean_bytes,
+ void* batch_normalization_24_variance, size_t batch_normalization_24_variance_bytes,
+ void* conv2d_13_w, size_t conv2d_13_w_bytes,
+ void* batch_normalization_25_gamma, size_t batch_normalization_25_gamma_bytes,
+ void* batch_normalization_25_beta, size_t batch_normalization_25_beta_bytes,
+ void* batch_normalization_25_mean, size_t batch_normalization_25_mean_bytes,
+ void* batch_normalization_25_variance, size_t batch_normalization_25_variance_bytes,
+ void* depthwise_conv2d_13_w, size_t depthwise_conv2d_13_w_bytes,
+ void* batch_normalization_26_gamma, size_t batch_normalization_26_gamma_bytes,
+ void* batch_normalization_26_beta, size_t batch_normalization_26_beta_bytes,
+ void* batch_normalization_26_mean, size_t batch_normalization_26_mean_bytes,
+ void* batch_normalization_26_variance, size_t batch_normalization_26_variance_bytes,
+ void* conv2d_14_w, size_t conv2d_14_w_bytes,
+ void* batch_normalization_27_gamma, size_t batch_normalization_27_gamma_bytes,
+ void* batch_normalization_27_beta, size_t batch_normalization_27_beta_bytes,
+ void* batch_normalization_27_mean, size_t batch_normalization_27_mean_bytes,
+ void* batch_normalization_27_variance, size_t batch_normalization_27_variance_bytes,
+ void* dense_1_w, size_t dense_1_w_bytes,
+ void* dense_1_b, size_t dense_1_b_bytes){
+
+
+ __visc__hint(visc::CPU_TARGET);
+ __visc__attributes(138, input, conv2d_1_w, batch_normalization_1_gamma, batch_normalization_1_beta, batch_normalization_1_mean, batch_normalization_1_variance, depthwise_conv2d_1_w, batch_normalization_2_gamma, batch_normalization_2_beta, batch_normalization_2_mean, batch_normalization_2_variance, conv2d_2_w, batch_normalization_3_gamma, batch_normalization_3_beta, batch_normalization_3_mean, batch_normalization_3_variance, depthwise_conv2d_2_w, batch_normalization_4_gamma, batch_normalization_4_beta, batch_normalization_4_mean, batch_normalization_4_variance, conv2d_3_w, batch_normalization_5_gamma, batch_normalization_5_beta, batch_normalization_5_mean, batch_normalization_5_variance, depthwise_conv2d_3_w, batch_normalization_6_gamma, batch_normalization_6_beta, batch_normalization_6_mean, batch_normalization_6_variance, conv2d_4_w, batch_normalization_7_gamma, batch_normalization_7_beta, batch_normalization_7_mean, batch_normalization_7_variance, depthwise_conv2d_4_w, batch_normalization_8_gamma, batch_normalization_8_beta, batch_normalization_8_mean, batch_normalization_8_variance, conv2d_5_w, batch_normalization_9_gamma, batch_normalization_9_beta, batch_normalization_9_mean, batch_normalization_9_variance, depthwise_conv2d_5_w, batch_normalization_10_gamma, batch_normalization_10_beta, batch_normalization_10_mean, batch_normalization_10_variance, conv2d_6_w, batch_normalization_11_gamma, batch_normalization_11_beta, batch_normalization_11_mean, batch_normalization_11_variance, depthwise_conv2d_6_w, batch_normalization_12_gamma, batch_normalization_12_beta, batch_normalization_12_mean, batch_normalization_12_variance, conv2d_7_w, batch_normalization_13_gamma, batch_normalization_13_beta, batch_normalization_13_mean, batch_normalization_13_variance, depthwise_conv2d_7_w, batch_normalization_14_gamma, batch_normalization_14_beta, batch_normalization_14_mean, batch_normalization_14_variance, conv2d_8_w, batch_normalization_15_gamma, batch_normalization_15_beta, batch_normalization_15_mean, batch_normalization_15_variance, depthwise_conv2d_8_w, batch_normalization_16_gamma, batch_normalization_16_beta, batch_normalization_16_mean, batch_normalization_16_variance, conv2d_9_w, batch_normalization_17_gamma, batch_normalization_17_beta, batch_normalization_17_mean, batch_normalization_17_variance, depthwise_conv2d_9_w, batch_normalization_18_gamma, batch_normalization_18_beta, batch_normalization_18_mean, batch_normalization_18_variance, conv2d_10_w, batch_normalization_19_gamma, batch_normalization_19_beta, batch_normalization_19_mean, batch_normalization_19_variance, depthwise_conv2d_10_w, batch_normalization_20_gamma, batch_normalization_20_beta, batch_normalization_20_mean, batch_normalization_20_variance, conv2d_11_w, batch_normalization_21_gamma, batch_normalization_21_beta, batch_normalization_21_mean, batch_normalization_21_variance, depthwise_conv2d_11_w, batch_normalization_22_gamma, batch_normalization_22_beta, batch_normalization_22_mean, batch_normalization_22_variance, conv2d_12_w, batch_normalization_23_gamma, batch_normalization_23_beta, batch_normalization_23_mean, batch_normalization_23_variance, depthwise_conv2d_12_w, batch_normalization_24_gamma, batch_normalization_24_beta, batch_normalization_24_mean, batch_normalization_24_variance, conv2d_13_w, batch_normalization_25_gamma, batch_normalization_25_beta, batch_normalization_25_mean, batch_normalization_25_variance, depthwise_conv2d_13_w, batch_normalization_26_gamma, batch_normalization_26_beta, batch_normalization_26_mean, batch_normalization_26_variance, conv2d_14_w, batch_normalization_27_gamma, batch_normalization_27_beta, batch_normalization_27_mean, batch_normalization_27_variance, dense_1_w, dense_1_b, 0);
+
+
+ void* var_0 = __visc__createNodeND(0, var_0_node);
+
+ __visc__bindIn(var_0, 0, 0, 0);
+ __visc__bindIn(var_0, 1, 1, 0);
+ __visc__bindIn(var_0, 2, 2, 0);
+ __visc__bindIn(var_0, 3, 3, 0);
+
+ void* var_1 = __visc__createNodeND(0, var_1_node);
+
+ __visc__edge(var_0, var_1, 1, 0, 0, 0);
+ __visc__edge(var_0, var_1, 1, 1, 1, 0);
+ __visc__bindIn(var_1, 4, 2, 0);
+ __visc__bindIn(var_1, 5, 3, 0);
+ __visc__bindIn(var_1, 6, 4, 0);
+ __visc__bindIn(var_1, 7, 5, 0);
+ __visc__bindIn(var_1, 8, 6, 0);
+ __visc__bindIn(var_1, 9, 7, 0);
+ __visc__bindIn(var_1, 10, 8, 0);
+ __visc__bindIn(var_1, 11, 9, 0);
+
+ void* var_2 = __visc__createNodeND(0, var_2_node);
+
+ __visc__edge(var_1, var_2, 1, 0, 0, 0);
+ __visc__edge(var_1, var_2, 1, 1, 1, 0);
+
+ void* var_3 = __visc__createNodeND(0, var_3_node);
+
+ __visc__edge(var_2, var_3, 1, 0, 0, 0);
+ __visc__edge(var_2, var_3, 1, 1, 1, 0);
+ __visc__bindIn(var_3, 12, 2, 0);
+ __visc__bindIn(var_3, 13, 3, 0);
+
+ void* var_4 = __visc__createNodeND(0, var_4_node);
+
+ __visc__edge(var_3, var_4, 1, 0, 0, 0);
+ __visc__edge(var_3, var_4, 1, 1, 1, 0);
+ __visc__bindIn(var_4, 14, 2, 0);
+ __visc__bindIn(var_4, 15, 3, 0);
+ __visc__bindIn(var_4, 16, 4, 0);
+ __visc__bindIn(var_4, 17, 5, 0);
+ __visc__bindIn(var_4, 18, 6, 0);
+ __visc__bindIn(var_4, 19, 7, 0);
+ __visc__bindIn(var_4, 20, 8, 0);
+ __visc__bindIn(var_4, 21, 9, 0);
+
+ void* var_5 = __visc__createNodeND(0, var_5_node);
+
+ __visc__edge(var_4, var_5, 1, 0, 0, 0);
+ __visc__edge(var_4, var_5, 1, 1, 1, 0);
+
+ void* var_6 = __visc__createNodeND(0, var_6_node);
+
+ __visc__edge(var_5, var_6, 1, 0, 0, 0);
+ __visc__edge(var_5, var_6, 1, 1, 1, 0);
+ __visc__bindIn(var_6, 22, 2, 0);
+ __visc__bindIn(var_6, 23, 3, 0);
+
+ void* var_7 = __visc__createNodeND(0, var_7_node);
+
+ __visc__edge(var_6, var_7, 1, 0, 0, 0);
+ __visc__edge(var_6, var_7, 1, 1, 1, 0);
+ __visc__bindIn(var_7, 24, 2, 0);
+ __visc__bindIn(var_7, 25, 3, 0);
+ __visc__bindIn(var_7, 26, 4, 0);
+ __visc__bindIn(var_7, 27, 5, 0);
+ __visc__bindIn(var_7, 28, 6, 0);
+ __visc__bindIn(var_7, 29, 7, 0);
+ __visc__bindIn(var_7, 30, 8, 0);
+ __visc__bindIn(var_7, 31, 9, 0);
+
+ void* var_8 = __visc__createNodeND(0, var_8_node);
+
+ __visc__edge(var_7, var_8, 1, 0, 0, 0);
+ __visc__edge(var_7, var_8, 1, 1, 1, 0);
+
+ void* var_9 = __visc__createNodeND(0, var_9_node);
+
+ __visc__edge(var_8, var_9, 1, 0, 0, 0);
+ __visc__edge(var_8, var_9, 1, 1, 1, 0);
+ __visc__bindIn(var_9, 32, 2, 0);
+ __visc__bindIn(var_9, 33, 3, 0);
+
+ void* var_10 = __visc__createNodeND(0, var_10_node);
+
+ __visc__edge(var_9, var_10, 1, 0, 0, 0);
+ __visc__edge(var_9, var_10, 1, 1, 1, 0);
+ __visc__bindIn(var_10, 34, 2, 0);
+ __visc__bindIn(var_10, 35, 3, 0);
+ __visc__bindIn(var_10, 36, 4, 0);
+ __visc__bindIn(var_10, 37, 5, 0);
+ __visc__bindIn(var_10, 38, 6, 0);
+ __visc__bindIn(var_10, 39, 7, 0);
+ __visc__bindIn(var_10, 40, 8, 0);
+ __visc__bindIn(var_10, 41, 9, 0);
+
+ void* var_11 = __visc__createNodeND(0, var_11_node);
+
+ __visc__edge(var_10, var_11, 1, 0, 0, 0);
+ __visc__edge(var_10, var_11, 1, 1, 1, 0);
+
+ void* var_12 = __visc__createNodeND(0, var_12_node);
+
+ __visc__edge(var_11, var_12, 1, 0, 0, 0);
+ __visc__edge(var_11, var_12, 1, 1, 1, 0);
+ __visc__bindIn(var_12, 42, 2, 0);
+ __visc__bindIn(var_12, 43, 3, 0);
+
+ void* var_13 = __visc__createNodeND(0, var_13_node);
+
+ __visc__edge(var_12, var_13, 1, 0, 0, 0);
+ __visc__edge(var_12, var_13, 1, 1, 1, 0);
+ __visc__bindIn(var_13, 44, 2, 0);
+ __visc__bindIn(var_13, 45, 3, 0);
+ __visc__bindIn(var_13, 46, 4, 0);
+ __visc__bindIn(var_13, 47, 5, 0);
+ __visc__bindIn(var_13, 48, 6, 0);
+ __visc__bindIn(var_13, 49, 7, 0);
+ __visc__bindIn(var_13, 50, 8, 0);
+ __visc__bindIn(var_13, 51, 9, 0);
+
+ void* var_14 = __visc__createNodeND(0, var_14_node);
+
+ __visc__edge(var_13, var_14, 1, 0, 0, 0);
+ __visc__edge(var_13, var_14, 1, 1, 1, 0);
+
+ void* var_15 = __visc__createNodeND(0, var_15_node);
+
+ __visc__edge(var_14, var_15, 1, 0, 0, 0);
+ __visc__edge(var_14, var_15, 1, 1, 1, 0);
+ __visc__bindIn(var_15, 52, 2, 0);
+ __visc__bindIn(var_15, 53, 3, 0);
+
+ void* var_16 = __visc__createNodeND(0, var_16_node);
+
+ __visc__edge(var_15, var_16, 1, 0, 0, 0);
+ __visc__edge(var_15, var_16, 1, 1, 1, 0);
+ __visc__bindIn(var_16, 54, 2, 0);
+ __visc__bindIn(var_16, 55, 3, 0);
+ __visc__bindIn(var_16, 56, 4, 0);
+ __visc__bindIn(var_16, 57, 5, 0);
+ __visc__bindIn(var_16, 58, 6, 0);
+ __visc__bindIn(var_16, 59, 7, 0);
+ __visc__bindIn(var_16, 60, 8, 0);
+ __visc__bindIn(var_16, 61, 9, 0);
+
+ void* var_17 = __visc__createNodeND(0, var_17_node);
+
+ __visc__edge(var_16, var_17, 1, 0, 0, 0);
+ __visc__edge(var_16, var_17, 1, 1, 1, 0);
+
+ void* var_18 = __visc__createNodeND(0, var_18_node);
+
+ __visc__edge(var_17, var_18, 1, 0, 0, 0);
+ __visc__edge(var_17, var_18, 1, 1, 1, 0);
+ __visc__bindIn(var_18, 62, 2, 0);
+ __visc__bindIn(var_18, 63, 3, 0);
+
+ void* var_19 = __visc__createNodeND(0, var_19_node);
+
+ __visc__edge(var_18, var_19, 1, 0, 0, 0);
+ __visc__edge(var_18, var_19, 1, 1, 1, 0);
+ __visc__bindIn(var_19, 64, 2, 0);
+ __visc__bindIn(var_19, 65, 3, 0);
+ __visc__bindIn(var_19, 66, 4, 0);
+ __visc__bindIn(var_19, 67, 5, 0);
+ __visc__bindIn(var_19, 68, 6, 0);
+ __visc__bindIn(var_19, 69, 7, 0);
+ __visc__bindIn(var_19, 70, 8, 0);
+ __visc__bindIn(var_19, 71, 9, 0);
+
+ void* var_20 = __visc__createNodeND(0, var_20_node);
+
+ __visc__edge(var_19, var_20, 1, 0, 0, 0);
+ __visc__edge(var_19, var_20, 1, 1, 1, 0);
+
+ void* var_21 = __visc__createNodeND(0, var_21_node);
+
+ __visc__edge(var_20, var_21, 1, 0, 0, 0);
+ __visc__edge(var_20, var_21, 1, 1, 1, 0);
+ __visc__bindIn(var_21, 72, 2, 0);
+ __visc__bindIn(var_21, 73, 3, 0);
+
+ void* var_22 = __visc__createNodeND(0, var_22_node);
+
+ __visc__edge(var_21, var_22, 1, 0, 0, 0);
+ __visc__edge(var_21, var_22, 1, 1, 1, 0);
+ __visc__bindIn(var_22, 74, 2, 0);
+ __visc__bindIn(var_22, 75, 3, 0);
+ __visc__bindIn(var_22, 76, 4, 0);
+ __visc__bindIn(var_22, 77, 5, 0);
+ __visc__bindIn(var_22, 78, 6, 0);
+ __visc__bindIn(var_22, 79, 7, 0);
+ __visc__bindIn(var_22, 80, 8, 0);
+ __visc__bindIn(var_22, 81, 9, 0);
+
+ void* var_23 = __visc__createNodeND(0, var_23_node);
+
+ __visc__edge(var_22, var_23, 1, 0, 0, 0);
+ __visc__edge(var_22, var_23, 1, 1, 1, 0);
+
+ void* var_24 = __visc__createNodeND(0, var_24_node);
+
+ __visc__edge(var_23, var_24, 1, 0, 0, 0);
+ __visc__edge(var_23, var_24, 1, 1, 1, 0);
+ __visc__bindIn(var_24, 82, 2, 0);
+ __visc__bindIn(var_24, 83, 3, 0);
+
+ void* var_25 = __visc__createNodeND(0, var_25_node);
+
+ __visc__edge(var_24, var_25, 1, 0, 0, 0);
+ __visc__edge(var_24, var_25, 1, 1, 1, 0);
+ __visc__bindIn(var_25, 84, 2, 0);
+ __visc__bindIn(var_25, 85, 3, 0);
+ __visc__bindIn(var_25, 86, 4, 0);
+ __visc__bindIn(var_25, 87, 5, 0);
+ __visc__bindIn(var_25, 88, 6, 0);
+ __visc__bindIn(var_25, 89, 7, 0);
+ __visc__bindIn(var_25, 90, 8, 0);
+ __visc__bindIn(var_25, 91, 9, 0);
+
+ void* var_26 = __visc__createNodeND(0, var_26_node);
+
+ __visc__edge(var_25, var_26, 1, 0, 0, 0);
+ __visc__edge(var_25, var_26, 1, 1, 1, 0);
+
+ void* var_27 = __visc__createNodeND(0, var_27_node);
+
+ __visc__edge(var_26, var_27, 1, 0, 0, 0);
+ __visc__edge(var_26, var_27, 1, 1, 1, 0);
+ __visc__bindIn(var_27, 92, 2, 0);
+ __visc__bindIn(var_27, 93, 3, 0);
+
+ void* var_28 = __visc__createNodeND(0, var_28_node);
+
+ __visc__edge(var_27, var_28, 1, 0, 0, 0);
+ __visc__edge(var_27, var_28, 1, 1, 1, 0);
+ __visc__bindIn(var_28, 94, 2, 0);
+ __visc__bindIn(var_28, 95, 3, 0);
+ __visc__bindIn(var_28, 96, 4, 0);
+ __visc__bindIn(var_28, 97, 5, 0);
+ __visc__bindIn(var_28, 98, 6, 0);
+ __visc__bindIn(var_28, 99, 7, 0);
+ __visc__bindIn(var_28, 100, 8, 0);
+ __visc__bindIn(var_28, 101, 9, 0);
+
+ void* var_29 = __visc__createNodeND(0, var_29_node);
+
+ __visc__edge(var_28, var_29, 1, 0, 0, 0);
+ __visc__edge(var_28, var_29, 1, 1, 1, 0);
+
+ void* var_30 = __visc__createNodeND(0, var_30_node);
+
+ __visc__edge(var_29, var_30, 1, 0, 0, 0);
+ __visc__edge(var_29, var_30, 1, 1, 1, 0);
+ __visc__bindIn(var_30, 102, 2, 0);
+ __visc__bindIn(var_30, 103, 3, 0);
+
+ void* var_31 = __visc__createNodeND(0, var_31_node);
+
+ __visc__edge(var_30, var_31, 1, 0, 0, 0);
+ __visc__edge(var_30, var_31, 1, 1, 1, 0);
+ __visc__bindIn(var_31, 104, 2, 0);
+ __visc__bindIn(var_31, 105, 3, 0);
+ __visc__bindIn(var_31, 106, 4, 0);
+ __visc__bindIn(var_31, 107, 5, 0);
+ __visc__bindIn(var_31, 108, 6, 0);
+ __visc__bindIn(var_31, 109, 7, 0);
+ __visc__bindIn(var_31, 110, 8, 0);
+ __visc__bindIn(var_31, 111, 9, 0);
+
+ void* var_32 = __visc__createNodeND(0, var_32_node);
+
+ __visc__edge(var_31, var_32, 1, 0, 0, 0);
+ __visc__edge(var_31, var_32, 1, 1, 1, 0);
+
+ void* var_33 = __visc__createNodeND(0, var_33_node);
+
+ __visc__edge(var_32, var_33, 1, 0, 0, 0);
+ __visc__edge(var_32, var_33, 1, 1, 1, 0);
+ __visc__bindIn(var_33, 112, 2, 0);
+ __visc__bindIn(var_33, 113, 3, 0);
+
+ void* var_34 = __visc__createNodeND(0, var_34_node);
+
+ __visc__edge(var_33, var_34, 1, 0, 0, 0);
+ __visc__edge(var_33, var_34, 1, 1, 1, 0);
+ __visc__bindIn(var_34, 114, 2, 0);
+ __visc__bindIn(var_34, 115, 3, 0);
+ __visc__bindIn(var_34, 116, 4, 0);
+ __visc__bindIn(var_34, 117, 5, 0);
+ __visc__bindIn(var_34, 118, 6, 0);
+ __visc__bindIn(var_34, 119, 7, 0);
+ __visc__bindIn(var_34, 120, 8, 0);
+ __visc__bindIn(var_34, 121, 9, 0);
+
+ void* var_35 = __visc__createNodeND(0, var_35_node);
+
+ __visc__edge(var_34, var_35, 1, 0, 0, 0);
+ __visc__edge(var_34, var_35, 1, 1, 1, 0);
+
+ void* var_36 = __visc__createNodeND(0, var_36_node);
+
+ __visc__edge(var_35, var_36, 1, 0, 0, 0);
+ __visc__edge(var_35, var_36, 1, 1, 1, 0);
+ __visc__bindIn(var_36, 122, 2, 0);
+ __visc__bindIn(var_36, 123, 3, 0);
+
+ void* var_37 = __visc__createNodeND(0, var_37_node);
+
+ __visc__edge(var_36, var_37, 1, 0, 0, 0);
+ __visc__edge(var_36, var_37, 1, 1, 1, 0);
+ __visc__bindIn(var_37, 124, 2, 0);
+ __visc__bindIn(var_37, 125, 3, 0);
+ __visc__bindIn(var_37, 126, 4, 0);
+ __visc__bindIn(var_37, 127, 5, 0);
+ __visc__bindIn(var_37, 128, 6, 0);
+ __visc__bindIn(var_37, 129, 7, 0);
+ __visc__bindIn(var_37, 130, 8, 0);
+ __visc__bindIn(var_37, 131, 9, 0);
+
+ void* var_38 = __visc__createNodeND(0, var_38_node);
+
+ __visc__edge(var_37, var_38, 1, 0, 0, 0);
+ __visc__edge(var_37, var_38, 1, 1, 1, 0);
+
+ void* var_39 = __visc__createNodeND(0, var_39_node);
+
+ __visc__edge(var_38, var_39, 1, 0, 0, 0);
+ __visc__edge(var_38, var_39, 1, 1, 1, 0);
+ __visc__bindIn(var_39, 132, 2, 0);
+ __visc__bindIn(var_39, 133, 3, 0);
+
+ void* var_40 = __visc__createNodeND(0, var_40_node);
+
+ __visc__edge(var_39, var_40, 1, 0, 0, 0);
+ __visc__edge(var_39, var_40, 1, 1, 1, 0);
+ __visc__bindIn(var_40, 134, 2, 0);
+ __visc__bindIn(var_40, 135, 3, 0);
+ __visc__bindIn(var_40, 136, 4, 0);
+ __visc__bindIn(var_40, 137, 5, 0);
+ __visc__bindIn(var_40, 138, 6, 0);
+ __visc__bindIn(var_40, 139, 7, 0);
+ __visc__bindIn(var_40, 140, 8, 0);
+ __visc__bindIn(var_40, 141, 9, 0);
+
+ void* var_41 = __visc__createNodeND(0, var_41_node);
+
+ __visc__edge(var_40, var_41, 1, 0, 0, 0);
+ __visc__edge(var_40, var_41, 1, 1, 1, 0);
+
+ void* var_42 = __visc__createNodeND(0, var_42_node);
+
+ __visc__edge(var_41, var_42, 1, 0, 0, 0);
+ __visc__edge(var_41, var_42, 1, 1, 1, 0);
+ __visc__bindIn(var_42, 142, 2, 0);
+ __visc__bindIn(var_42, 143, 3, 0);
+
+ void* var_43 = __visc__createNodeND(0, var_43_node);
+
+ __visc__edge(var_42, var_43, 1, 0, 0, 0);
+ __visc__edge(var_42, var_43, 1, 1, 1, 0);
+ __visc__bindIn(var_43, 144, 2, 0);
+ __visc__bindIn(var_43, 145, 3, 0);
+ __visc__bindIn(var_43, 146, 4, 0);
+ __visc__bindIn(var_43, 147, 5, 0);
+ __visc__bindIn(var_43, 148, 6, 0);
+ __visc__bindIn(var_43, 149, 7, 0);
+ __visc__bindIn(var_43, 150, 8, 0);
+ __visc__bindIn(var_43, 151, 9, 0);
+
+ void* var_44 = __visc__createNodeND(0, var_44_node);
+
+ __visc__edge(var_43, var_44, 1, 0, 0, 0);
+ __visc__edge(var_43, var_44, 1, 1, 1, 0);
+
+ void* var_45 = __visc__createNodeND(0, var_45_node);
+
+ __visc__edge(var_44, var_45, 1, 0, 0, 0);
+ __visc__edge(var_44, var_45, 1, 1, 1, 0);
+ __visc__bindIn(var_45, 152, 2, 0);
+ __visc__bindIn(var_45, 153, 3, 0);
+
+ void* var_46 = __visc__createNodeND(0, var_46_node);
+
+ __visc__edge(var_45, var_46, 1, 0, 0, 0);
+ __visc__edge(var_45, var_46, 1, 1, 1, 0);
+ __visc__bindIn(var_46, 154, 2, 0);
+ __visc__bindIn(var_46, 155, 3, 0);
+ __visc__bindIn(var_46, 156, 4, 0);
+ __visc__bindIn(var_46, 157, 5, 0);
+ __visc__bindIn(var_46, 158, 6, 0);
+ __visc__bindIn(var_46, 159, 7, 0);
+ __visc__bindIn(var_46, 160, 8, 0);
+ __visc__bindIn(var_46, 161, 9, 0);
+
+ void* var_47 = __visc__createNodeND(0, var_47_node);
+
+ __visc__edge(var_46, var_47, 1, 0, 0, 0);
+ __visc__edge(var_46, var_47, 1, 1, 1, 0);
+
+ void* var_48 = __visc__createNodeND(0, var_48_node);
+
+ __visc__edge(var_47, var_48, 1, 0, 0, 0);
+ __visc__edge(var_47, var_48, 1, 1, 1, 0);
+ __visc__bindIn(var_48, 162, 2, 0);
+ __visc__bindIn(var_48, 163, 3, 0);
+
+ void* var_49 = __visc__createNodeND(0, var_49_node);
+
+ __visc__edge(var_48, var_49, 1, 0, 0, 0);
+ __visc__edge(var_48, var_49, 1, 1, 1, 0);
+ __visc__bindIn(var_49, 164, 2, 0);
+ __visc__bindIn(var_49, 165, 3, 0);
+ __visc__bindIn(var_49, 166, 4, 0);
+ __visc__bindIn(var_49, 167, 5, 0);
+ __visc__bindIn(var_49, 168, 6, 0);
+ __visc__bindIn(var_49, 169, 7, 0);
+ __visc__bindIn(var_49, 170, 8, 0);
+ __visc__bindIn(var_49, 171, 9, 0);
+
+ void* var_50 = __visc__createNodeND(0, var_50_node);
+
+ __visc__edge(var_49, var_50, 1, 0, 0, 0);
+ __visc__edge(var_49, var_50, 1, 1, 1, 0);
+
+ void* var_51 = __visc__createNodeND(0, var_51_node);
+
+ __visc__edge(var_50, var_51, 1, 0, 0, 0);
+ __visc__edge(var_50, var_51, 1, 1, 1, 0);
+ __visc__bindIn(var_51, 172, 2, 0);
+ __visc__bindIn(var_51, 173, 3, 0);
+
+ void* var_52 = __visc__createNodeND(0, var_52_node);
+
+ __visc__edge(var_51, var_52, 1, 0, 0, 0);
+ __visc__edge(var_51, var_52, 1, 1, 1, 0);
+ __visc__bindIn(var_52, 174, 2, 0);
+ __visc__bindIn(var_52, 175, 3, 0);
+ __visc__bindIn(var_52, 176, 4, 0);
+ __visc__bindIn(var_52, 177, 5, 0);
+ __visc__bindIn(var_52, 178, 6, 0);
+ __visc__bindIn(var_52, 179, 7, 0);
+ __visc__bindIn(var_52, 180, 8, 0);
+ __visc__bindIn(var_52, 181, 9, 0);
+
+ void* var_53 = __visc__createNodeND(0, var_53_node);
+
+ __visc__edge(var_52, var_53, 1, 0, 0, 0);
+ __visc__edge(var_52, var_53, 1, 1, 1, 0);
+
+ void* var_54 = __visc__createNodeND(0, var_54_node);
+
+ __visc__edge(var_53, var_54, 1, 0, 0, 0);
+ __visc__edge(var_53, var_54, 1, 1, 1, 0);
+ __visc__bindIn(var_54, 182, 2, 0);
+ __visc__bindIn(var_54, 183, 3, 0);
+
+ void* var_55 = __visc__createNodeND(0, var_55_node);
+
+ __visc__edge(var_54, var_55, 1, 0, 0, 0);
+ __visc__edge(var_54, var_55, 1, 1, 1, 0);
+ __visc__bindIn(var_55, 184, 2, 0);
+ __visc__bindIn(var_55, 185, 3, 0);
+ __visc__bindIn(var_55, 186, 4, 0);
+ __visc__bindIn(var_55, 187, 5, 0);
+ __visc__bindIn(var_55, 188, 6, 0);
+ __visc__bindIn(var_55, 189, 7, 0);
+ __visc__bindIn(var_55, 190, 8, 0);
+ __visc__bindIn(var_55, 191, 9, 0);
+
+ void* var_56 = __visc__createNodeND(0, var_56_node);
+
+ __visc__edge(var_55, var_56, 1, 0, 0, 0);
+ __visc__edge(var_55, var_56, 1, 1, 1, 0);
+
+ void* var_57 = __visc__createNodeND(0, var_57_node);
+
+ __visc__edge(var_56, var_57, 1, 0, 0, 0);
+ __visc__edge(var_56, var_57, 1, 1, 1, 0);
+ __visc__bindIn(var_57, 192, 2, 0);
+ __visc__bindIn(var_57, 193, 3, 0);
+
+ void* var_58 = __visc__createNodeND(0, var_58_node);
+
+ __visc__edge(var_57, var_58, 1, 0, 0, 0);
+ __visc__edge(var_57, var_58, 1, 1, 1, 0);
+ __visc__bindIn(var_58, 194, 2, 0);
+ __visc__bindIn(var_58, 195, 3, 0);
+ __visc__bindIn(var_58, 196, 4, 0);
+ __visc__bindIn(var_58, 197, 5, 0);
+ __visc__bindIn(var_58, 198, 6, 0);
+ __visc__bindIn(var_58, 199, 7, 0);
+ __visc__bindIn(var_58, 200, 8, 0);
+ __visc__bindIn(var_58, 201, 9, 0);
+
+ void* var_59 = __visc__createNodeND(0, var_59_node);
+
+ __visc__edge(var_58, var_59, 1, 0, 0, 0);
+ __visc__edge(var_58, var_59, 1, 1, 1, 0);
+
+ void* var_60 = __visc__createNodeND(0, var_60_node);
+
+ __visc__edge(var_59, var_60, 1, 0, 0, 0);
+ __visc__edge(var_59, var_60, 1, 1, 1, 0);
+ __visc__bindIn(var_60, 202, 2, 0);
+ __visc__bindIn(var_60, 203, 3, 0);
+
+ void* var_61 = __visc__createNodeND(0, var_61_node);
+
+ __visc__edge(var_60, var_61, 1, 0, 0, 0);
+ __visc__edge(var_60, var_61, 1, 1, 1, 0);
+ __visc__bindIn(var_61, 204, 2, 0);
+ __visc__bindIn(var_61, 205, 3, 0);
+ __visc__bindIn(var_61, 206, 4, 0);
+ __visc__bindIn(var_61, 207, 5, 0);
+ __visc__bindIn(var_61, 208, 6, 0);
+ __visc__bindIn(var_61, 209, 7, 0);
+ __visc__bindIn(var_61, 210, 8, 0);
+ __visc__bindIn(var_61, 211, 9, 0);
+
+ void* var_62 = __visc__createNodeND(0, var_62_node);
+
+ __visc__edge(var_61, var_62, 1, 0, 0, 0);
+ __visc__edge(var_61, var_62, 1, 1, 1, 0);
+
+ void* var_63 = __visc__createNodeND(0, var_63_node);
+
+ __visc__edge(var_62, var_63, 1, 0, 0, 0);
+ __visc__edge(var_62, var_63, 1, 1, 1, 0);
+ __visc__bindIn(var_63, 212, 2, 0);
+ __visc__bindIn(var_63, 213, 3, 0);
+
+ void* var_64 = __visc__createNodeND(0, var_64_node);
+
+ __visc__edge(var_63, var_64, 1, 0, 0, 0);
+ __visc__edge(var_63, var_64, 1, 1, 1, 0);
+ __visc__bindIn(var_64, 214, 2, 0);
+ __visc__bindIn(var_64, 215, 3, 0);
+ __visc__bindIn(var_64, 216, 4, 0);
+ __visc__bindIn(var_64, 217, 5, 0);
+ __visc__bindIn(var_64, 218, 6, 0);
+ __visc__bindIn(var_64, 219, 7, 0);
+ __visc__bindIn(var_64, 220, 8, 0);
+ __visc__bindIn(var_64, 221, 9, 0);
+
+ void* var_65 = __visc__createNodeND(0, var_65_node);
+
+ __visc__edge(var_64, var_65, 1, 0, 0, 0);
+ __visc__edge(var_64, var_65, 1, 1, 1, 0);
+
+ void* var_66 = __visc__createNodeND(0, var_66_node);
+
+ __visc__edge(var_65, var_66, 1, 0, 0, 0);
+ __visc__edge(var_65, var_66, 1, 1, 1, 0);
+ __visc__bindIn(var_66, 222, 2, 0);
+ __visc__bindIn(var_66, 223, 3, 0);
+
+ void* var_67 = __visc__createNodeND(0, var_67_node);
+
+ __visc__edge(var_66, var_67, 1, 0, 0, 0);
+ __visc__edge(var_66, var_67, 1, 1, 1, 0);
+ __visc__bindIn(var_67, 224, 2, 0);
+ __visc__bindIn(var_67, 225, 3, 0);
+ __visc__bindIn(var_67, 226, 4, 0);
+ __visc__bindIn(var_67, 227, 5, 0);
+ __visc__bindIn(var_67, 228, 6, 0);
+ __visc__bindIn(var_67, 229, 7, 0);
+ __visc__bindIn(var_67, 230, 8, 0);
+ __visc__bindIn(var_67, 231, 9, 0);
+
+ void* var_68 = __visc__createNodeND(0, var_68_node);
+
+ __visc__edge(var_67, var_68, 1, 0, 0, 0);
+ __visc__edge(var_67, var_68, 1, 1, 1, 0);
+
+ void* var_69 = __visc__createNodeND(0, var_69_node);
+
+ __visc__edge(var_68, var_69, 1, 0, 0, 0);
+ __visc__edge(var_68, var_69, 1, 1, 1, 0);
+ __visc__bindIn(var_69, 232, 2, 0);
+ __visc__bindIn(var_69, 233, 3, 0);
+
+ void* var_70 = __visc__createNodeND(0, var_70_node);
+
+ __visc__edge(var_69, var_70, 1, 0, 0, 0);
+ __visc__edge(var_69, var_70, 1, 1, 1, 0);
+ __visc__bindIn(var_70, 234, 2, 0);
+ __visc__bindIn(var_70, 235, 3, 0);
+ __visc__bindIn(var_70, 236, 4, 0);
+ __visc__bindIn(var_70, 237, 5, 0);
+ __visc__bindIn(var_70, 238, 6, 0);
+ __visc__bindIn(var_70, 239, 7, 0);
+ __visc__bindIn(var_70, 240, 8, 0);
+ __visc__bindIn(var_70, 241, 9, 0);
+
+ void* var_71 = __visc__createNodeND(0, var_71_node);
+
+ __visc__edge(var_70, var_71, 1, 0, 0, 0);
+ __visc__edge(var_70, var_71, 1, 1, 1, 0);
+
+ void* var_72 = __visc__createNodeND(0, var_72_node);
+
+ __visc__edge(var_71, var_72, 1, 0, 0, 0);
+ __visc__edge(var_71, var_72, 1, 1, 1, 0);
+ __visc__bindIn(var_72, 242, 2, 0);
+ __visc__bindIn(var_72, 243, 3, 0);
+
+ void* var_73 = __visc__createNodeND(0, var_73_node);
+
+ __visc__edge(var_72, var_73, 1, 0, 0, 0);
+ __visc__edge(var_72, var_73, 1, 1, 1, 0);
+ __visc__bindIn(var_73, 244, 2, 0);
+ __visc__bindIn(var_73, 245, 3, 0);
+ __visc__bindIn(var_73, 246, 4, 0);
+ __visc__bindIn(var_73, 247, 5, 0);
+ __visc__bindIn(var_73, 248, 6, 0);
+ __visc__bindIn(var_73, 249, 7, 0);
+ __visc__bindIn(var_73, 250, 8, 0);
+ __visc__bindIn(var_73, 251, 9, 0);
+
+ void* var_74 = __visc__createNodeND(0, var_74_node);
+
+ __visc__edge(var_73, var_74, 1, 0, 0, 0);
+ __visc__edge(var_73, var_74, 1, 1, 1, 0);
+
+ void* var_75 = __visc__createNodeND(0, var_75_node);
+
+ __visc__edge(var_74, var_75, 1, 0, 0, 0);
+ __visc__edge(var_74, var_75, 1, 1, 1, 0);
+ __visc__bindIn(var_75, 252, 2, 0);
+ __visc__bindIn(var_75, 253, 3, 0);
+
+ void* var_76 = __visc__createNodeND(0, var_76_node);
+
+ __visc__edge(var_75, var_76, 1, 0, 0, 0);
+ __visc__edge(var_75, var_76, 1, 1, 1, 0);
+ __visc__bindIn(var_76, 254, 2, 0);
+ __visc__bindIn(var_76, 255, 3, 0);
+ __visc__bindIn(var_76, 256, 4, 0);
+ __visc__bindIn(var_76, 257, 5, 0);
+ __visc__bindIn(var_76, 258, 6, 0);
+ __visc__bindIn(var_76, 259, 7, 0);
+ __visc__bindIn(var_76, 260, 8, 0);
+ __visc__bindIn(var_76, 261, 9, 0);
+
+ void* var_77 = __visc__createNodeND(0, var_77_node);
+
+ __visc__edge(var_76, var_77, 1, 0, 0, 0);
+ __visc__edge(var_76, var_77, 1, 1, 1, 0);
+
+ void* var_78 = __visc__createNodeND(0, var_78_node);
+
+ __visc__edge(var_77, var_78, 1, 0, 0, 0);
+ __visc__edge(var_77, var_78, 1, 1, 1, 0);
+ __visc__bindIn(var_78, 262, 2, 0);
+ __visc__bindIn(var_78, 263, 3, 0);
+
+ void* var_79 = __visc__createNodeND(0, var_79_node);
+
+ __visc__edge(var_78, var_79, 1, 0, 0, 0);
+ __visc__edge(var_78, var_79, 1, 1, 1, 0);
+ __visc__bindIn(var_79, 264, 2, 0);
+ __visc__bindIn(var_79, 265, 3, 0);
+ __visc__bindIn(var_79, 266, 4, 0);
+ __visc__bindIn(var_79, 267, 5, 0);
+ __visc__bindIn(var_79, 268, 6, 0);
+ __visc__bindIn(var_79, 269, 7, 0);
+ __visc__bindIn(var_79, 270, 8, 0);
+ __visc__bindIn(var_79, 271, 9, 0);
+
+ void* var_80 = __visc__createNodeND(0, var_80_node);
+
+ __visc__edge(var_79, var_80, 1, 0, 0, 0);
+ __visc__edge(var_79, var_80, 1, 1, 1, 0);
+
+ void* var_81 = __visc__createNodeND(0, var_81_node);
+
+ __visc__edge(var_80, var_81, 1, 0, 0, 0);
+ __visc__edge(var_80, var_81, 1, 1, 1, 0);
+
+ void* var_82 = __visc__createNodeND(0, var_82_node);
+
+ __visc__edge(var_81, var_82, 1, 0, 0, 0);
+ __visc__edge(var_81, var_82, 1, 1, 1, 0);
+ __visc__bindIn(var_82, 272, 2, 0);
+ __visc__bindIn(var_82, 273, 3, 0);
+
+ void* var_83 = __visc__createNodeND(0, var_83_node);
+
+ __visc__edge(var_82, var_83, 1, 0, 0, 0);
+ __visc__edge(var_82, var_83, 1, 1, 1, 0);
+ __visc__bindIn(var_83, 274, 2, 0);
+ __visc__bindIn(var_83, 275, 3, 0);
+
+ void* var_84 = __visc__createNodeND(0, var_84_node);
+
+ __visc__edge(var_83, var_84, 1, 0, 0, 0);
+ __visc__edge(var_83, var_84, 1, 1, 1, 0);
+
+ __visc__bindOut(var_84, 0, 0, 0);
+ __visc__bindOut(var_84, 1, 1, 0);
+
+}
+
+struct ret_t {
+ void* tensor;
+ size_t bytes;
+};
+
+typedef struct __attribute__((__packed__)) {
+ void* input;
+ size_t input_bytes;
+ void* conv2d_1_w;
+ size_t conv2d_1_w_bytes;
+ void* batch_normalization_1_gamma;
+ size_t batch_normalization_1_gamma_bytes;
+ void* batch_normalization_1_beta;
+ size_t batch_normalization_1_beta_bytes;
+ void* batch_normalization_1_mean;
+ size_t batch_normalization_1_mean_bytes;
+ void* batch_normalization_1_variance;
+ size_t batch_normalization_1_variance_bytes;
+ void* depthwise_conv2d_1_w;
+ size_t depthwise_conv2d_1_w_bytes;
+ void* batch_normalization_2_gamma;
+ size_t batch_normalization_2_gamma_bytes;
+ void* batch_normalization_2_beta;
+ size_t batch_normalization_2_beta_bytes;
+ void* batch_normalization_2_mean;
+ size_t batch_normalization_2_mean_bytes;
+ void* batch_normalization_2_variance;
+ size_t batch_normalization_2_variance_bytes;
+ void* conv2d_2_w;
+ size_t conv2d_2_w_bytes;
+ void* batch_normalization_3_gamma;
+ size_t batch_normalization_3_gamma_bytes;
+ void* batch_normalization_3_beta;
+ size_t batch_normalization_3_beta_bytes;
+ void* batch_normalization_3_mean;
+ size_t batch_normalization_3_mean_bytes;
+ void* batch_normalization_3_variance;
+ size_t batch_normalization_3_variance_bytes;
+ void* depthwise_conv2d_2_w;
+ size_t depthwise_conv2d_2_w_bytes;
+ void* batch_normalization_4_gamma;
+ size_t batch_normalization_4_gamma_bytes;
+ void* batch_normalization_4_beta;
+ size_t batch_normalization_4_beta_bytes;
+ void* batch_normalization_4_mean;
+ size_t batch_normalization_4_mean_bytes;
+ void* batch_normalization_4_variance;
+ size_t batch_normalization_4_variance_bytes;
+ void* conv2d_3_w;
+ size_t conv2d_3_w_bytes;
+ void* batch_normalization_5_gamma;
+ size_t batch_normalization_5_gamma_bytes;
+ void* batch_normalization_5_beta;
+ size_t batch_normalization_5_beta_bytes;
+ void* batch_normalization_5_mean;
+ size_t batch_normalization_5_mean_bytes;
+ void* batch_normalization_5_variance;
+ size_t batch_normalization_5_variance_bytes;
+ void* depthwise_conv2d_3_w;
+ size_t depthwise_conv2d_3_w_bytes;
+ void* batch_normalization_6_gamma;
+ size_t batch_normalization_6_gamma_bytes;
+ void* batch_normalization_6_beta;
+ size_t batch_normalization_6_beta_bytes;
+ void* batch_normalization_6_mean;
+ size_t batch_normalization_6_mean_bytes;
+ void* batch_normalization_6_variance;
+ size_t batch_normalization_6_variance_bytes;
+ void* conv2d_4_w;
+ size_t conv2d_4_w_bytes;
+ void* batch_normalization_7_gamma;
+ size_t batch_normalization_7_gamma_bytes;
+ void* batch_normalization_7_beta;
+ size_t batch_normalization_7_beta_bytes;
+ void* batch_normalization_7_mean;
+ size_t batch_normalization_7_mean_bytes;
+ void* batch_normalization_7_variance;
+ size_t batch_normalization_7_variance_bytes;
+ void* depthwise_conv2d_4_w;
+ size_t depthwise_conv2d_4_w_bytes;
+ void* batch_normalization_8_gamma;
+ size_t batch_normalization_8_gamma_bytes;
+ void* batch_normalization_8_beta;
+ size_t batch_normalization_8_beta_bytes;
+ void* batch_normalization_8_mean;
+ size_t batch_normalization_8_mean_bytes;
+ void* batch_normalization_8_variance;
+ size_t batch_normalization_8_variance_bytes;
+ void* conv2d_5_w;
+ size_t conv2d_5_w_bytes;
+ void* batch_normalization_9_gamma;
+ size_t batch_normalization_9_gamma_bytes;
+ void* batch_normalization_9_beta;
+ size_t batch_normalization_9_beta_bytes;
+ void* batch_normalization_9_mean;
+ size_t batch_normalization_9_mean_bytes;
+ void* batch_normalization_9_variance;
+ size_t batch_normalization_9_variance_bytes;
+ void* depthwise_conv2d_5_w;
+ size_t depthwise_conv2d_5_w_bytes;
+ void* batch_normalization_10_gamma;
+ size_t batch_normalization_10_gamma_bytes;
+ void* batch_normalization_10_beta;
+ size_t batch_normalization_10_beta_bytes;
+ void* batch_normalization_10_mean;
+ size_t batch_normalization_10_mean_bytes;
+ void* batch_normalization_10_variance;
+ size_t batch_normalization_10_variance_bytes;
+ void* conv2d_6_w;
+ size_t conv2d_6_w_bytes;
+ void* batch_normalization_11_gamma;
+ size_t batch_normalization_11_gamma_bytes;
+ void* batch_normalization_11_beta;
+ size_t batch_normalization_11_beta_bytes;
+ void* batch_normalization_11_mean;
+ size_t batch_normalization_11_mean_bytes;
+ void* batch_normalization_11_variance;
+ size_t batch_normalization_11_variance_bytes;
+ void* depthwise_conv2d_6_w;
+ size_t depthwise_conv2d_6_w_bytes;
+ void* batch_normalization_12_gamma;
+ size_t batch_normalization_12_gamma_bytes;
+ void* batch_normalization_12_beta;
+ size_t batch_normalization_12_beta_bytes;
+ void* batch_normalization_12_mean;
+ size_t batch_normalization_12_mean_bytes;
+ void* batch_normalization_12_variance;
+ size_t batch_normalization_12_variance_bytes;
+ void* conv2d_7_w;
+ size_t conv2d_7_w_bytes;
+ void* batch_normalization_13_gamma;
+ size_t batch_normalization_13_gamma_bytes;
+ void* batch_normalization_13_beta;
+ size_t batch_normalization_13_beta_bytes;
+ void* batch_normalization_13_mean;
+ size_t batch_normalization_13_mean_bytes;
+ void* batch_normalization_13_variance;
+ size_t batch_normalization_13_variance_bytes;
+ void* depthwise_conv2d_7_w;
+ size_t depthwise_conv2d_7_w_bytes;
+ void* batch_normalization_14_gamma;
+ size_t batch_normalization_14_gamma_bytes;
+ void* batch_normalization_14_beta;
+ size_t batch_normalization_14_beta_bytes;
+ void* batch_normalization_14_mean;
+ size_t batch_normalization_14_mean_bytes;
+ void* batch_normalization_14_variance;
+ size_t batch_normalization_14_variance_bytes;
+ void* conv2d_8_w;
+ size_t conv2d_8_w_bytes;
+ void* batch_normalization_15_gamma;
+ size_t batch_normalization_15_gamma_bytes;
+ void* batch_normalization_15_beta;
+ size_t batch_normalization_15_beta_bytes;
+ void* batch_normalization_15_mean;
+ size_t batch_normalization_15_mean_bytes;
+ void* batch_normalization_15_variance;
+ size_t batch_normalization_15_variance_bytes;
+ void* depthwise_conv2d_8_w;
+ size_t depthwise_conv2d_8_w_bytes;
+ void* batch_normalization_16_gamma;
+ size_t batch_normalization_16_gamma_bytes;
+ void* batch_normalization_16_beta;
+ size_t batch_normalization_16_beta_bytes;
+ void* batch_normalization_16_mean;
+ size_t batch_normalization_16_mean_bytes;
+ void* batch_normalization_16_variance;
+ size_t batch_normalization_16_variance_bytes;
+ void* conv2d_9_w;
+ size_t conv2d_9_w_bytes;
+ void* batch_normalization_17_gamma;
+ size_t batch_normalization_17_gamma_bytes;
+ void* batch_normalization_17_beta;
+ size_t batch_normalization_17_beta_bytes;
+ void* batch_normalization_17_mean;
+ size_t batch_normalization_17_mean_bytes;
+ void* batch_normalization_17_variance;
+ size_t batch_normalization_17_variance_bytes;
+ void* depthwise_conv2d_9_w;
+ size_t depthwise_conv2d_9_w_bytes;
+ void* batch_normalization_18_gamma;
+ size_t batch_normalization_18_gamma_bytes;
+ void* batch_normalization_18_beta;
+ size_t batch_normalization_18_beta_bytes;
+ void* batch_normalization_18_mean;
+ size_t batch_normalization_18_mean_bytes;
+ void* batch_normalization_18_variance;
+ size_t batch_normalization_18_variance_bytes;
+ void* conv2d_10_w;
+ size_t conv2d_10_w_bytes;
+ void* batch_normalization_19_gamma;
+ size_t batch_normalization_19_gamma_bytes;
+ void* batch_normalization_19_beta;
+ size_t batch_normalization_19_beta_bytes;
+ void* batch_normalization_19_mean;
+ size_t batch_normalization_19_mean_bytes;
+ void* batch_normalization_19_variance;
+ size_t batch_normalization_19_variance_bytes;
+ void* depthwise_conv2d_10_w;
+ size_t depthwise_conv2d_10_w_bytes;
+ void* batch_normalization_20_gamma;
+ size_t batch_normalization_20_gamma_bytes;
+ void* batch_normalization_20_beta;
+ size_t batch_normalization_20_beta_bytes;
+ void* batch_normalization_20_mean;
+ size_t batch_normalization_20_mean_bytes;
+ void* batch_normalization_20_variance;
+ size_t batch_normalization_20_variance_bytes;
+ void* conv2d_11_w;
+ size_t conv2d_11_w_bytes;
+ void* batch_normalization_21_gamma;
+ size_t batch_normalization_21_gamma_bytes;
+ void* batch_normalization_21_beta;
+ size_t batch_normalization_21_beta_bytes;
+ void* batch_normalization_21_mean;
+ size_t batch_normalization_21_mean_bytes;
+ void* batch_normalization_21_variance;
+ size_t batch_normalization_21_variance_bytes;
+ void* depthwise_conv2d_11_w;
+ size_t depthwise_conv2d_11_w_bytes;
+ void* batch_normalization_22_gamma;
+ size_t batch_normalization_22_gamma_bytes;
+ void* batch_normalization_22_beta;
+ size_t batch_normalization_22_beta_bytes;
+ void* batch_normalization_22_mean;
+ size_t batch_normalization_22_mean_bytes;
+ void* batch_normalization_22_variance;
+ size_t batch_normalization_22_variance_bytes;
+ void* conv2d_12_w;
+ size_t conv2d_12_w_bytes;
+ void* batch_normalization_23_gamma;
+ size_t batch_normalization_23_gamma_bytes;
+ void* batch_normalization_23_beta;
+ size_t batch_normalization_23_beta_bytes;
+ void* batch_normalization_23_mean;
+ size_t batch_normalization_23_mean_bytes;
+ void* batch_normalization_23_variance;
+ size_t batch_normalization_23_variance_bytes;
+ void* depthwise_conv2d_12_w;
+ size_t depthwise_conv2d_12_w_bytes;
+ void* batch_normalization_24_gamma;
+ size_t batch_normalization_24_gamma_bytes;
+ void* batch_normalization_24_beta;
+ size_t batch_normalization_24_beta_bytes;
+ void* batch_normalization_24_mean;
+ size_t batch_normalization_24_mean_bytes;
+ void* batch_normalization_24_variance;
+ size_t batch_normalization_24_variance_bytes;
+ void* conv2d_13_w;
+ size_t conv2d_13_w_bytes;
+ void* batch_normalization_25_gamma;
+ size_t batch_normalization_25_gamma_bytes;
+ void* batch_normalization_25_beta;
+ size_t batch_normalization_25_beta_bytes;
+ void* batch_normalization_25_mean;
+ size_t batch_normalization_25_mean_bytes;
+ void* batch_normalization_25_variance;
+ size_t batch_normalization_25_variance_bytes;
+ void* depthwise_conv2d_13_w;
+ size_t depthwise_conv2d_13_w_bytes;
+ void* batch_normalization_26_gamma;
+ size_t batch_normalization_26_gamma_bytes;
+ void* batch_normalization_26_beta;
+ size_t batch_normalization_26_beta_bytes;
+ void* batch_normalization_26_mean;
+ size_t batch_normalization_26_mean_bytes;
+ void* batch_normalization_26_variance;
+ size_t batch_normalization_26_variance_bytes;
+ void* conv2d_14_w;
+ size_t conv2d_14_w_bytes;
+ void* batch_normalization_27_gamma;
+ size_t batch_normalization_27_gamma_bytes;
+ void* batch_normalization_27_beta;
+ size_t batch_normalization_27_beta_bytes;
+ void* batch_normalization_27_mean;
+ size_t batch_normalization_27_mean_bytes;
+ void* batch_normalization_27_variance;
+ size_t batch_normalization_27_variance_bytes;
+ void* dense_1_w;
+ size_t dense_1_w_bytes;
+ void* dense_1_b;
+ size_t dense_1_b_bytes;
+
+ struct ret_t r;
+}
+RootIn;
+
+int main(){
+
+std::string dir_prefix = std::string("data/mobilenet_quant/");
+std::string input_path = dir_prefix + std::string("input.bin");
+std::string labels_path = dir_prefix + std::string("labels.bin");
+std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
+void* conv2d_1_w = readTrainedWeights(conv2d_1_w_path.c_str(), 0,32,3,3,3);
+std::string batch_normalization_1_gamma_path = dir_prefix + std::string("batch_normalization_1_gamma.bin");
+void* batch_normalization_1_gamma = readTrainedWeights(batch_normalization_1_gamma_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_1_beta_path = dir_prefix + std::string("batch_normalization_1_beta.bin");
+void* batch_normalization_1_beta = readTrainedWeights(batch_normalization_1_beta_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_1_mean_path = dir_prefix + std::string("batch_normalization_1_mean.bin");
+void* batch_normalization_1_mean = readTrainedWeights(batch_normalization_1_mean_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_1_variance_path = dir_prefix + std::string("batch_normalization_1_variance.bin");
+void* batch_normalization_1_variance = readTrainedWeights(batch_normalization_1_variance_path.c_str(), 0,1,32,1,1);
+std::string depthwise_conv2d_1_w_path = dir_prefix + std::string("depthwise_conv2d_1_w.bin");
+void* depthwise_conv2d_1_w = readTrainedWeights(depthwise_conv2d_1_w_path.c_str(), 0,32,1,3,3);
+std::string batch_normalization_2_gamma_path = dir_prefix + std::string("batch_normalization_2_gamma.bin");
+void* batch_normalization_2_gamma = readTrainedWeights(batch_normalization_2_gamma_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_2_beta_path = dir_prefix + std::string("batch_normalization_2_beta.bin");
+void* batch_normalization_2_beta = readTrainedWeights(batch_normalization_2_beta_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_2_mean_path = dir_prefix + std::string("batch_normalization_2_mean.bin");
+void* batch_normalization_2_mean = readTrainedWeights(batch_normalization_2_mean_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_2_variance_path = dir_prefix + std::string("batch_normalization_2_variance.bin");
+void* batch_normalization_2_variance = readTrainedWeights(batch_normalization_2_variance_path.c_str(), 0,1,32,1,1);
+std::string conv2d_2_w_path = dir_prefix + std::string("conv2d_2_w.bin");
+void* conv2d_2_w = readTrainedWeights(conv2d_2_w_path.c_str(), 0,64,32,1,1);
+std::string batch_normalization_3_gamma_path = dir_prefix + std::string("batch_normalization_3_gamma.bin");
+void* batch_normalization_3_gamma = readTrainedWeights(batch_normalization_3_gamma_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_3_beta_path = dir_prefix + std::string("batch_normalization_3_beta.bin");
+void* batch_normalization_3_beta = readTrainedWeights(batch_normalization_3_beta_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_3_mean_path = dir_prefix + std::string("batch_normalization_3_mean.bin");
+void* batch_normalization_3_mean = readTrainedWeights(batch_normalization_3_mean_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_3_variance_path = dir_prefix + std::string("batch_normalization_3_variance.bin");
+void* batch_normalization_3_variance = readTrainedWeights(batch_normalization_3_variance_path.c_str(), 0,1,64,1,1);
+std::string depthwise_conv2d_2_w_path = dir_prefix + std::string("depthwise_conv2d_2_w.bin");
+void* depthwise_conv2d_2_w = readTrainedWeights(depthwise_conv2d_2_w_path.c_str(), 0,64,1,3,3);
+std::string batch_normalization_4_gamma_path = dir_prefix + std::string("batch_normalization_4_gamma.bin");
+void* batch_normalization_4_gamma = readTrainedWeights(batch_normalization_4_gamma_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_4_beta_path = dir_prefix + std::string("batch_normalization_4_beta.bin");
+void* batch_normalization_4_beta = readTrainedWeights(batch_normalization_4_beta_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_4_mean_path = dir_prefix + std::string("batch_normalization_4_mean.bin");
+void* batch_normalization_4_mean = readTrainedWeights(batch_normalization_4_mean_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_4_variance_path = dir_prefix + std::string("batch_normalization_4_variance.bin");
+void* batch_normalization_4_variance = readTrainedWeights(batch_normalization_4_variance_path.c_str(), 0,1,64,1,1);
+std::string conv2d_3_w_path = dir_prefix + std::string("conv2d_3_w.bin");
+void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,128,64,1,1);
+std::string batch_normalization_5_gamma_path = dir_prefix + std::string("batch_normalization_5_gamma.bin");
+void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_5_beta_path = dir_prefix + std::string("batch_normalization_5_beta.bin");
+void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_5_mean_path = dir_prefix + std::string("batch_normalization_5_mean.bin");
+void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_5_variance_path = dir_prefix + std::string("batch_normalization_5_variance.bin");
+void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,128,1,1);
+std::string depthwise_conv2d_3_w_path = dir_prefix + std::string("depthwise_conv2d_3_w.bin");
+void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,128,1,3,3);
+std::string batch_normalization_6_gamma_path = dir_prefix + std::string("batch_normalization_6_gamma.bin");
+void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_6_beta_path = dir_prefix + std::string("batch_normalization_6_beta.bin");
+void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_6_mean_path = dir_prefix + std::string("batch_normalization_6_mean.bin");
+void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_6_variance_path = dir_prefix + std::string("batch_normalization_6_variance.bin");
+void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,128,1,1);
+std::string conv2d_4_w_path = dir_prefix + std::string("conv2d_4_w.bin");
+void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,128,1,1);
+std::string batch_normalization_7_gamma_path = dir_prefix + std::string("batch_normalization_7_gamma.bin");
+void* batch_normalization_7_gamma = readTrainedWeights(batch_normalization_7_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_7_beta_path = dir_prefix + std::string("batch_normalization_7_beta.bin");
+void* batch_normalization_7_beta = readTrainedWeights(batch_normalization_7_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_7_mean_path = dir_prefix + std::string("batch_normalization_7_mean.bin");
+void* batch_normalization_7_mean = readTrainedWeights(batch_normalization_7_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_7_variance_path = dir_prefix + std::string("batch_normalization_7_variance.bin");
+void* batch_normalization_7_variance = readTrainedWeights(batch_normalization_7_variance_path.c_str(), 0,1,128,1,1);
+std::string depthwise_conv2d_4_w_path = dir_prefix + std::string("depthwise_conv2d_4_w.bin");
+void* depthwise_conv2d_4_w = readTrainedWeights(depthwise_conv2d_4_w_path.c_str(), 0,128,1,3,3);
+std::string batch_normalization_8_gamma_path = dir_prefix + std::string("batch_normalization_8_gamma.bin");
+void* batch_normalization_8_gamma = readTrainedWeights(batch_normalization_8_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_8_beta_path = dir_prefix + std::string("batch_normalization_8_beta.bin");
+void* batch_normalization_8_beta = readTrainedWeights(batch_normalization_8_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_8_mean_path = dir_prefix + std::string("batch_normalization_8_mean.bin");
+void* batch_normalization_8_mean = readTrainedWeights(batch_normalization_8_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_8_variance_path = dir_prefix + std::string("batch_normalization_8_variance.bin");
+void* batch_normalization_8_variance = readTrainedWeights(batch_normalization_8_variance_path.c_str(), 0,1,128,1,1);
+std::string conv2d_5_w_path = dir_prefix + std::string("conv2d_5_w.bin");
+void* conv2d_5_w = readTrainedWeights(conv2d_5_w_path.c_str(), 0,256,128,1,1);
+std::string batch_normalization_9_gamma_path = dir_prefix + std::string("batch_normalization_9_gamma.bin");
+void* batch_normalization_9_gamma = readTrainedWeights(batch_normalization_9_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_9_beta_path = dir_prefix + std::string("batch_normalization_9_beta.bin");
+void* batch_normalization_9_beta = readTrainedWeights(batch_normalization_9_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_9_mean_path = dir_prefix + std::string("batch_normalization_9_mean.bin");
+void* batch_normalization_9_mean = readTrainedWeights(batch_normalization_9_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_9_variance_path = dir_prefix + std::string("batch_normalization_9_variance.bin");
+void* batch_normalization_9_variance = readTrainedWeights(batch_normalization_9_variance_path.c_str(), 0,1,256,1,1);
+std::string depthwise_conv2d_5_w_path = dir_prefix + std::string("depthwise_conv2d_5_w.bin");
+void* depthwise_conv2d_5_w = readTrainedWeights(depthwise_conv2d_5_w_path.c_str(), 0,256,1,3,3);
+std::string batch_normalization_10_gamma_path = dir_prefix + std::string("batch_normalization_10_gamma.bin");
+void* batch_normalization_10_gamma = readTrainedWeights(batch_normalization_10_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_10_beta_path = dir_prefix + std::string("batch_normalization_10_beta.bin");
+void* batch_normalization_10_beta = readTrainedWeights(batch_normalization_10_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_10_mean_path = dir_prefix + std::string("batch_normalization_10_mean.bin");
+void* batch_normalization_10_mean = readTrainedWeights(batch_normalization_10_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_10_variance_path = dir_prefix + std::string("batch_normalization_10_variance.bin");
+void* batch_normalization_10_variance = readTrainedWeights(batch_normalization_10_variance_path.c_str(), 0,1,256,1,1);
+std::string conv2d_6_w_path = dir_prefix + std::string("conv2d_6_w.bin");
+void* conv2d_6_w = readTrainedWeights(conv2d_6_w_path.c_str(), 0,256,256,1,1);
+std::string batch_normalization_11_gamma_path = dir_prefix + std::string("batch_normalization_11_gamma.bin");
+void* batch_normalization_11_gamma = readTrainedWeights(batch_normalization_11_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_11_beta_path = dir_prefix + std::string("batch_normalization_11_beta.bin");
+void* batch_normalization_11_beta = readTrainedWeights(batch_normalization_11_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_11_mean_path = dir_prefix + std::string("batch_normalization_11_mean.bin");
+void* batch_normalization_11_mean = readTrainedWeights(batch_normalization_11_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_11_variance_path = dir_prefix + std::string("batch_normalization_11_variance.bin");
+void* batch_normalization_11_variance = readTrainedWeights(batch_normalization_11_variance_path.c_str(), 0,1,256,1,1);
+std::string depthwise_conv2d_6_w_path = dir_prefix + std::string("depthwise_conv2d_6_w.bin");
+void* depthwise_conv2d_6_w = readTrainedWeights(depthwise_conv2d_6_w_path.c_str(), 0,256,1,3,3);
+std::string batch_normalization_12_gamma_path = dir_prefix + std::string("batch_normalization_12_gamma.bin");
+void* batch_normalization_12_gamma = readTrainedWeights(batch_normalization_12_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_beta_path = dir_prefix + std::string("batch_normalization_12_beta.bin");
+void* batch_normalization_12_beta = readTrainedWeights(batch_normalization_12_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_mean_path = dir_prefix + std::string("batch_normalization_12_mean.bin");
+void* batch_normalization_12_mean = readTrainedWeights(batch_normalization_12_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_variance_path = dir_prefix + std::string("batch_normalization_12_variance.bin");
+void* batch_normalization_12_variance = readTrainedWeights(batch_normalization_12_variance_path.c_str(), 0,1,256,1,1);
+std::string conv2d_7_w_path = dir_prefix + std::string("conv2d_7_w.bin");
+void* conv2d_7_w = readTrainedWeights(conv2d_7_w_path.c_str(), 0,512,256,1,1);
+std::string batch_normalization_13_gamma_path = dir_prefix + std::string("batch_normalization_13_gamma.bin");
+void* batch_normalization_13_gamma = readTrainedWeights(batch_normalization_13_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_beta_path = dir_prefix + std::string("batch_normalization_13_beta.bin");
+void* batch_normalization_13_beta = readTrainedWeights(batch_normalization_13_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_mean_path = dir_prefix + std::string("batch_normalization_13_mean.bin");
+void* batch_normalization_13_mean = readTrainedWeights(batch_normalization_13_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_variance_path = dir_prefix + std::string("batch_normalization_13_variance.bin");
+void* batch_normalization_13_variance = readTrainedWeights(batch_normalization_13_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_7_w_path = dir_prefix + std::string("depthwise_conv2d_7_w.bin");
+void* depthwise_conv2d_7_w = readTrainedWeights(depthwise_conv2d_7_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_14_gamma_path = dir_prefix + std::string("batch_normalization_14_gamma.bin");
+void* batch_normalization_14_gamma = readTrainedWeights(batch_normalization_14_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_14_beta_path = dir_prefix + std::string("batch_normalization_14_beta.bin");
+void* batch_normalization_14_beta = readTrainedWeights(batch_normalization_14_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_14_mean_path = dir_prefix + std::string("batch_normalization_14_mean.bin");
+void* batch_normalization_14_mean = readTrainedWeights(batch_normalization_14_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_14_variance_path = dir_prefix + std::string("batch_normalization_14_variance.bin");
+void* batch_normalization_14_variance = readTrainedWeights(batch_normalization_14_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_8_w_path = dir_prefix + std::string("conv2d_8_w.bin");
+void* conv2d_8_w = readTrainedWeights(conv2d_8_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_15_gamma_path = dir_prefix + std::string("batch_normalization_15_gamma.bin");
+void* batch_normalization_15_gamma = readTrainedWeights(batch_normalization_15_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_15_beta_path = dir_prefix + std::string("batch_normalization_15_beta.bin");
+void* batch_normalization_15_beta = readTrainedWeights(batch_normalization_15_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_15_mean_path = dir_prefix + std::string("batch_normalization_15_mean.bin");
+void* batch_normalization_15_mean = readTrainedWeights(batch_normalization_15_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_15_variance_path = dir_prefix + std::string("batch_normalization_15_variance.bin");
+void* batch_normalization_15_variance = readTrainedWeights(batch_normalization_15_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_8_w_path = dir_prefix + std::string("depthwise_conv2d_8_w.bin");
+void* depthwise_conv2d_8_w = readTrainedWeights(depthwise_conv2d_8_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_16_gamma_path = dir_prefix + std::string("batch_normalization_16_gamma.bin");
+void* batch_normalization_16_gamma = readTrainedWeights(batch_normalization_16_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_16_beta_path = dir_prefix + std::string("batch_normalization_16_beta.bin");
+void* batch_normalization_16_beta = readTrainedWeights(batch_normalization_16_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_16_mean_path = dir_prefix + std::string("batch_normalization_16_mean.bin");
+void* batch_normalization_16_mean = readTrainedWeights(batch_normalization_16_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_16_variance_path = dir_prefix + std::string("batch_normalization_16_variance.bin");
+void* batch_normalization_16_variance = readTrainedWeights(batch_normalization_16_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_9_w_path = dir_prefix + std::string("conv2d_9_w.bin");
+void* conv2d_9_w = readTrainedWeights(conv2d_9_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_17_gamma_path = dir_prefix + std::string("batch_normalization_17_gamma.bin");
+void* batch_normalization_17_gamma = readTrainedWeights(batch_normalization_17_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_17_beta_path = dir_prefix + std::string("batch_normalization_17_beta.bin");
+void* batch_normalization_17_beta = readTrainedWeights(batch_normalization_17_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_17_mean_path = dir_prefix + std::string("batch_normalization_17_mean.bin");
+void* batch_normalization_17_mean = readTrainedWeights(batch_normalization_17_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_17_variance_path = dir_prefix + std::string("batch_normalization_17_variance.bin");
+void* batch_normalization_17_variance = readTrainedWeights(batch_normalization_17_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_9_w_path = dir_prefix + std::string("depthwise_conv2d_9_w.bin");
+void* depthwise_conv2d_9_w = readTrainedWeights(depthwise_conv2d_9_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_18_gamma_path = dir_prefix + std::string("batch_normalization_18_gamma.bin");
+void* batch_normalization_18_gamma = readTrainedWeights(batch_normalization_18_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_18_beta_path = dir_prefix + std::string("batch_normalization_18_beta.bin");
+void* batch_normalization_18_beta = readTrainedWeights(batch_normalization_18_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_18_mean_path = dir_prefix + std::string("batch_normalization_18_mean.bin");
+void* batch_normalization_18_mean = readTrainedWeights(batch_normalization_18_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_18_variance_path = dir_prefix + std::string("batch_normalization_18_variance.bin");
+void* batch_normalization_18_variance = readTrainedWeights(batch_normalization_18_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_10_w_path = dir_prefix + std::string("conv2d_10_w.bin");
+void* conv2d_10_w = readTrainedWeights(conv2d_10_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_19_gamma_path = dir_prefix + std::string("batch_normalization_19_gamma.bin");
+void* batch_normalization_19_gamma = readTrainedWeights(batch_normalization_19_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_19_beta_path = dir_prefix + std::string("batch_normalization_19_beta.bin");
+void* batch_normalization_19_beta = readTrainedWeights(batch_normalization_19_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_19_mean_path = dir_prefix + std::string("batch_normalization_19_mean.bin");
+void* batch_normalization_19_mean = readTrainedWeights(batch_normalization_19_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_19_variance_path = dir_prefix + std::string("batch_normalization_19_variance.bin");
+void* batch_normalization_19_variance = readTrainedWeights(batch_normalization_19_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_10_w_path = dir_prefix + std::string("depthwise_conv2d_10_w.bin");
+void* depthwise_conv2d_10_w = readTrainedWeights(depthwise_conv2d_10_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_20_gamma_path = dir_prefix + std::string("batch_normalization_20_gamma.bin");
+void* batch_normalization_20_gamma = readTrainedWeights(batch_normalization_20_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_20_beta_path = dir_prefix + std::string("batch_normalization_20_beta.bin");
+void* batch_normalization_20_beta = readTrainedWeights(batch_normalization_20_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_20_mean_path = dir_prefix + std::string("batch_normalization_20_mean.bin");
+void* batch_normalization_20_mean = readTrainedWeights(batch_normalization_20_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_20_variance_path = dir_prefix + std::string("batch_normalization_20_variance.bin");
+void* batch_normalization_20_variance = readTrainedWeights(batch_normalization_20_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_11_w_path = dir_prefix + std::string("conv2d_11_w.bin");
+void* conv2d_11_w = readTrainedWeights(conv2d_11_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_21_gamma_path = dir_prefix + std::string("batch_normalization_21_gamma.bin");
+void* batch_normalization_21_gamma = readTrainedWeights(batch_normalization_21_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_21_beta_path = dir_prefix + std::string("batch_normalization_21_beta.bin");
+void* batch_normalization_21_beta = readTrainedWeights(batch_normalization_21_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_21_mean_path = dir_prefix + std::string("batch_normalization_21_mean.bin");
+void* batch_normalization_21_mean = readTrainedWeights(batch_normalization_21_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_21_variance_path = dir_prefix + std::string("batch_normalization_21_variance.bin");
+void* batch_normalization_21_variance = readTrainedWeights(batch_normalization_21_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_11_w_path = dir_prefix + std::string("depthwise_conv2d_11_w.bin");
+void* depthwise_conv2d_11_w = readTrainedWeights(depthwise_conv2d_11_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_22_gamma_path = dir_prefix + std::string("batch_normalization_22_gamma.bin");
+void* batch_normalization_22_gamma = readTrainedWeights(batch_normalization_22_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_22_beta_path = dir_prefix + std::string("batch_normalization_22_beta.bin");
+void* batch_normalization_22_beta = readTrainedWeights(batch_normalization_22_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_22_mean_path = dir_prefix + std::string("batch_normalization_22_mean.bin");
+void* batch_normalization_22_mean = readTrainedWeights(batch_normalization_22_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_22_variance_path = dir_prefix + std::string("batch_normalization_22_variance.bin");
+void* batch_normalization_22_variance = readTrainedWeights(batch_normalization_22_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_12_w_path = dir_prefix + std::string("conv2d_12_w.bin");
+void* conv2d_12_w = readTrainedWeights(conv2d_12_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_23_gamma_path = dir_prefix + std::string("batch_normalization_23_gamma.bin");
+void* batch_normalization_23_gamma = readTrainedWeights(batch_normalization_23_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_23_beta_path = dir_prefix + std::string("batch_normalization_23_beta.bin");
+void* batch_normalization_23_beta = readTrainedWeights(batch_normalization_23_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_23_mean_path = dir_prefix + std::string("batch_normalization_23_mean.bin");
+void* batch_normalization_23_mean = readTrainedWeights(batch_normalization_23_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_23_variance_path = dir_prefix + std::string("batch_normalization_23_variance.bin");
+void* batch_normalization_23_variance = readTrainedWeights(batch_normalization_23_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_12_w_path = dir_prefix + std::string("depthwise_conv2d_12_w.bin");
+void* depthwise_conv2d_12_w = readTrainedWeights(depthwise_conv2d_12_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_24_gamma_path = dir_prefix + std::string("batch_normalization_24_gamma.bin");
+void* batch_normalization_24_gamma = readTrainedWeights(batch_normalization_24_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_24_beta_path = dir_prefix + std::string("batch_normalization_24_beta.bin");
+void* batch_normalization_24_beta = readTrainedWeights(batch_normalization_24_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_24_mean_path = dir_prefix + std::string("batch_normalization_24_mean.bin");
+void* batch_normalization_24_mean = readTrainedWeights(batch_normalization_24_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_24_variance_path = dir_prefix + std::string("batch_normalization_24_variance.bin");
+void* batch_normalization_24_variance = readTrainedWeights(batch_normalization_24_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_13_w_path = dir_prefix + std::string("conv2d_13_w.bin");
+void* conv2d_13_w = readTrainedWeights(conv2d_13_w_path.c_str(), 0,1024,512,1,1);
+std::string batch_normalization_25_gamma_path = dir_prefix + std::string("batch_normalization_25_gamma.bin");
+void* batch_normalization_25_gamma = readTrainedWeights(batch_normalization_25_gamma_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_25_beta_path = dir_prefix + std::string("batch_normalization_25_beta.bin");
+void* batch_normalization_25_beta = readTrainedWeights(batch_normalization_25_beta_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_25_mean_path = dir_prefix + std::string("batch_normalization_25_mean.bin");
+void* batch_normalization_25_mean = readTrainedWeights(batch_normalization_25_mean_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_25_variance_path = dir_prefix + std::string("batch_normalization_25_variance.bin");
+void* batch_normalization_25_variance = readTrainedWeights(batch_normalization_25_variance_path.c_str(), 0,1,1024,1,1);
+std::string depthwise_conv2d_13_w_path = dir_prefix + std::string("depthwise_conv2d_13_w.bin");
+void* depthwise_conv2d_13_w = readTrainedWeights(depthwise_conv2d_13_w_path.c_str(), 0,1024,1,3,3);
+std::string batch_normalization_26_gamma_path = dir_prefix + std::string("batch_normalization_26_gamma.bin");
+void* batch_normalization_26_gamma = readTrainedWeights(batch_normalization_26_gamma_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_26_beta_path = dir_prefix + std::string("batch_normalization_26_beta.bin");
+void* batch_normalization_26_beta = readTrainedWeights(batch_normalization_26_beta_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_26_mean_path = dir_prefix + std::string("batch_normalization_26_mean.bin");
+void* batch_normalization_26_mean = readTrainedWeights(batch_normalization_26_mean_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_26_variance_path = dir_prefix + std::string("batch_normalization_26_variance.bin");
+void* batch_normalization_26_variance = readTrainedWeights(batch_normalization_26_variance_path.c_str(), 0,1,1024,1,1);
+std::string conv2d_14_w_path = dir_prefix + std::string("conv2d_14_w.bin");
+void* conv2d_14_w = readTrainedWeights(conv2d_14_w_path.c_str(), 0,1024,1024,1,1);
+std::string batch_normalization_27_gamma_path = dir_prefix + std::string("batch_normalization_27_gamma.bin");
+void* batch_normalization_27_gamma = readTrainedWeights(batch_normalization_27_gamma_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_27_beta_path = dir_prefix + std::string("batch_normalization_27_beta.bin");
+void* batch_normalization_27_beta = readTrainedWeights(batch_normalization_27_beta_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_27_mean_path = dir_prefix + std::string("batch_normalization_27_mean.bin");
+void* batch_normalization_27_mean = readTrainedWeights(batch_normalization_27_mean_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_27_variance_path = dir_prefix + std::string("batch_normalization_27_variance.bin");
+void* batch_normalization_27_variance = readTrainedWeights(batch_normalization_27_variance_path.c_str(), 0,1,1024,1,1);
+std::string dense_1_w_path = dir_prefix + std::string("dense_1_w.bin");
+void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,1024,10);
+std::string dense_1_b_path = dir_prefix + std::string("dense_1_b.bin");
+void* dense_1_b = readTrainedWeights(dense_1_b_path.c_str(), 0,1,10,1,1);
+void* input = readTrainedWeights(input_path.c_str(), 0,10000,3,32,32);
+uint8_t* labels = readLabels(labels_path.c_str(),10000);
+
+__visc__init();
+RootIn* args = static_cast<RootIn*>(malloc(sizeof(RootIn)));
+
+args->input = input;
+args->input_bytes = 0;
+args->conv2d_1_w = conv2d_1_w;
+args->conv2d_1_w_bytes = 0;
+args->batch_normalization_1_gamma = batch_normalization_1_gamma;
+args->batch_normalization_1_gamma_bytes = 0;
+args->batch_normalization_1_beta = batch_normalization_1_beta;
+args->batch_normalization_1_beta_bytes = 0;
+args->batch_normalization_1_mean = batch_normalization_1_mean;
+args->batch_normalization_1_mean_bytes = 0;
+args->batch_normalization_1_variance = batch_normalization_1_variance;
+args->batch_normalization_1_variance_bytes = 0;
+args->depthwise_conv2d_1_w = depthwise_conv2d_1_w;
+args->depthwise_conv2d_1_w_bytes = 0;
+args->batch_normalization_2_gamma = batch_normalization_2_gamma;
+args->batch_normalization_2_gamma_bytes = 0;
+args->batch_normalization_2_beta = batch_normalization_2_beta;
+args->batch_normalization_2_beta_bytes = 0;
+args->batch_normalization_2_mean = batch_normalization_2_mean;
+args->batch_normalization_2_mean_bytes = 0;
+args->batch_normalization_2_variance = batch_normalization_2_variance;
+args->batch_normalization_2_variance_bytes = 0;
+args->conv2d_2_w = conv2d_2_w;
+args->conv2d_2_w_bytes = 0;
+args->batch_normalization_3_gamma = batch_normalization_3_gamma;
+args->batch_normalization_3_gamma_bytes = 0;
+args->batch_normalization_3_beta = batch_normalization_3_beta;
+args->batch_normalization_3_beta_bytes = 0;
+args->batch_normalization_3_mean = batch_normalization_3_mean;
+args->batch_normalization_3_mean_bytes = 0;
+args->batch_normalization_3_variance = batch_normalization_3_variance;
+args->batch_normalization_3_variance_bytes = 0;
+args->depthwise_conv2d_2_w = depthwise_conv2d_2_w;
+args->depthwise_conv2d_2_w_bytes = 0;
+args->batch_normalization_4_gamma = batch_normalization_4_gamma;
+args->batch_normalization_4_gamma_bytes = 0;
+args->batch_normalization_4_beta = batch_normalization_4_beta;
+args->batch_normalization_4_beta_bytes = 0;
+args->batch_normalization_4_mean = batch_normalization_4_mean;
+args->batch_normalization_4_mean_bytes = 0;
+args->batch_normalization_4_variance = batch_normalization_4_variance;
+args->batch_normalization_4_variance_bytes = 0;
+args->conv2d_3_w = conv2d_3_w;
+args->conv2d_3_w_bytes = 0;
+args->batch_normalization_5_gamma = batch_normalization_5_gamma;
+args->batch_normalization_5_gamma_bytes = 0;
+args->batch_normalization_5_beta = batch_normalization_5_beta;
+args->batch_normalization_5_beta_bytes = 0;
+args->batch_normalization_5_mean = batch_normalization_5_mean;
+args->batch_normalization_5_mean_bytes = 0;
+args->batch_normalization_5_variance = batch_normalization_5_variance;
+args->batch_normalization_5_variance_bytes = 0;
+args->depthwise_conv2d_3_w = depthwise_conv2d_3_w;
+args->depthwise_conv2d_3_w_bytes = 0;
+args->batch_normalization_6_gamma = batch_normalization_6_gamma;
+args->batch_normalization_6_gamma_bytes = 0;
+args->batch_normalization_6_beta = batch_normalization_6_beta;
+args->batch_normalization_6_beta_bytes = 0;
+args->batch_normalization_6_mean = batch_normalization_6_mean;
+args->batch_normalization_6_mean_bytes = 0;
+args->batch_normalization_6_variance = batch_normalization_6_variance;
+args->batch_normalization_6_variance_bytes = 0;
+args->conv2d_4_w = conv2d_4_w;
+args->conv2d_4_w_bytes = 0;
+args->batch_normalization_7_gamma = batch_normalization_7_gamma;
+args->batch_normalization_7_gamma_bytes = 0;
+args->batch_normalization_7_beta = batch_normalization_7_beta;
+args->batch_normalization_7_beta_bytes = 0;
+args->batch_normalization_7_mean = batch_normalization_7_mean;
+args->batch_normalization_7_mean_bytes = 0;
+args->batch_normalization_7_variance = batch_normalization_7_variance;
+args->batch_normalization_7_variance_bytes = 0;
+args->depthwise_conv2d_4_w = depthwise_conv2d_4_w;
+args->depthwise_conv2d_4_w_bytes = 0;
+args->batch_normalization_8_gamma = batch_normalization_8_gamma;
+args->batch_normalization_8_gamma_bytes = 0;
+args->batch_normalization_8_beta = batch_normalization_8_beta;
+args->batch_normalization_8_beta_bytes = 0;
+args->batch_normalization_8_mean = batch_normalization_8_mean;
+args->batch_normalization_8_mean_bytes = 0;
+args->batch_normalization_8_variance = batch_normalization_8_variance;
+args->batch_normalization_8_variance_bytes = 0;
+args->conv2d_5_w = conv2d_5_w;
+args->conv2d_5_w_bytes = 0;
+args->batch_normalization_9_gamma = batch_normalization_9_gamma;
+args->batch_normalization_9_gamma_bytes = 0;
+args->batch_normalization_9_beta = batch_normalization_9_beta;
+args->batch_normalization_9_beta_bytes = 0;
+args->batch_normalization_9_mean = batch_normalization_9_mean;
+args->batch_normalization_9_mean_bytes = 0;
+args->batch_normalization_9_variance = batch_normalization_9_variance;
+args->batch_normalization_9_variance_bytes = 0;
+args->depthwise_conv2d_5_w = depthwise_conv2d_5_w;
+args->depthwise_conv2d_5_w_bytes = 0;
+args->batch_normalization_10_gamma = batch_normalization_10_gamma;
+args->batch_normalization_10_gamma_bytes = 0;
+args->batch_normalization_10_beta = batch_normalization_10_beta;
+args->batch_normalization_10_beta_bytes = 0;
+args->batch_normalization_10_mean = batch_normalization_10_mean;
+args->batch_normalization_10_mean_bytes = 0;
+args->batch_normalization_10_variance = batch_normalization_10_variance;
+args->batch_normalization_10_variance_bytes = 0;
+args->conv2d_6_w = conv2d_6_w;
+args->conv2d_6_w_bytes = 0;
+args->batch_normalization_11_gamma = batch_normalization_11_gamma;
+args->batch_normalization_11_gamma_bytes = 0;
+args->batch_normalization_11_beta = batch_normalization_11_beta;
+args->batch_normalization_11_beta_bytes = 0;
+args->batch_normalization_11_mean = batch_normalization_11_mean;
+args->batch_normalization_11_mean_bytes = 0;
+args->batch_normalization_11_variance = batch_normalization_11_variance;
+args->batch_normalization_11_variance_bytes = 0;
+args->depthwise_conv2d_6_w = depthwise_conv2d_6_w;
+args->depthwise_conv2d_6_w_bytes = 0;
+args->batch_normalization_12_gamma = batch_normalization_12_gamma;
+args->batch_normalization_12_gamma_bytes = 0;
+args->batch_normalization_12_beta = batch_normalization_12_beta;
+args->batch_normalization_12_beta_bytes = 0;
+args->batch_normalization_12_mean = batch_normalization_12_mean;
+args->batch_normalization_12_mean_bytes = 0;
+args->batch_normalization_12_variance = batch_normalization_12_variance;
+args->batch_normalization_12_variance_bytes = 0;
+args->conv2d_7_w = conv2d_7_w;
+args->conv2d_7_w_bytes = 0;
+args->batch_normalization_13_gamma = batch_normalization_13_gamma;
+args->batch_normalization_13_gamma_bytes = 0;
+args->batch_normalization_13_beta = batch_normalization_13_beta;
+args->batch_normalization_13_beta_bytes = 0;
+args->batch_normalization_13_mean = batch_normalization_13_mean;
+args->batch_normalization_13_mean_bytes = 0;
+args->batch_normalization_13_variance = batch_normalization_13_variance;
+args->batch_normalization_13_variance_bytes = 0;
+args->depthwise_conv2d_7_w = depthwise_conv2d_7_w;
+args->depthwise_conv2d_7_w_bytes = 0;
+args->batch_normalization_14_gamma = batch_normalization_14_gamma;
+args->batch_normalization_14_gamma_bytes = 0;
+args->batch_normalization_14_beta = batch_normalization_14_beta;
+args->batch_normalization_14_beta_bytes = 0;
+args->batch_normalization_14_mean = batch_normalization_14_mean;
+args->batch_normalization_14_mean_bytes = 0;
+args->batch_normalization_14_variance = batch_normalization_14_variance;
+args->batch_normalization_14_variance_bytes = 0;
+args->conv2d_8_w = conv2d_8_w;
+args->conv2d_8_w_bytes = 0;
+args->batch_normalization_15_gamma = batch_normalization_15_gamma;
+args->batch_normalization_15_gamma_bytes = 0;
+args->batch_normalization_15_beta = batch_normalization_15_beta;
+args->batch_normalization_15_beta_bytes = 0;
+args->batch_normalization_15_mean = batch_normalization_15_mean;
+args->batch_normalization_15_mean_bytes = 0;
+args->batch_normalization_15_variance = batch_normalization_15_variance;
+args->batch_normalization_15_variance_bytes = 0;
+args->depthwise_conv2d_8_w = depthwise_conv2d_8_w;
+args->depthwise_conv2d_8_w_bytes = 0;
+args->batch_normalization_16_gamma = batch_normalization_16_gamma;
+args->batch_normalization_16_gamma_bytes = 0;
+args->batch_normalization_16_beta = batch_normalization_16_beta;
+args->batch_normalization_16_beta_bytes = 0;
+args->batch_normalization_16_mean = batch_normalization_16_mean;
+args->batch_normalization_16_mean_bytes = 0;
+args->batch_normalization_16_variance = batch_normalization_16_variance;
+args->batch_normalization_16_variance_bytes = 0;
+args->conv2d_9_w = conv2d_9_w;
+args->conv2d_9_w_bytes = 0;
+args->batch_normalization_17_gamma = batch_normalization_17_gamma;
+args->batch_normalization_17_gamma_bytes = 0;
+args->batch_normalization_17_beta = batch_normalization_17_beta;
+args->batch_normalization_17_beta_bytes = 0;
+args->batch_normalization_17_mean = batch_normalization_17_mean;
+args->batch_normalization_17_mean_bytes = 0;
+args->batch_normalization_17_variance = batch_normalization_17_variance;
+args->batch_normalization_17_variance_bytes = 0;
+args->depthwise_conv2d_9_w = depthwise_conv2d_9_w;
+args->depthwise_conv2d_9_w_bytes = 0;
+args->batch_normalization_18_gamma = batch_normalization_18_gamma;
+args->batch_normalization_18_gamma_bytes = 0;
+args->batch_normalization_18_beta = batch_normalization_18_beta;
+args->batch_normalization_18_beta_bytes = 0;
+args->batch_normalization_18_mean = batch_normalization_18_mean;
+args->batch_normalization_18_mean_bytes = 0;
+args->batch_normalization_18_variance = batch_normalization_18_variance;
+args->batch_normalization_18_variance_bytes = 0;
+args->conv2d_10_w = conv2d_10_w;
+args->conv2d_10_w_bytes = 0;
+args->batch_normalization_19_gamma = batch_normalization_19_gamma;
+args->batch_normalization_19_gamma_bytes = 0;
+args->batch_normalization_19_beta = batch_normalization_19_beta;
+args->batch_normalization_19_beta_bytes = 0;
+args->batch_normalization_19_mean = batch_normalization_19_mean;
+args->batch_normalization_19_mean_bytes = 0;
+args->batch_normalization_19_variance = batch_normalization_19_variance;
+args->batch_normalization_19_variance_bytes = 0;
+args->depthwise_conv2d_10_w = depthwise_conv2d_10_w;
+args->depthwise_conv2d_10_w_bytes = 0;
+args->batch_normalization_20_gamma = batch_normalization_20_gamma;
+args->batch_normalization_20_gamma_bytes = 0;
+args->batch_normalization_20_beta = batch_normalization_20_beta;
+args->batch_normalization_20_beta_bytes = 0;
+args->batch_normalization_20_mean = batch_normalization_20_mean;
+args->batch_normalization_20_mean_bytes = 0;
+args->batch_normalization_20_variance = batch_normalization_20_variance;
+args->batch_normalization_20_variance_bytes = 0;
+args->conv2d_11_w = conv2d_11_w;
+args->conv2d_11_w_bytes = 0;
+args->batch_normalization_21_gamma = batch_normalization_21_gamma;
+args->batch_normalization_21_gamma_bytes = 0;
+args->batch_normalization_21_beta = batch_normalization_21_beta;
+args->batch_normalization_21_beta_bytes = 0;
+args->batch_normalization_21_mean = batch_normalization_21_mean;
+args->batch_normalization_21_mean_bytes = 0;
+args->batch_normalization_21_variance = batch_normalization_21_variance;
+args->batch_normalization_21_variance_bytes = 0;
+args->depthwise_conv2d_11_w = depthwise_conv2d_11_w;
+args->depthwise_conv2d_11_w_bytes = 0;
+args->batch_normalization_22_gamma = batch_normalization_22_gamma;
+args->batch_normalization_22_gamma_bytes = 0;
+args->batch_normalization_22_beta = batch_normalization_22_beta;
+args->batch_normalization_22_beta_bytes = 0;
+args->batch_normalization_22_mean = batch_normalization_22_mean;
+args->batch_normalization_22_mean_bytes = 0;
+args->batch_normalization_22_variance = batch_normalization_22_variance;
+args->batch_normalization_22_variance_bytes = 0;
+args->conv2d_12_w = conv2d_12_w;
+args->conv2d_12_w_bytes = 0;
+args->batch_normalization_23_gamma = batch_normalization_23_gamma;
+args->batch_normalization_23_gamma_bytes = 0;
+args->batch_normalization_23_beta = batch_normalization_23_beta;
+args->batch_normalization_23_beta_bytes = 0;
+args->batch_normalization_23_mean = batch_normalization_23_mean;
+args->batch_normalization_23_mean_bytes = 0;
+args->batch_normalization_23_variance = batch_normalization_23_variance;
+args->batch_normalization_23_variance_bytes = 0;
+args->depthwise_conv2d_12_w = depthwise_conv2d_12_w;
+args->depthwise_conv2d_12_w_bytes = 0;
+args->batch_normalization_24_gamma = batch_normalization_24_gamma;
+args->batch_normalization_24_gamma_bytes = 0;
+args->batch_normalization_24_beta = batch_normalization_24_beta;
+args->batch_normalization_24_beta_bytes = 0;
+args->batch_normalization_24_mean = batch_normalization_24_mean;
+args->batch_normalization_24_mean_bytes = 0;
+args->batch_normalization_24_variance = batch_normalization_24_variance;
+args->batch_normalization_24_variance_bytes = 0;
+args->conv2d_13_w = conv2d_13_w;
+args->conv2d_13_w_bytes = 0;
+args->batch_normalization_25_gamma = batch_normalization_25_gamma;
+args->batch_normalization_25_gamma_bytes = 0;
+args->batch_normalization_25_beta = batch_normalization_25_beta;
+args->batch_normalization_25_beta_bytes = 0;
+args->batch_normalization_25_mean = batch_normalization_25_mean;
+args->batch_normalization_25_mean_bytes = 0;
+args->batch_normalization_25_variance = batch_normalization_25_variance;
+args->batch_normalization_25_variance_bytes = 0;
+args->depthwise_conv2d_13_w = depthwise_conv2d_13_w;
+args->depthwise_conv2d_13_w_bytes = 0;
+args->batch_normalization_26_gamma = batch_normalization_26_gamma;
+args->batch_normalization_26_gamma_bytes = 0;
+args->batch_normalization_26_beta = batch_normalization_26_beta;
+args->batch_normalization_26_beta_bytes = 0;
+args->batch_normalization_26_mean = batch_normalization_26_mean;
+args->batch_normalization_26_mean_bytes = 0;
+args->batch_normalization_26_variance = batch_normalization_26_variance;
+args->batch_normalization_26_variance_bytes = 0;
+args->conv2d_14_w = conv2d_14_w;
+args->conv2d_14_w_bytes = 0;
+args->batch_normalization_27_gamma = batch_normalization_27_gamma;
+args->batch_normalization_27_gamma_bytes = 0;
+args->batch_normalization_27_beta = batch_normalization_27_beta;
+args->batch_normalization_27_beta_bytes = 0;
+args->batch_normalization_27_mean = batch_normalization_27_mean;
+args->batch_normalization_27_mean_bytes = 0;
+args->batch_normalization_27_variance = batch_normalization_27_variance;
+args->batch_normalization_27_variance_bytes = 0;
+args->dense_1_w = dense_1_w;
+args->dense_1_w_bytes = 0;
+args->dense_1_b = dense_1_b;
+args->dense_1_b_bytes = 0;
+
+void* dfg = __visc__launch(0, root, (void*) args);
+
+__visc__wait(dfg);
+
+void *result = static_cast<RootIn*>(args)->input;
+hpvm_request_tensor(result, 0);
+
+__visc__cleanup();
+ computeAccuracy2(labels, 10000, result);
+return 0;
+
+}
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_10_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_10_beta.bin
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Binary files /dev/null and b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_10_beta.bin differ
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_10_gamma.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_10_gamma.bin
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Binary files /dev/null and b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_10_gamma.bin differ
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_10_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_10_mean.bin
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Binary files /dev/null and b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_10_mean.bin differ
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_10_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_10_variance.bin
new file mode 100644
index 0000000000000000000000000000000000000000..f92c73f59eb5eb35ca94e3ce006e5f3c4f60ecef
--- /dev/null
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_11_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_11_variance.bin
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_12_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_12_beta.bin
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_12_gamma.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_12_gamma.bin
new file mode 100644
index 0000000000000000000000000000000000000000..6dfb7c3833821b29f9230df806c4abc0c16a7b59
--- /dev/null
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_12_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_12_mean.bin
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index 0000000000000000000000000000000000000000..8899c2ad8395a98c752b1777095018cc90ca693b
Binary files /dev/null and b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_12_mean.bin differ
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_12_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_12_variance.bin
new file mode 100644
index 0000000000000000000000000000000000000000..9206092b5ee7fa6178bb9109a9aabd5dbfaa7ccf
Binary files /dev/null and b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_12_variance.bin differ
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_13_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_13_beta.bin
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Binary files /dev/null and b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/batch_normalization_13_beta.bin differ
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index 0000000000000000000000000000000000000000..5888235eb54a3c9ad548a51708eb39c13d7e8ddd
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/input.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/input.bin
similarity index 100%
rename from llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/input.bin
rename to llvm/projects/hpvm-tensor-rt/model_params/mobilenet/input.bin
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/labels.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/labels.bin
similarity index 100%
rename from llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/labels.bin
rename to llvm/projects/hpvm-tensor-rt/model_params/mobilenet/labels.bin
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/layer_composition.txt b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/layer_composition.txt
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index 0000000000000000000000000000000000000000..10692997a90e4490a91ad3d0e6e04285754144fd
--- /dev/null
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/layer_composition.txt
@@ -0,0 +1,83 @@
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+
+
+activation
+conv
+
+activation
+pool
+dense add
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/layers.txt b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/layers.txt
new file mode 100644
index 0000000000000000000000000000000000000000..0bd2b554374c10d748a652f52e5427c716be0084
--- /dev/null
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/layers.txt
@@ -0,0 +1,83 @@
+Conv1,10000,3,32,32,32,3,3,3
+#tensorBatchNorm1
+#tensorRelu1
+#tensorDepthwiseConv1
+#tensorBatchNorm2
+#tensorRelu2
+Conv2,10000,32,32,32,64,32,1,1
+#tensorBatchNorm3
+#tensorRelu3
+#tensorDepthwiseConv2
+#tensorBatchNorm4
+#tensorRelu4
+Conv3,10000,64,16,16,128,64,1,1
+#tensorBatchNorm5
+#tensorRelu5
+#tensorDepthwiseConv3
+#tensorBatchNorm6
+#tensorRelu6
+Conv4,10000,128,16,16,128,128,1,1
+#tensorBatchNorm7
+#tensorRelu7
+#tensorDepthwiseConv4
+#tensorBatchNorm8
+#tensorRelu8
+Conv5,10000,128,8,8,256,128,1,1
+#tensorBatchNorm9
+#tensorRelu9
+#tensorDepthwiseConv5
+#tensorBatchNorm10
+#tensorRelu10
+Conv6,10000,256,8,8,256,256,1,1
+#tensorBatchNorm11
+#tensorRelu11
+#tensorDepthwiseConv6
+#tensorBatchNorm12
+#tensorRelu12
+Conv7,10000,256,4,4,512,256,1,1
+#tensorBatchNorm13
+#tensorRelu13
+#tensorDepthwiseConv7
+#tensorBatchNorm14
+#tensorRelu14
+Conv8,10000,512,4,4,512,512,1,1
+#tensorBatchNorm15
+#tensorRelu15
+#tensorDepthwiseConv8
+#tensorBatchNorm16
+#tensorRelu16
+Conv9,10000,512,4,4,512,512,1,1
+#tensorBatchNorm17
+#tensorRelu17
+#tensorDepthwiseConv9
+#tensorBatchNorm18
+#tensorRelu18
+Conv10,10000,512,4,4,512,512,1,1
+#tensorBatchNorm19
+#tensorRelu19
+#tensorDepthwiseConv10
+#tensorBatchNorm20
+#tensorRelu20
+Conv11,10000,512,4,4,512,512,1,1
+#tensorBatchNorm21
+#tensorRelu21
+#tensorDepthwiseConv11
+#tensorBatchNorm22
+#tensorRelu22
+Conv12,10000,512,4,4,512,512,1,1
+#tensorBatchNorm23
+#tensorRelu23
+#tensorDepthwiseConv12
+#tensorBatchNorm24
+#tensorRelu24
+Conv13,10000,512,2,2,1024,512,1,1
+#tensorBatchNorm25
+#tensorRelu25
+#tensorDepthwiseConv13
+#tensorBatchNorm26
+#tensorRelu26
+Conv14,10000,1024,2,2,1024,1024,1,1
+#tensorBatchNorm27
+#tensorRelu27
+#tensorPooling1
+FC1,10000,1024,1024,10
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/mobilenet_layers.txt b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/mobilenet_layers.txt
new file mode 100644
index 0000000000000000000000000000000000000000..c2a4a29509ad89724905c869ff900f8ecaa5bf8c
--- /dev/null
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/mobilenet_layers.txt
@@ -0,0 +1,83 @@
+Conv1,10000,3,32,32,32,3,3,3
+NML1
+NML2
+NML3
+NML4
+NML5
+Conv3,10000,32,32,32,64,32,1,1
+NML6
+NML7
+NML8
+NML9
+NML10
+Conv5,10000,64,16,16,128,64,1,1
+NML11
+NML12
+NML13
+NML14
+NML15
+Conv7,10000,128,16,16,128,128,1,1
+NML16
+NML17
+NML18
+NML19
+NML20
+Conv9,10000,128,8,8,256,128,1,1
+NML21
+NML22
+NML23
+NML24
+NML25
+Conv11,10000,256,8,8,256,256,1,1
+NML26
+NML27
+NML28
+NML29
+NML30
+Conv13,10000,256,4,4,512,256,1,1
+NML31
+NML32
+NML33
+NML34
+NML35
+Conv15,10000,512,4,4,512,512,1,1
+NML36
+NML37
+NML38
+NML39
+NML40
+Conv17,10000,512,4,4,512,512,1,1
+NML41
+NML42
+NML43
+NML44
+NML45
+Conv19,10000,512,4,4,512,512,1,1
+NML46
+NML47
+NML48
+NML49
+NML50
+Conv21,10000,512,4,4,512,512,1,1
+NML51
+NML52
+NML53
+NML54
+NML55
+Conv23,10000,512,4,4,512,512,1,1
+NML56
+NML57
+NML58
+NML59
+NML60
+Conv25,10000,512,2,2,1024,512,1,1
+NML61
+NML62
+NML63
+NML64
+NML65
+Conv27,10000,1024,2,2,1024,1024,1,1
+NML66
+NML67
+NML68
+FC1,10000,1024,1024,10
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/mobilenet_ops.txt b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/mobilenet_ops.txt
new file mode 100644
index 0000000000000000000000000000000000000000..8e18f2ec58cddb9ab0251229b1e908b23b71d6bc
--- /dev/null
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/mobilenet_ops.txt
@@ -0,0 +1,165 @@
+#Conv1,1
+Conv1
+#NML1,1
+BatchNorm1
+#NML2,1
+Relu1
+#NML3,1
+Conv2
+#NML4,1
+BatchNorm2
+#NML5,1
+Relu2
+#Conv3,1
+Conv3
+#NML6,1
+BatchNorm3
+#NML7,1
+Relu3
+#NML8,1
+Conv4
+#NML9,1
+BatchNorm4
+#NML10,1
+Relu4
+#Conv5,1
+Conv5
+#NML11,1
+BatchNorm5
+#NML12,1
+Relu5
+#NML13,1
+Conv6
+#NML14,1
+BatchNorm6
+#NML15,1
+Relu6
+#Conv7,1
+Conv7
+#NML16,1
+BatchNorm7
+#NML17,1
+Relu7
+#NML18,1
+Conv8
+#NML19,1
+BatchNorm8
+#NML20,1
+Relu8
+#Conv9,1
+Conv9
+#NML21,1
+BatchNorm9
+#NML22,1
+Relu9
+#NML23,1
+Conv10
+#NML24,1
+BatchNorm10
+#NML25,1
+Relu10
+#Conv11,1
+Conv11
+#NML26,1
+BatchNorm11
+#NML27,1
+Relu11
+#NML28,1
+Conv12
+#NML29,1
+BatchNorm12
+#NML30,1
+Relu12
+#Conv13,1
+Conv13
+#NML31,1
+BatchNorm13
+#NML32,1
+Relu13
+#NML33,1
+Conv14
+#NML34,1
+BatchNorm14
+#NML35,1
+Relu14
+#Conv15,1
+Conv15
+#NML36,1
+BatchNorm15
+#NML37,1
+Relu15
+#NML38,1
+Conv16
+#NML39,1
+BatchNorm16
+#NML40,1
+Relu16
+#Conv17,1
+Conv17
+#NML41,1
+BatchNorm17
+#NML42,1
+Relu17
+#NML43,1
+Conv18
+#NML44,1
+BatchNorm18
+#NML45,1
+Relu18
+#Conv19,1
+Conv19
+#NML46,1
+BatchNorm19
+#NML47,1
+Relu19
+#NML48,1
+Conv20
+#NML49,1
+BatchNorm20
+#NML50,1
+Relu20
+#Conv21,1
+conv21
+#NML51,1
+BatchNorm21
+#NML52,1
+Relu21
+#NML53,1
+Conv22
+#NML54,1
+BatchNorm22
+#NML55,1
+Relu22
+#Conv23,1
+Conv23
+#NML56,1
+BatchNorm23
+#NML57,1
+Relu23
+#NML58,1
+Conv24
+#NML59,1
+BatchNorm24
+#NML60,1
+Relu24
+#Conv25,1
+Conv25
+#NML61,1
+BatchNorm25
+#NML62,1
+Relu25
+#NML63,1
+Conv26
+#NML64,1
+BatchNorm26
+#NML65,1
+Relu26
+#Conv27,1
+Conv27
+#NML66,1
+BatchNorm27
+#NML67,1
+Relu27
+#NML68,1
+Pool1
+FC1,10000,1024,1024,10
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/promise_src.cc b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/promise_src.cc
new file mode 100644
index 0000000000000000000000000000000000000000..146bc640cc4b1e8da65e3e7bb6cb5c7f2a007399
--- /dev/null
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/promise_src.cc
@@ -0,0 +1,420 @@
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <unistd.h>
+#include <fcntl.h>
+#include <sys/types.h>
+#include <sys/stat.h>
+#include <string.h>
+#include "../../../tensor_runtime/include/tensor_runtime.h"
+#include "../../include/utils.h"
+
+int main(){
+
+llvm_hpvm_initTensorRt(0);
+
+int total_runs = 100;
+for (int i = 0 ; i < total_runs; i++){
+
+
+startMemTracking();
+
+int test_input_size = 10000;
+int batch_size = 10000;
+int batch_count = test_input_size / batch_size;
+float final_accuracy = 0.0;
+
+for(int i = 0; i < batch_count; i++){
+
+
+
+std::string dir_prefix = std::string("data/mobilenet_quant/");
+std::string input_path = dir_prefix + std::string("input.bin");
+std::string labels_path = dir_prefix + std::string("labels.bin");
+std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
+void* conv2d_1_w = readTrainedWeights(conv2d_1_w_path.c_str(), 0,32,3,3,3);
+std::string batch_normalization_1_gamma_path = dir_prefix + std::string("batch_normalization_1_gamma.bin");
+void* batch_normalization_1_gamma = readTrainedWeights(batch_normalization_1_gamma_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_1_beta_path = dir_prefix + std::string("batch_normalization_1_beta.bin");
+void* batch_normalization_1_beta = readTrainedWeights(batch_normalization_1_beta_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_1_mean_path = dir_prefix + std::string("batch_normalization_1_mean.bin");
+void* batch_normalization_1_mean = readTrainedWeights(batch_normalization_1_mean_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_1_variance_path = dir_prefix + std::string("batch_normalization_1_variance.bin");
+void* batch_normalization_1_variance = readTrainedWeights(batch_normalization_1_variance_path.c_str(), 0,1,32,1,1);
+std::string depthwise_conv2d_1_w_path = dir_prefix + std::string("depthwise_conv2d_1_w.bin");
+void* depthwise_conv2d_1_w = readTrainedWeights(depthwise_conv2d_1_w_path.c_str(), 0,32,1,3,3);
+std::string batch_normalization_2_gamma_path = dir_prefix + std::string("batch_normalization_2_gamma.bin");
+void* batch_normalization_2_gamma = readTrainedWeights(batch_normalization_2_gamma_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_2_beta_path = dir_prefix + std::string("batch_normalization_2_beta.bin");
+void* batch_normalization_2_beta = readTrainedWeights(batch_normalization_2_beta_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_2_mean_path = dir_prefix + std::string("batch_normalization_2_mean.bin");
+void* batch_normalization_2_mean = readTrainedWeights(batch_normalization_2_mean_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_2_variance_path = dir_prefix + std::string("batch_normalization_2_variance.bin");
+void* batch_normalization_2_variance = readTrainedWeights(batch_normalization_2_variance_path.c_str(), 0,1,32,1,1);
+std::string conv2d_2_w_path = dir_prefix + std::string("conv2d_2_w.bin");
+void* conv2d_2_w = readTrainedWeights(conv2d_2_w_path.c_str(), 0,64,32,1,1);
+std::string batch_normalization_3_gamma_path = dir_prefix + std::string("batch_normalization_3_gamma.bin");
+void* batch_normalization_3_gamma = readTrainedWeights(batch_normalization_3_gamma_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_3_beta_path = dir_prefix + std::string("batch_normalization_3_beta.bin");
+void* batch_normalization_3_beta = readTrainedWeights(batch_normalization_3_beta_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_3_mean_path = dir_prefix + std::string("batch_normalization_3_mean.bin");
+void* batch_normalization_3_mean = readTrainedWeights(batch_normalization_3_mean_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_3_variance_path = dir_prefix + std::string("batch_normalization_3_variance.bin");
+void* batch_normalization_3_variance = readTrainedWeights(batch_normalization_3_variance_path.c_str(), 0,1,64,1,1);
+std::string depthwise_conv2d_2_w_path = dir_prefix + std::string("depthwise_conv2d_2_w.bin");
+void* depthwise_conv2d_2_w = readTrainedWeights(depthwise_conv2d_2_w_path.c_str(), 0,64,1,3,3);
+std::string batch_normalization_4_gamma_path = dir_prefix + std::string("batch_normalization_4_gamma.bin");
+void* batch_normalization_4_gamma = readTrainedWeights(batch_normalization_4_gamma_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_4_beta_path = dir_prefix + std::string("batch_normalization_4_beta.bin");
+void* batch_normalization_4_beta = readTrainedWeights(batch_normalization_4_beta_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_4_mean_path = dir_prefix + std::string("batch_normalization_4_mean.bin");
+void* batch_normalization_4_mean = readTrainedWeights(batch_normalization_4_mean_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_4_variance_path = dir_prefix + std::string("batch_normalization_4_variance.bin");
+void* batch_normalization_4_variance = readTrainedWeights(batch_normalization_4_variance_path.c_str(), 0,1,64,1,1);
+std::string conv2d_3_w_path = dir_prefix + std::string("conv2d_3_w.bin");
+void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,128,64,1,1);
+std::string batch_normalization_5_gamma_path = dir_prefix + std::string("batch_normalization_5_gamma.bin");
+void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_5_beta_path = dir_prefix + std::string("batch_normalization_5_beta.bin");
+void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_5_mean_path = dir_prefix + std::string("batch_normalization_5_mean.bin");
+void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_5_variance_path = dir_prefix + std::string("batch_normalization_5_variance.bin");
+void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,128,1,1);
+std::string depthwise_conv2d_3_w_path = dir_prefix + std::string("depthwise_conv2d_3_w.bin");
+void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,128,1,3,3);
+std::string batch_normalization_6_gamma_path = dir_prefix + std::string("batch_normalization_6_gamma.bin");
+void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_6_beta_path = dir_prefix + std::string("batch_normalization_6_beta.bin");
+void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_6_mean_path = dir_prefix + std::string("batch_normalization_6_mean.bin");
+void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_6_variance_path = dir_prefix + std::string("batch_normalization_6_variance.bin");
+void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,128,1,1);
+std::string conv2d_4_w_path = dir_prefix + std::string("conv2d_4_w.bin");
+void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,128,1,1);
+std::string batch_normalization_7_gamma_path = dir_prefix + std::string("batch_normalization_7_gamma.bin");
+void* batch_normalization_7_gamma = readTrainedWeights(batch_normalization_7_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_7_beta_path = dir_prefix + std::string("batch_normalization_7_beta.bin");
+void* batch_normalization_7_beta = readTrainedWeights(batch_normalization_7_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_7_mean_path = dir_prefix + std::string("batch_normalization_7_mean.bin");
+void* batch_normalization_7_mean = readTrainedWeights(batch_normalization_7_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_7_variance_path = dir_prefix + std::string("batch_normalization_7_variance.bin");
+void* batch_normalization_7_variance = readTrainedWeights(batch_normalization_7_variance_path.c_str(), 0,1,128,1,1);
+std::string depthwise_conv2d_4_w_path = dir_prefix + std::string("depthwise_conv2d_4_w.bin");
+void* depthwise_conv2d_4_w = readTrainedWeights(depthwise_conv2d_4_w_path.c_str(), 0,128,1,3,3);
+std::string batch_normalization_8_gamma_path = dir_prefix + std::string("batch_normalization_8_gamma.bin");
+void* batch_normalization_8_gamma = readTrainedWeights(batch_normalization_8_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_8_beta_path = dir_prefix + std::string("batch_normalization_8_beta.bin");
+void* batch_normalization_8_beta = readTrainedWeights(batch_normalization_8_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_8_mean_path = dir_prefix + std::string("batch_normalization_8_mean.bin");
+void* batch_normalization_8_mean = readTrainedWeights(batch_normalization_8_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_8_variance_path = dir_prefix + std::string("batch_normalization_8_variance.bin");
+void* batch_normalization_8_variance = readTrainedWeights(batch_normalization_8_variance_path.c_str(), 0,1,128,1,1);
+std::string conv2d_5_w_path = dir_prefix + std::string("conv2d_5_w.bin");
+void* conv2d_5_w = readTrainedWeights(conv2d_5_w_path.c_str(), 0,256,128,1,1);
+std::string batch_normalization_9_gamma_path = dir_prefix + std::string("batch_normalization_9_gamma.bin");
+void* batch_normalization_9_gamma = readTrainedWeights(batch_normalization_9_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_9_beta_path = dir_prefix + std::string("batch_normalization_9_beta.bin");
+void* batch_normalization_9_beta = readTrainedWeights(batch_normalization_9_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_9_mean_path = dir_prefix + std::string("batch_normalization_9_mean.bin");
+void* batch_normalization_9_mean = readTrainedWeights(batch_normalization_9_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_9_variance_path = dir_prefix + std::string("batch_normalization_9_variance.bin");
+void* batch_normalization_9_variance = readTrainedWeights(batch_normalization_9_variance_path.c_str(), 0,1,256,1,1);
+std::string depthwise_conv2d_5_w_path = dir_prefix + std::string("depthwise_conv2d_5_w.bin");
+void* depthwise_conv2d_5_w = readTrainedWeights(depthwise_conv2d_5_w_path.c_str(), 0,256,1,3,3);
+std::string batch_normalization_10_gamma_path = dir_prefix + std::string("batch_normalization_10_gamma.bin");
+void* batch_normalization_10_gamma = readTrainedWeights(batch_normalization_10_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_10_beta_path = dir_prefix + std::string("batch_normalization_10_beta.bin");
+void* batch_normalization_10_beta = readTrainedWeights(batch_normalization_10_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_10_mean_path = dir_prefix + std::string("batch_normalization_10_mean.bin");
+void* batch_normalization_10_mean = readTrainedWeights(batch_normalization_10_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_10_variance_path = dir_prefix + std::string("batch_normalization_10_variance.bin");
+void* batch_normalization_10_variance = readTrainedWeights(batch_normalization_10_variance_path.c_str(), 0,1,256,1,1);
+std::string conv2d_6_w_path = dir_prefix + std::string("conv2d_6_w.bin");
+void* conv2d_6_w = readTrainedWeights(conv2d_6_w_path.c_str(), 0,256,256,1,1);
+std::string batch_normalization_11_gamma_path = dir_prefix + std::string("batch_normalization_11_gamma.bin");
+void* batch_normalization_11_gamma = readTrainedWeights(batch_normalization_11_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_11_beta_path = dir_prefix + std::string("batch_normalization_11_beta.bin");
+void* batch_normalization_11_beta = readTrainedWeights(batch_normalization_11_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_11_mean_path = dir_prefix + std::string("batch_normalization_11_mean.bin");
+void* batch_normalization_11_mean = readTrainedWeights(batch_normalization_11_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_11_variance_path = dir_prefix + std::string("batch_normalization_11_variance.bin");
+void* batch_normalization_11_variance = readTrainedWeights(batch_normalization_11_variance_path.c_str(), 0,1,256,1,1);
+std::string depthwise_conv2d_6_w_path = dir_prefix + std::string("depthwise_conv2d_6_w.bin");
+void* depthwise_conv2d_6_w = readTrainedWeights(depthwise_conv2d_6_w_path.c_str(), 0,256,1,3,3);
+std::string batch_normalization_12_gamma_path = dir_prefix + std::string("batch_normalization_12_gamma.bin");
+void* batch_normalization_12_gamma = readTrainedWeights(batch_normalization_12_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_beta_path = dir_prefix + std::string("batch_normalization_12_beta.bin");
+void* batch_normalization_12_beta = readTrainedWeights(batch_normalization_12_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_mean_path = dir_prefix + std::string("batch_normalization_12_mean.bin");
+void* batch_normalization_12_mean = readTrainedWeights(batch_normalization_12_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_variance_path = dir_prefix + std::string("batch_normalization_12_variance.bin");
+void* batch_normalization_12_variance = readTrainedWeights(batch_normalization_12_variance_path.c_str(), 0,1,256,1,1);
+std::string conv2d_7_w_path = dir_prefix + std::string("conv2d_7_w.bin");
+void* conv2d_7_w = readTrainedWeights(conv2d_7_w_path.c_str(), 0,512,256,1,1);
+std::string batch_normalization_13_gamma_path = dir_prefix + std::string("batch_normalization_13_gamma.bin");
+void* batch_normalization_13_gamma = readTrainedWeights(batch_normalization_13_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_beta_path = dir_prefix + std::string("batch_normalization_13_beta.bin");
+void* batch_normalization_13_beta = readTrainedWeights(batch_normalization_13_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_mean_path = dir_prefix + std::string("batch_normalization_13_mean.bin");
+void* batch_normalization_13_mean = readTrainedWeights(batch_normalization_13_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_variance_path = dir_prefix + std::string("batch_normalization_13_variance.bin");
+void* batch_normalization_13_variance = readTrainedWeights(batch_normalization_13_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_7_w_path = dir_prefix + std::string("depthwise_conv2d_7_w.bin");
+void* depthwise_conv2d_7_w = readTrainedWeights(depthwise_conv2d_7_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_14_gamma_path = dir_prefix + std::string("batch_normalization_14_gamma.bin");
+void* batch_normalization_14_gamma = readTrainedWeights(batch_normalization_14_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_14_beta_path = dir_prefix + std::string("batch_normalization_14_beta.bin");
+void* batch_normalization_14_beta = readTrainedWeights(batch_normalization_14_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_14_mean_path = dir_prefix + std::string("batch_normalization_14_mean.bin");
+void* batch_normalization_14_mean = readTrainedWeights(batch_normalization_14_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_14_variance_path = dir_prefix + std::string("batch_normalization_14_variance.bin");
+void* batch_normalization_14_variance = readTrainedWeights(batch_normalization_14_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_8_w_path = dir_prefix + std::string("conv2d_8_w.bin");
+void* conv2d_8_w = readTrainedWeights(conv2d_8_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_15_gamma_path = dir_prefix + std::string("batch_normalization_15_gamma.bin");
+void* batch_normalization_15_gamma = readTrainedWeights(batch_normalization_15_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_15_beta_path = dir_prefix + std::string("batch_normalization_15_beta.bin");
+void* batch_normalization_15_beta = readTrainedWeights(batch_normalization_15_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_15_mean_path = dir_prefix + std::string("batch_normalization_15_mean.bin");
+void* batch_normalization_15_mean = readTrainedWeights(batch_normalization_15_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_15_variance_path = dir_prefix + std::string("batch_normalization_15_variance.bin");
+void* batch_normalization_15_variance = readTrainedWeights(batch_normalization_15_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_8_w_path = dir_prefix + std::string("depthwise_conv2d_8_w.bin");
+void* depthwise_conv2d_8_w = readTrainedWeights(depthwise_conv2d_8_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_16_gamma_path = dir_prefix + std::string("batch_normalization_16_gamma.bin");
+void* batch_normalization_16_gamma = readTrainedWeights(batch_normalization_16_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_16_beta_path = dir_prefix + std::string("batch_normalization_16_beta.bin");
+void* batch_normalization_16_beta = readTrainedWeights(batch_normalization_16_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_16_mean_path = dir_prefix + std::string("batch_normalization_16_mean.bin");
+void* batch_normalization_16_mean = readTrainedWeights(batch_normalization_16_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_16_variance_path = dir_prefix + std::string("batch_normalization_16_variance.bin");
+void* batch_normalization_16_variance = readTrainedWeights(batch_normalization_16_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_9_w_path = dir_prefix + std::string("conv2d_9_w.bin");
+void* conv2d_9_w = readTrainedWeights(conv2d_9_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_17_gamma_path = dir_prefix + std::string("batch_normalization_17_gamma.bin");
+void* batch_normalization_17_gamma = readTrainedWeights(batch_normalization_17_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_17_beta_path = dir_prefix + std::string("batch_normalization_17_beta.bin");
+void* batch_normalization_17_beta = readTrainedWeights(batch_normalization_17_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_17_mean_path = dir_prefix + std::string("batch_normalization_17_mean.bin");
+void* batch_normalization_17_mean = readTrainedWeights(batch_normalization_17_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_17_variance_path = dir_prefix + std::string("batch_normalization_17_variance.bin");
+void* batch_normalization_17_variance = readTrainedWeights(batch_normalization_17_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_9_w_path = dir_prefix + std::string("depthwise_conv2d_9_w.bin");
+void* depthwise_conv2d_9_w = readTrainedWeights(depthwise_conv2d_9_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_18_gamma_path = dir_prefix + std::string("batch_normalization_18_gamma.bin");
+void* batch_normalization_18_gamma = readTrainedWeights(batch_normalization_18_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_18_beta_path = dir_prefix + std::string("batch_normalization_18_beta.bin");
+void* batch_normalization_18_beta = readTrainedWeights(batch_normalization_18_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_18_mean_path = dir_prefix + std::string("batch_normalization_18_mean.bin");
+void* batch_normalization_18_mean = readTrainedWeights(batch_normalization_18_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_18_variance_path = dir_prefix + std::string("batch_normalization_18_variance.bin");
+void* batch_normalization_18_variance = readTrainedWeights(batch_normalization_18_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_10_w_path = dir_prefix + std::string("conv2d_10_w.bin");
+void* conv2d_10_w = readTrainedWeights(conv2d_10_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_19_gamma_path = dir_prefix + std::string("batch_normalization_19_gamma.bin");
+void* batch_normalization_19_gamma = readTrainedWeights(batch_normalization_19_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_19_beta_path = dir_prefix + std::string("batch_normalization_19_beta.bin");
+void* batch_normalization_19_beta = readTrainedWeights(batch_normalization_19_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_19_mean_path = dir_prefix + std::string("batch_normalization_19_mean.bin");
+void* batch_normalization_19_mean = readTrainedWeights(batch_normalization_19_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_19_variance_path = dir_prefix + std::string("batch_normalization_19_variance.bin");
+void* batch_normalization_19_variance = readTrainedWeights(batch_normalization_19_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_10_w_path = dir_prefix + std::string("depthwise_conv2d_10_w.bin");
+void* depthwise_conv2d_10_w = readTrainedWeights(depthwise_conv2d_10_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_20_gamma_path = dir_prefix + std::string("batch_normalization_20_gamma.bin");
+void* batch_normalization_20_gamma = readTrainedWeights(batch_normalization_20_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_20_beta_path = dir_prefix + std::string("batch_normalization_20_beta.bin");
+void* batch_normalization_20_beta = readTrainedWeights(batch_normalization_20_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_20_mean_path = dir_prefix + std::string("batch_normalization_20_mean.bin");
+void* batch_normalization_20_mean = readTrainedWeights(batch_normalization_20_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_20_variance_path = dir_prefix + std::string("batch_normalization_20_variance.bin");
+void* batch_normalization_20_variance = readTrainedWeights(batch_normalization_20_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_11_w_path = dir_prefix + std::string("conv2d_11_w.bin");
+void* conv2d_11_w = readTrainedWeights(conv2d_11_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_21_gamma_path = dir_prefix + std::string("batch_normalization_21_gamma.bin");
+void* batch_normalization_21_gamma = readTrainedWeights(batch_normalization_21_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_21_beta_path = dir_prefix + std::string("batch_normalization_21_beta.bin");
+void* batch_normalization_21_beta = readTrainedWeights(batch_normalization_21_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_21_mean_path = dir_prefix + std::string("batch_normalization_21_mean.bin");
+void* batch_normalization_21_mean = readTrainedWeights(batch_normalization_21_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_21_variance_path = dir_prefix + std::string("batch_normalization_21_variance.bin");
+void* batch_normalization_21_variance = readTrainedWeights(batch_normalization_21_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_11_w_path = dir_prefix + std::string("depthwise_conv2d_11_w.bin");
+void* depthwise_conv2d_11_w = readTrainedWeights(depthwise_conv2d_11_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_22_gamma_path = dir_prefix + std::string("batch_normalization_22_gamma.bin");
+void* batch_normalization_22_gamma = readTrainedWeights(batch_normalization_22_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_22_beta_path = dir_prefix + std::string("batch_normalization_22_beta.bin");
+void* batch_normalization_22_beta = readTrainedWeights(batch_normalization_22_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_22_mean_path = dir_prefix + std::string("batch_normalization_22_mean.bin");
+void* batch_normalization_22_mean = readTrainedWeights(batch_normalization_22_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_22_variance_path = dir_prefix + std::string("batch_normalization_22_variance.bin");
+void* batch_normalization_22_variance = readTrainedWeights(batch_normalization_22_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_12_w_path = dir_prefix + std::string("conv2d_12_w.bin");
+void* conv2d_12_w = readTrainedWeights(conv2d_12_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_23_gamma_path = dir_prefix + std::string("batch_normalization_23_gamma.bin");
+void* batch_normalization_23_gamma = readTrainedWeights(batch_normalization_23_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_23_beta_path = dir_prefix + std::string("batch_normalization_23_beta.bin");
+void* batch_normalization_23_beta = readTrainedWeights(batch_normalization_23_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_23_mean_path = dir_prefix + std::string("batch_normalization_23_mean.bin");
+void* batch_normalization_23_mean = readTrainedWeights(batch_normalization_23_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_23_variance_path = dir_prefix + std::string("batch_normalization_23_variance.bin");
+void* batch_normalization_23_variance = readTrainedWeights(batch_normalization_23_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_12_w_path = dir_prefix + std::string("depthwise_conv2d_12_w.bin");
+void* depthwise_conv2d_12_w = readTrainedWeights(depthwise_conv2d_12_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_24_gamma_path = dir_prefix + std::string("batch_normalization_24_gamma.bin");
+void* batch_normalization_24_gamma = readTrainedWeights(batch_normalization_24_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_24_beta_path = dir_prefix + std::string("batch_normalization_24_beta.bin");
+void* batch_normalization_24_beta = readTrainedWeights(batch_normalization_24_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_24_mean_path = dir_prefix + std::string("batch_normalization_24_mean.bin");
+void* batch_normalization_24_mean = readTrainedWeights(batch_normalization_24_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_24_variance_path = dir_prefix + std::string("batch_normalization_24_variance.bin");
+void* batch_normalization_24_variance = readTrainedWeights(batch_normalization_24_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_13_w_path = dir_prefix + std::string("conv2d_13_w.bin");
+void* conv2d_13_w = readTrainedWeights(conv2d_13_w_path.c_str(), 0,1024,512,1,1);
+std::string batch_normalization_25_gamma_path = dir_prefix + std::string("batch_normalization_25_gamma.bin");
+void* batch_normalization_25_gamma = readTrainedWeights(batch_normalization_25_gamma_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_25_beta_path = dir_prefix + std::string("batch_normalization_25_beta.bin");
+void* batch_normalization_25_beta = readTrainedWeights(batch_normalization_25_beta_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_25_mean_path = dir_prefix + std::string("batch_normalization_25_mean.bin");
+void* batch_normalization_25_mean = readTrainedWeights(batch_normalization_25_mean_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_25_variance_path = dir_prefix + std::string("batch_normalization_25_variance.bin");
+void* batch_normalization_25_variance = readTrainedWeights(batch_normalization_25_variance_path.c_str(), 0,1,1024,1,1);
+std::string depthwise_conv2d_13_w_path = dir_prefix + std::string("depthwise_conv2d_13_w.bin");
+void* depthwise_conv2d_13_w = readTrainedWeights(depthwise_conv2d_13_w_path.c_str(), 0,1024,1,3,3);
+std::string batch_normalization_26_gamma_path = dir_prefix + std::string("batch_normalization_26_gamma.bin");
+void* batch_normalization_26_gamma = readTrainedWeights(batch_normalization_26_gamma_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_26_beta_path = dir_prefix + std::string("batch_normalization_26_beta.bin");
+void* batch_normalization_26_beta = readTrainedWeights(batch_normalization_26_beta_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_26_mean_path = dir_prefix + std::string("batch_normalization_26_mean.bin");
+void* batch_normalization_26_mean = readTrainedWeights(batch_normalization_26_mean_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_26_variance_path = dir_prefix + std::string("batch_normalization_26_variance.bin");
+void* batch_normalization_26_variance = readTrainedWeights(batch_normalization_26_variance_path.c_str(), 0,1,1024,1,1);
+std::string conv2d_14_w_path = dir_prefix + std::string("conv2d_14_w.bin");
+void* conv2d_14_w = readTrainedWeights(conv2d_14_w_path.c_str(), 0,1024,1024,1,1);
+std::string batch_normalization_27_gamma_path = dir_prefix + std::string("batch_normalization_27_gamma.bin");
+void* batch_normalization_27_gamma = readTrainedWeights(batch_normalization_27_gamma_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_27_beta_path = dir_prefix + std::string("batch_normalization_27_beta.bin");
+void* batch_normalization_27_beta = readTrainedWeights(batch_normalization_27_beta_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_27_mean_path = dir_prefix + std::string("batch_normalization_27_mean.bin");
+void* batch_normalization_27_mean = readTrainedWeights(batch_normalization_27_mean_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_27_variance_path = dir_prefix + std::string("batch_normalization_27_variance.bin");
+void* batch_normalization_27_variance = readTrainedWeights(batch_normalization_27_variance_path.c_str(), 0,1,1024,1,1);
+std::string dense_1_w_path = dir_prefix + std::string("dense_1_w.bin");
+void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,1024,10);
+std::string dense_1_b_path = dir_prefix + std::string("dense_1_b.bin");
+void* dense_1_b = readTrainedWeights(dense_1_b_path.c_str(), 0,1,10,1,1);
+
+
+int start = i * batch_size;
+int end = (i + 1) * batch_size;
+
+void* input = readInputBatch(input_path.c_str(),0,start,end,3,32,32);
+
+void* var_0 = ConvLayer_PROMISE(input, -1.9892114, 2.126797, conv2d_1_w, -2.196306920051575, 1.347581704139706, NULL, 0, 0, 1, 1, 1, 1, -1, 0, -1, -60.89275047302246, 51.99256916046146, 9);
+void* var_1 = tensorBatchNorm(var_0, batch_normalization_1_gamma, batch_normalization_1_beta, batch_normalization_1_mean, batch_normalization_1_variance, 0.001);
+void* var_2 = tensorRelu(var_1);
+void* var_3 = tensorConvolution(var_2, depthwise_conv2d_1_w, 1, 1, 1, 1, 1, 32);
+void* var_4 = tensorBatchNorm(var_3, batch_normalization_2_gamma, batch_normalization_2_beta, batch_normalization_2_mean, batch_normalization_2_variance, 0.001);
+void* var_5 = tensorRelu(var_4);
+void* var_6 = ConvLayer_PROMISE(var_5, 0.0, 5.713541553974245, conv2d_2_w, -0.9317721160650253, 1.0774258937835774, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -6.518589503288269, 6.810842518806449, 9);
+void* var_7 = tensorBatchNorm(var_6, batch_normalization_3_gamma, batch_normalization_3_beta, batch_normalization_3_mean, batch_normalization_3_variance, 0.001);
+void* var_8 = tensorRelu(var_7);
+void* var_9 = tensorConvolution(var_8, depthwise_conv2d_2_w, 1, 1, 2, 2, 1, 64);
+void* var_10 = tensorBatchNorm(var_9, batch_normalization_4_gamma, batch_normalization_4_beta, batch_normalization_4_mean, batch_normalization_4_variance, 0.001);
+void* var_11 = tensorRelu(var_10);
+void* var_12 = ConvLayer_PROMISE(var_11, 0.0, 4.932139402866376, conv2d_3_w, -0.5316544661521911, 0.5753790403604531, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -4.482631235122681, 3.96730119752885, 9);
+void* var_13 = tensorBatchNorm(var_12, batch_normalization_5_gamma, batch_normalization_5_beta, batch_normalization_5_mean, batch_normalization_5_variance, 0.001);
+void* var_14 = tensorRelu(var_13);
+void* var_15 = tensorConvolution(var_14, depthwise_conv2d_3_w, 1, 1, 1, 1, 1, 128);
+void* var_16 = tensorBatchNorm(var_15, batch_normalization_6_gamma, batch_normalization_6_beta, batch_normalization_6_mean, batch_normalization_6_variance, 0.001);
+void* var_17 = tensorRelu(var_16);
+void* var_18 = ConvLayer_PROMISE(var_17, 0.0, 4.103263397693674, conv2d_4_w, -0.36234098821878435, 0.4076913900375366, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -4.04261828327179, 3.88677932929993, 9);
+void* var_19 = tensorBatchNorm(var_18, batch_normalization_7_gamma, batch_normalization_7_beta, batch_normalization_7_mean, batch_normalization_7_variance, 0.001);
+void* var_20 = tensorRelu(var_19);
+void* var_21 = tensorConvolution(var_20, depthwise_conv2d_4_w, 1, 1, 2, 2, 1, 128);
+void* var_22 = tensorBatchNorm(var_21, batch_normalization_8_gamma, batch_normalization_8_beta, batch_normalization_8_mean, batch_normalization_8_variance, 0.001);
+void* var_23 = tensorRelu(var_22);
+void* var_24 = ConvLayer_PROMISE(var_23, 0.0, 5.383221302509475, conv2d_5_w, -0.3131200549006462, 0.29357679939270065, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -5.921469215393066, 4.338679324150087, 9);
+void* var_25 = tensorBatchNorm(var_24, batch_normalization_9_gamma, batch_normalization_9_beta, batch_normalization_9_mean, batch_normalization_9_variance, 0.001);
+void* var_26 = tensorRelu(var_25);
+void* var_27 = tensorConvolution(var_26, depthwise_conv2d_5_w, 1, 1, 1, 1, 1, 256);
+void* var_28 = tensorBatchNorm(var_27, batch_normalization_10_gamma, batch_normalization_10_beta, batch_normalization_10_mean, batch_normalization_10_variance, 0.001);
+void* var_29 = tensorRelu(var_28);
+void* var_30 = ConvLayer_PROMISE(var_29, 0.0, 4.316738154411368, conv2d_6_w, -0.23299247801303866, 0.2580290257930756, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -4.207789947509766, 3.932436970710759, 9);
+void* var_31 = tensorBatchNorm(var_30, batch_normalization_11_gamma, batch_normalization_11_beta, batch_normalization_11_mean, batch_normalization_11_variance, 0.001);
+void* var_32 = tensorRelu(var_31);
+void* var_33 = tensorConvolution(var_32, depthwise_conv2d_6_w, 1, 1, 2, 2, 1, 256);
+void* var_34 = tensorBatchNorm(var_33, batch_normalization_12_gamma, batch_normalization_12_beta, batch_normalization_12_mean, batch_normalization_12_variance, 0.001);
+void* var_35 = tensorRelu(var_34);
+void* var_36 = ConvLayer_PROMISE(var_35, 0.0, 5.830408106803901, conv2d_7_w, -0.20233777219057084, 0.18998308175802117, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -6.298286915779113, 4.848135117530843, 9);
+void* var_37 = tensorBatchNorm(var_36, batch_normalization_13_gamma, batch_normalization_13_beta, batch_normalization_13_mean, batch_normalization_13_variance, 0.001);
+void* var_38 = tensorRelu(var_37);
+void* var_39 = tensorConvolution(var_38, depthwise_conv2d_7_w, 1, 1, 1, 1, 1, 512);
+void* var_40 = tensorBatchNorm(var_39, batch_normalization_14_gamma, batch_normalization_14_beta, batch_normalization_14_mean, batch_normalization_14_variance, 0.001);
+void* var_41 = tensorRelu(var_40);
+void* var_42 = ConvLayer_PROMISE(var_41, 0.0, 4.446417809963227, conv2d_8_w, -0.17442735651135444, 0.17695830866694454, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -4.347910885810852, 3.6144364695549145, 9);
+void* var_43 = tensorBatchNorm(var_42, batch_normalization_15_gamma, batch_normalization_15_beta, batch_normalization_15_mean, batch_normalization_15_variance, 0.001);
+void* var_44 = tensorRelu(var_43);
+void* var_45 = tensorConvolution(var_44, depthwise_conv2d_8_w, 1, 1, 1, 1, 1, 512);
+void* var_46 = tensorBatchNorm(var_45, batch_normalization_16_gamma, batch_normalization_16_beta, batch_normalization_16_mean, batch_normalization_16_variance, 0.001);
+void* var_47 = tensorRelu(var_46);
+void* var_48 = ConvLayer_PROMISE(var_47, 0.0, 4.518095604896667, conv2d_9_w, -0.14546796187758446, 0.15256431668996823, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -3.0287702755928043, 2.9487365779876953, 9);
+void* var_49 = tensorBatchNorm(var_48, batch_normalization_17_gamma, batch_normalization_17_beta, batch_normalization_17_mean, batch_normalization_17_variance, 0.001);
+void* var_50 = tensorRelu(var_49);
+void* var_51 = tensorConvolution(var_50, depthwise_conv2d_9_w, 1, 1, 1, 1, 1, 512);
+void* var_52 = tensorBatchNorm(var_51, batch_normalization_18_gamma, batch_normalization_18_beta, batch_normalization_18_mean, batch_normalization_18_variance, 0.001);
+void* var_53 = tensorRelu(var_52);
+void* var_54 = ConvLayer_PROMISE(var_53, 0.0, 6.348575634956407, conv2d_10_w, -0.13025874522328376, 0.13558243343234128, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -4.2293100805282595, 3.5315046372413645, 9);
+void* var_55 = tensorBatchNorm(var_54, batch_normalization_19_gamma, batch_normalization_19_beta, batch_normalization_19_mean, batch_normalization_19_variance, 0.001);
+void* var_56 = tensorRelu(var_55);
+void* var_57 = tensorConvolution(var_56, depthwise_conv2d_10_w, 1, 1, 1, 1, 1, 512);
+void* var_58 = tensorBatchNorm(var_57, batch_normalization_20_gamma, batch_normalization_20_beta, batch_normalization_20_mean, batch_normalization_20_variance, 0.001);
+void* var_59 = tensorRelu(var_58);
+void* var_60 = ConvLayer_PROMISE(var_59, 0.0, 5.221003110408843, conv2d_11_w, -0.11900172759592534, 0.12536374783515936, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -4.038203780174255, 4.004009407043483, 9);
+void* var_61 = tensorBatchNorm(var_60, batch_normalization_21_gamma, batch_normalization_21_beta, batch_normalization_21_mean, batch_normalization_21_variance, 0.001);
+void* var_62 = tensorRelu(var_61);
+void* var_63 = tensorConvolution(var_62, depthwise_conv2d_11_w, 1, 1, 1, 1, 1, 512);
+void* var_64 = tensorBatchNorm(var_63, batch_normalization_22_gamma, batch_normalization_22_beta, batch_normalization_22_mean, batch_normalization_22_variance, 0.001);
+void* var_65 = tensorRelu(var_64);
+void* var_66 = ConvLayer_PROMISE(var_65, 0.0, 5.732498347759442, conv2d_12_w, -0.10839721685647964, 0.11625668607652187, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -3.3111015114784244, 4.462933233261136, 9);
+void* var_67 = tensorBatchNorm(var_66, batch_normalization_23_gamma, batch_normalization_23_beta, batch_normalization_23_mean, batch_normalization_23_variance, 0.001);
+void* var_68 = tensorRelu(var_67);
+void* var_69 = tensorConvolution(var_68, depthwise_conv2d_12_w, 1, 1, 2, 2, 1, 512);
+void* var_70 = tensorBatchNorm(var_69, batch_normalization_24_gamma, batch_normalization_24_beta, batch_normalization_24_mean, batch_normalization_24_variance, 0.001);
+void* var_71 = tensorRelu(var_70);
+void* var_72 = ConvLayer_PROMISE(var_71, 0.0, 7.240498211860681, conv2d_13_w, -0.08623744961619377, 0.08859449951350662, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -4.175431394577027, 6.2043294754027345, 9);
+void* var_73 = tensorBatchNorm(var_72, batch_normalization_25_gamma, batch_normalization_25_beta, batch_normalization_25_mean, batch_normalization_25_variance, 0.001);
+void* var_74 = tensorRelu(var_73);
+void* var_75 = tensorConvolution(var_74, depthwise_conv2d_13_w, 1, 1, 1, 1, 1, 1024);
+void* var_76 = tensorBatchNorm(var_75, batch_normalization_26_gamma, batch_normalization_26_beta, batch_normalization_26_mean, batch_normalization_26_variance, 0.001);
+void* var_77 = tensorRelu(var_76);
+void* var_78 = ConvLayer_PROMISE(var_77, 0.0, 7.813958834648251, conv2d_14_w, -0.06813025139272214, 0.07002027779817581, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -10.920566423416137, 2.6442912578582534, 9);
+void* var_79 = tensorBatchNorm(var_78, batch_normalization_27_gamma, batch_normalization_27_beta, batch_normalization_27_mean, batch_normalization_27_variance, 0.001);
+void* var_80 = tensorRelu(var_79);
+void* var_81 = tensorPooling(var_80,1,2,2,0,0,2,2);
+void* var_82 = FCLayer_PROMISE(var_81, 0.0, 2.8692066650391013, dense_1_w, -0.22301019695401192, 0.1442659378200768, dense_1_b, -0.1654396, 0.23336112, -1, -12.245949958801269, 23.80532513427739, 9);
+void* var_83 = tensorSoftmax(var_82);
+
+uint8_t* labels = readLabelsBatch(labels_path.c_str(),start,end);
+
+float accuracy = computeAccuracy2(labels, batch_size, var_83);
+final_accuracy += accuracy;
+freeBatchMemory();
+
+}
+
+final_accuracy = final_accuracy / batch_count;
+dumpFinalAccuracy(final_accuracy);
+
+
+}
+
+dumpExecutionAccuracies();
+
+llvm_hpvm_cleanupTensorRt();
+
+return 0;
+
+}
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/src.cc b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/src.cc
new file mode 100644
index 0000000000000000000000000000000000000000..25aec9bde3bc1aac157e2acc368dcddf866e455d
--- /dev/null
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet/src.cc
@@ -0,0 +1,413 @@
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <unistd.h>
+#include <fcntl.h>
+#include <sys/types.h>
+#include <sys/stat.h>
+#include <string.h>
+#include "../../tensor_runtime/include/tensor_runtime.h"
+#include "../include/utils.h"
+
+int main(){
+
+llvm_hpvm_initTensorRt(0);
+
+
+std::string dir_prefix = std::string("data/mobilenet_quant/");
+std::string input_path = dir_prefix + std::string("input.bin");
+std::string labels_path = dir_prefix + std::string("labels.bin");
+std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
+void* conv2d_1_w = readTrainedWeights(conv2d_1_w_path.c_str(), 0,32,3,3,3);
+std::string batch_normalization_1_gamma_path = dir_prefix + std::string("batch_normalization_1_gamma.bin");
+void* batch_normalization_1_gamma = readTrainedWeights(batch_normalization_1_gamma_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_1_beta_path = dir_prefix + std::string("batch_normalization_1_beta.bin");
+void* batch_normalization_1_beta = readTrainedWeights(batch_normalization_1_beta_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_1_mean_path = dir_prefix + std::string("batch_normalization_1_mean.bin");
+void* batch_normalization_1_mean = readTrainedWeights(batch_normalization_1_mean_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_1_variance_path = dir_prefix + std::string("batch_normalization_1_variance.bin");
+void* batch_normalization_1_variance = readTrainedWeights(batch_normalization_1_variance_path.c_str(), 0,1,32,1,1);
+std::string depthwise_conv2d_1_w_path = dir_prefix + std::string("depthwise_conv2d_1_w.bin");
+void* depthwise_conv2d_1_w = readTrainedWeights(depthwise_conv2d_1_w_path.c_str(), 0,32,1,3,3);
+std::string batch_normalization_2_gamma_path = dir_prefix + std::string("batch_normalization_2_gamma.bin");
+void* batch_normalization_2_gamma = readTrainedWeights(batch_normalization_2_gamma_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_2_beta_path = dir_prefix + std::string("batch_normalization_2_beta.bin");
+void* batch_normalization_2_beta = readTrainedWeights(batch_normalization_2_beta_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_2_mean_path = dir_prefix + std::string("batch_normalization_2_mean.bin");
+void* batch_normalization_2_mean = readTrainedWeights(batch_normalization_2_mean_path.c_str(), 0,1,32,1,1);
+std::string batch_normalization_2_variance_path = dir_prefix + std::string("batch_normalization_2_variance.bin");
+void* batch_normalization_2_variance = readTrainedWeights(batch_normalization_2_variance_path.c_str(), 0,1,32,1,1);
+std::string conv2d_2_w_path = dir_prefix + std::string("conv2d_2_w.bin");
+void* conv2d_2_w = readTrainedWeights(conv2d_2_w_path.c_str(), 0,64,32,1,1);
+std::string batch_normalization_3_gamma_path = dir_prefix + std::string("batch_normalization_3_gamma.bin");
+void* batch_normalization_3_gamma = readTrainedWeights(batch_normalization_3_gamma_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_3_beta_path = dir_prefix + std::string("batch_normalization_3_beta.bin");
+void* batch_normalization_3_beta = readTrainedWeights(batch_normalization_3_beta_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_3_mean_path = dir_prefix + std::string("batch_normalization_3_mean.bin");
+void* batch_normalization_3_mean = readTrainedWeights(batch_normalization_3_mean_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_3_variance_path = dir_prefix + std::string("batch_normalization_3_variance.bin");
+void* batch_normalization_3_variance = readTrainedWeights(batch_normalization_3_variance_path.c_str(), 0,1,64,1,1);
+std::string depthwise_conv2d_2_w_path = dir_prefix + std::string("depthwise_conv2d_2_w.bin");
+void* depthwise_conv2d_2_w = readTrainedWeights(depthwise_conv2d_2_w_path.c_str(), 0,64,1,3,3);
+std::string batch_normalization_4_gamma_path = dir_prefix + std::string("batch_normalization_4_gamma.bin");
+void* batch_normalization_4_gamma = readTrainedWeights(batch_normalization_4_gamma_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_4_beta_path = dir_prefix + std::string("batch_normalization_4_beta.bin");
+void* batch_normalization_4_beta = readTrainedWeights(batch_normalization_4_beta_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_4_mean_path = dir_prefix + std::string("batch_normalization_4_mean.bin");
+void* batch_normalization_4_mean = readTrainedWeights(batch_normalization_4_mean_path.c_str(), 0,1,64,1,1);
+std::string batch_normalization_4_variance_path = dir_prefix + std::string("batch_normalization_4_variance.bin");
+void* batch_normalization_4_variance = readTrainedWeights(batch_normalization_4_variance_path.c_str(), 0,1,64,1,1);
+std::string conv2d_3_w_path = dir_prefix + std::string("conv2d_3_w.bin");
+void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,128,64,1,1);
+std::string batch_normalization_5_gamma_path = dir_prefix + std::string("batch_normalization_5_gamma.bin");
+void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_5_beta_path = dir_prefix + std::string("batch_normalization_5_beta.bin");
+void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_5_mean_path = dir_prefix + std::string("batch_normalization_5_mean.bin");
+void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_5_variance_path = dir_prefix + std::string("batch_normalization_5_variance.bin");
+void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,128,1,1);
+std::string depthwise_conv2d_3_w_path = dir_prefix + std::string("depthwise_conv2d_3_w.bin");
+void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,128,1,3,3);
+std::string batch_normalization_6_gamma_path = dir_prefix + std::string("batch_normalization_6_gamma.bin");
+void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_6_beta_path = dir_prefix + std::string("batch_normalization_6_beta.bin");
+void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_6_mean_path = dir_prefix + std::string("batch_normalization_6_mean.bin");
+void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_6_variance_path = dir_prefix + std::string("batch_normalization_6_variance.bin");
+void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,128,1,1);
+std::string conv2d_4_w_path = dir_prefix + std::string("conv2d_4_w.bin");
+void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,128,1,1);
+std::string batch_normalization_7_gamma_path = dir_prefix + std::string("batch_normalization_7_gamma.bin");
+void* batch_normalization_7_gamma = readTrainedWeights(batch_normalization_7_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_7_beta_path = dir_prefix + std::string("batch_normalization_7_beta.bin");
+void* batch_normalization_7_beta = readTrainedWeights(batch_normalization_7_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_7_mean_path = dir_prefix + std::string("batch_normalization_7_mean.bin");
+void* batch_normalization_7_mean = readTrainedWeights(batch_normalization_7_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_7_variance_path = dir_prefix + std::string("batch_normalization_7_variance.bin");
+void* batch_normalization_7_variance = readTrainedWeights(batch_normalization_7_variance_path.c_str(), 0,1,128,1,1);
+std::string depthwise_conv2d_4_w_path = dir_prefix + std::string("depthwise_conv2d_4_w.bin");
+void* depthwise_conv2d_4_w = readTrainedWeights(depthwise_conv2d_4_w_path.c_str(), 0,128,1,3,3);
+std::string batch_normalization_8_gamma_path = dir_prefix + std::string("batch_normalization_8_gamma.bin");
+void* batch_normalization_8_gamma = readTrainedWeights(batch_normalization_8_gamma_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_8_beta_path = dir_prefix + std::string("batch_normalization_8_beta.bin");
+void* batch_normalization_8_beta = readTrainedWeights(batch_normalization_8_beta_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_8_mean_path = dir_prefix + std::string("batch_normalization_8_mean.bin");
+void* batch_normalization_8_mean = readTrainedWeights(batch_normalization_8_mean_path.c_str(), 0,1,128,1,1);
+std::string batch_normalization_8_variance_path = dir_prefix + std::string("batch_normalization_8_variance.bin");
+void* batch_normalization_8_variance = readTrainedWeights(batch_normalization_8_variance_path.c_str(), 0,1,128,1,1);
+std::string conv2d_5_w_path = dir_prefix + std::string("conv2d_5_w.bin");
+void* conv2d_5_w = readTrainedWeights(conv2d_5_w_path.c_str(), 0,256,128,1,1);
+std::string batch_normalization_9_gamma_path = dir_prefix + std::string("batch_normalization_9_gamma.bin");
+void* batch_normalization_9_gamma = readTrainedWeights(batch_normalization_9_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_9_beta_path = dir_prefix + std::string("batch_normalization_9_beta.bin");
+void* batch_normalization_9_beta = readTrainedWeights(batch_normalization_9_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_9_mean_path = dir_prefix + std::string("batch_normalization_9_mean.bin");
+void* batch_normalization_9_mean = readTrainedWeights(batch_normalization_9_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_9_variance_path = dir_prefix + std::string("batch_normalization_9_variance.bin");
+void* batch_normalization_9_variance = readTrainedWeights(batch_normalization_9_variance_path.c_str(), 0,1,256,1,1);
+std::string depthwise_conv2d_5_w_path = dir_prefix + std::string("depthwise_conv2d_5_w.bin");
+void* depthwise_conv2d_5_w = readTrainedWeights(depthwise_conv2d_5_w_path.c_str(), 0,256,1,3,3);
+std::string batch_normalization_10_gamma_path = dir_prefix + std::string("batch_normalization_10_gamma.bin");
+void* batch_normalization_10_gamma = readTrainedWeights(batch_normalization_10_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_10_beta_path = dir_prefix + std::string("batch_normalization_10_beta.bin");
+void* batch_normalization_10_beta = readTrainedWeights(batch_normalization_10_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_10_mean_path = dir_prefix + std::string("batch_normalization_10_mean.bin");
+void* batch_normalization_10_mean = readTrainedWeights(batch_normalization_10_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_10_variance_path = dir_prefix + std::string("batch_normalization_10_variance.bin");
+void* batch_normalization_10_variance = readTrainedWeights(batch_normalization_10_variance_path.c_str(), 0,1,256,1,1);
+std::string conv2d_6_w_path = dir_prefix + std::string("conv2d_6_w.bin");
+void* conv2d_6_w = readTrainedWeights(conv2d_6_w_path.c_str(), 0,256,256,1,1);
+std::string batch_normalization_11_gamma_path = dir_prefix + std::string("batch_normalization_11_gamma.bin");
+void* batch_normalization_11_gamma = readTrainedWeights(batch_normalization_11_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_11_beta_path = dir_prefix + std::string("batch_normalization_11_beta.bin");
+void* batch_normalization_11_beta = readTrainedWeights(batch_normalization_11_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_11_mean_path = dir_prefix + std::string("batch_normalization_11_mean.bin");
+void* batch_normalization_11_mean = readTrainedWeights(batch_normalization_11_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_11_variance_path = dir_prefix + std::string("batch_normalization_11_variance.bin");
+void* batch_normalization_11_variance = readTrainedWeights(batch_normalization_11_variance_path.c_str(), 0,1,256,1,1);
+std::string depthwise_conv2d_6_w_path = dir_prefix + std::string("depthwise_conv2d_6_w.bin");
+void* depthwise_conv2d_6_w = readTrainedWeights(depthwise_conv2d_6_w_path.c_str(), 0,256,1,3,3);
+std::string batch_normalization_12_gamma_path = dir_prefix + std::string("batch_normalization_12_gamma.bin");
+void* batch_normalization_12_gamma = readTrainedWeights(batch_normalization_12_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_beta_path = dir_prefix + std::string("batch_normalization_12_beta.bin");
+void* batch_normalization_12_beta = readTrainedWeights(batch_normalization_12_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_mean_path = dir_prefix + std::string("batch_normalization_12_mean.bin");
+void* batch_normalization_12_mean = readTrainedWeights(batch_normalization_12_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_variance_path = dir_prefix + std::string("batch_normalization_12_variance.bin");
+void* batch_normalization_12_variance = readTrainedWeights(batch_normalization_12_variance_path.c_str(), 0,1,256,1,1);
+std::string conv2d_7_w_path = dir_prefix + std::string("conv2d_7_w.bin");
+void* conv2d_7_w = readTrainedWeights(conv2d_7_w_path.c_str(), 0,512,256,1,1);
+std::string batch_normalization_13_gamma_path = dir_prefix + std::string("batch_normalization_13_gamma.bin");
+void* batch_normalization_13_gamma = readTrainedWeights(batch_normalization_13_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_beta_path = dir_prefix + std::string("batch_normalization_13_beta.bin");
+void* batch_normalization_13_beta = readTrainedWeights(batch_normalization_13_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_mean_path = dir_prefix + std::string("batch_normalization_13_mean.bin");
+void* batch_normalization_13_mean = readTrainedWeights(batch_normalization_13_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_variance_path = dir_prefix + std::string("batch_normalization_13_variance.bin");
+void* batch_normalization_13_variance = readTrainedWeights(batch_normalization_13_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_7_w_path = dir_prefix + std::string("depthwise_conv2d_7_w.bin");
+void* depthwise_conv2d_7_w = readTrainedWeights(depthwise_conv2d_7_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_14_gamma_path = dir_prefix + std::string("batch_normalization_14_gamma.bin");
+void* batch_normalization_14_gamma = readTrainedWeights(batch_normalization_14_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_14_beta_path = dir_prefix + std::string("batch_normalization_14_beta.bin");
+void* batch_normalization_14_beta = readTrainedWeights(batch_normalization_14_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_14_mean_path = dir_prefix + std::string("batch_normalization_14_mean.bin");
+void* batch_normalization_14_mean = readTrainedWeights(batch_normalization_14_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_14_variance_path = dir_prefix + std::string("batch_normalization_14_variance.bin");
+void* batch_normalization_14_variance = readTrainedWeights(batch_normalization_14_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_8_w_path = dir_prefix + std::string("conv2d_8_w.bin");
+void* conv2d_8_w = readTrainedWeights(conv2d_8_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_15_gamma_path = dir_prefix + std::string("batch_normalization_15_gamma.bin");
+void* batch_normalization_15_gamma = readTrainedWeights(batch_normalization_15_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_15_beta_path = dir_prefix + std::string("batch_normalization_15_beta.bin");
+void* batch_normalization_15_beta = readTrainedWeights(batch_normalization_15_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_15_mean_path = dir_prefix + std::string("batch_normalization_15_mean.bin");
+void* batch_normalization_15_mean = readTrainedWeights(batch_normalization_15_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_15_variance_path = dir_prefix + std::string("batch_normalization_15_variance.bin");
+void* batch_normalization_15_variance = readTrainedWeights(batch_normalization_15_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_8_w_path = dir_prefix + std::string("depthwise_conv2d_8_w.bin");
+void* depthwise_conv2d_8_w = readTrainedWeights(depthwise_conv2d_8_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_16_gamma_path = dir_prefix + std::string("batch_normalization_16_gamma.bin");
+void* batch_normalization_16_gamma = readTrainedWeights(batch_normalization_16_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_16_beta_path = dir_prefix + std::string("batch_normalization_16_beta.bin");
+void* batch_normalization_16_beta = readTrainedWeights(batch_normalization_16_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_16_mean_path = dir_prefix + std::string("batch_normalization_16_mean.bin");
+void* batch_normalization_16_mean = readTrainedWeights(batch_normalization_16_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_16_variance_path = dir_prefix + std::string("batch_normalization_16_variance.bin");
+void* batch_normalization_16_variance = readTrainedWeights(batch_normalization_16_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_9_w_path = dir_prefix + std::string("conv2d_9_w.bin");
+void* conv2d_9_w = readTrainedWeights(conv2d_9_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_17_gamma_path = dir_prefix + std::string("batch_normalization_17_gamma.bin");
+void* batch_normalization_17_gamma = readTrainedWeights(batch_normalization_17_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_17_beta_path = dir_prefix + std::string("batch_normalization_17_beta.bin");
+void* batch_normalization_17_beta = readTrainedWeights(batch_normalization_17_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_17_mean_path = dir_prefix + std::string("batch_normalization_17_mean.bin");
+void* batch_normalization_17_mean = readTrainedWeights(batch_normalization_17_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_17_variance_path = dir_prefix + std::string("batch_normalization_17_variance.bin");
+void* batch_normalization_17_variance = readTrainedWeights(batch_normalization_17_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_9_w_path = dir_prefix + std::string("depthwise_conv2d_9_w.bin");
+void* depthwise_conv2d_9_w = readTrainedWeights(depthwise_conv2d_9_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_18_gamma_path = dir_prefix + std::string("batch_normalization_18_gamma.bin");
+void* batch_normalization_18_gamma = readTrainedWeights(batch_normalization_18_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_18_beta_path = dir_prefix + std::string("batch_normalization_18_beta.bin");
+void* batch_normalization_18_beta = readTrainedWeights(batch_normalization_18_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_18_mean_path = dir_prefix + std::string("batch_normalization_18_mean.bin");
+void* batch_normalization_18_mean = readTrainedWeights(batch_normalization_18_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_18_variance_path = dir_prefix + std::string("batch_normalization_18_variance.bin");
+void* batch_normalization_18_variance = readTrainedWeights(batch_normalization_18_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_10_w_path = dir_prefix + std::string("conv2d_10_w.bin");
+void* conv2d_10_w = readTrainedWeights(conv2d_10_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_19_gamma_path = dir_prefix + std::string("batch_normalization_19_gamma.bin");
+void* batch_normalization_19_gamma = readTrainedWeights(batch_normalization_19_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_19_beta_path = dir_prefix + std::string("batch_normalization_19_beta.bin");
+void* batch_normalization_19_beta = readTrainedWeights(batch_normalization_19_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_19_mean_path = dir_prefix + std::string("batch_normalization_19_mean.bin");
+void* batch_normalization_19_mean = readTrainedWeights(batch_normalization_19_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_19_variance_path = dir_prefix + std::string("batch_normalization_19_variance.bin");
+void* batch_normalization_19_variance = readTrainedWeights(batch_normalization_19_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_10_w_path = dir_prefix + std::string("depthwise_conv2d_10_w.bin");
+void* depthwise_conv2d_10_w = readTrainedWeights(depthwise_conv2d_10_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_20_gamma_path = dir_prefix + std::string("batch_normalization_20_gamma.bin");
+void* batch_normalization_20_gamma = readTrainedWeights(batch_normalization_20_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_20_beta_path = dir_prefix + std::string("batch_normalization_20_beta.bin");
+void* batch_normalization_20_beta = readTrainedWeights(batch_normalization_20_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_20_mean_path = dir_prefix + std::string("batch_normalization_20_mean.bin");
+void* batch_normalization_20_mean = readTrainedWeights(batch_normalization_20_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_20_variance_path = dir_prefix + std::string("batch_normalization_20_variance.bin");
+void* batch_normalization_20_variance = readTrainedWeights(batch_normalization_20_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_11_w_path = dir_prefix + std::string("conv2d_11_w.bin");
+void* conv2d_11_w = readTrainedWeights(conv2d_11_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_21_gamma_path = dir_prefix + std::string("batch_normalization_21_gamma.bin");
+void* batch_normalization_21_gamma = readTrainedWeights(batch_normalization_21_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_21_beta_path = dir_prefix + std::string("batch_normalization_21_beta.bin");
+void* batch_normalization_21_beta = readTrainedWeights(batch_normalization_21_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_21_mean_path = dir_prefix + std::string("batch_normalization_21_mean.bin");
+void* batch_normalization_21_mean = readTrainedWeights(batch_normalization_21_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_21_variance_path = dir_prefix + std::string("batch_normalization_21_variance.bin");
+void* batch_normalization_21_variance = readTrainedWeights(batch_normalization_21_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_11_w_path = dir_prefix + std::string("depthwise_conv2d_11_w.bin");
+void* depthwise_conv2d_11_w = readTrainedWeights(depthwise_conv2d_11_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_22_gamma_path = dir_prefix + std::string("batch_normalization_22_gamma.bin");
+void* batch_normalization_22_gamma = readTrainedWeights(batch_normalization_22_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_22_beta_path = dir_prefix + std::string("batch_normalization_22_beta.bin");
+void* batch_normalization_22_beta = readTrainedWeights(batch_normalization_22_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_22_mean_path = dir_prefix + std::string("batch_normalization_22_mean.bin");
+void* batch_normalization_22_mean = readTrainedWeights(batch_normalization_22_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_22_variance_path = dir_prefix + std::string("batch_normalization_22_variance.bin");
+void* batch_normalization_22_variance = readTrainedWeights(batch_normalization_22_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_12_w_path = dir_prefix + std::string("conv2d_12_w.bin");
+void* conv2d_12_w = readTrainedWeights(conv2d_12_w_path.c_str(), 0,512,512,1,1);
+std::string batch_normalization_23_gamma_path = dir_prefix + std::string("batch_normalization_23_gamma.bin");
+void* batch_normalization_23_gamma = readTrainedWeights(batch_normalization_23_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_23_beta_path = dir_prefix + std::string("batch_normalization_23_beta.bin");
+void* batch_normalization_23_beta = readTrainedWeights(batch_normalization_23_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_23_mean_path = dir_prefix + std::string("batch_normalization_23_mean.bin");
+void* batch_normalization_23_mean = readTrainedWeights(batch_normalization_23_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_23_variance_path = dir_prefix + std::string("batch_normalization_23_variance.bin");
+void* batch_normalization_23_variance = readTrainedWeights(batch_normalization_23_variance_path.c_str(), 0,1,512,1,1);
+std::string depthwise_conv2d_12_w_path = dir_prefix + std::string("depthwise_conv2d_12_w.bin");
+void* depthwise_conv2d_12_w = readTrainedWeights(depthwise_conv2d_12_w_path.c_str(), 0,512,1,3,3);
+std::string batch_normalization_24_gamma_path = dir_prefix + std::string("batch_normalization_24_gamma.bin");
+void* batch_normalization_24_gamma = readTrainedWeights(batch_normalization_24_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_24_beta_path = dir_prefix + std::string("batch_normalization_24_beta.bin");
+void* batch_normalization_24_beta = readTrainedWeights(batch_normalization_24_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_24_mean_path = dir_prefix + std::string("batch_normalization_24_mean.bin");
+void* batch_normalization_24_mean = readTrainedWeights(batch_normalization_24_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_24_variance_path = dir_prefix + std::string("batch_normalization_24_variance.bin");
+void* batch_normalization_24_variance = readTrainedWeights(batch_normalization_24_variance_path.c_str(), 0,1,512,1,1);
+std::string conv2d_13_w_path = dir_prefix + std::string("conv2d_13_w.bin");
+void* conv2d_13_w = readTrainedWeights(conv2d_13_w_path.c_str(), 0,1024,512,1,1);
+std::string batch_normalization_25_gamma_path = dir_prefix + std::string("batch_normalization_25_gamma.bin");
+void* batch_normalization_25_gamma = readTrainedWeights(batch_normalization_25_gamma_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_25_beta_path = dir_prefix + std::string("batch_normalization_25_beta.bin");
+void* batch_normalization_25_beta = readTrainedWeights(batch_normalization_25_beta_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_25_mean_path = dir_prefix + std::string("batch_normalization_25_mean.bin");
+void* batch_normalization_25_mean = readTrainedWeights(batch_normalization_25_mean_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_25_variance_path = dir_prefix + std::string("batch_normalization_25_variance.bin");
+void* batch_normalization_25_variance = readTrainedWeights(batch_normalization_25_variance_path.c_str(), 0,1,1024,1,1);
+std::string depthwise_conv2d_13_w_path = dir_prefix + std::string("depthwise_conv2d_13_w.bin");
+void* depthwise_conv2d_13_w = readTrainedWeights(depthwise_conv2d_13_w_path.c_str(), 0,1024,1,3,3);
+std::string batch_normalization_26_gamma_path = dir_prefix + std::string("batch_normalization_26_gamma.bin");
+void* batch_normalization_26_gamma = readTrainedWeights(batch_normalization_26_gamma_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_26_beta_path = dir_prefix + std::string("batch_normalization_26_beta.bin");
+void* batch_normalization_26_beta = readTrainedWeights(batch_normalization_26_beta_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_26_mean_path = dir_prefix + std::string("batch_normalization_26_mean.bin");
+void* batch_normalization_26_mean = readTrainedWeights(batch_normalization_26_mean_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_26_variance_path = dir_prefix + std::string("batch_normalization_26_variance.bin");
+void* batch_normalization_26_variance = readTrainedWeights(batch_normalization_26_variance_path.c_str(), 0,1,1024,1,1);
+std::string conv2d_14_w_path = dir_prefix + std::string("conv2d_14_w.bin");
+void* conv2d_14_w = readTrainedWeights(conv2d_14_w_path.c_str(), 0,1024,1024,1,1);
+std::string batch_normalization_27_gamma_path = dir_prefix + std::string("batch_normalization_27_gamma.bin");
+void* batch_normalization_27_gamma = readTrainedWeights(batch_normalization_27_gamma_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_27_beta_path = dir_prefix + std::string("batch_normalization_27_beta.bin");
+void* batch_normalization_27_beta = readTrainedWeights(batch_normalization_27_beta_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_27_mean_path = dir_prefix + std::string("batch_normalization_27_mean.bin");
+void* batch_normalization_27_mean = readTrainedWeights(batch_normalization_27_mean_path.c_str(), 0,1,1024,1,1);
+std::string batch_normalization_27_variance_path = dir_prefix + std::string("batch_normalization_27_variance.bin");
+void* batch_normalization_27_variance = readTrainedWeights(batch_normalization_27_variance_path.c_str(), 0,1,1024,1,1);
+std::string dense_1_w_path = dir_prefix + std::string("dense_1_w.bin");
+void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,1024,10);
+std::string dense_1_b_path = dir_prefix + std::string("dense_1_b.bin");
+void* dense_1_b = readTrainedWeights(dense_1_b_path.c_str(), 0,1,10,1,1);
+
+
+
+startMemTracking();
+
+int test_input_size = 10000;
+int batch_size = 10000;
+int batch_count = test_input_size / batch_size;
+float final_accuracy = 0.0;
+
+for(int i = 0; i < batch_count; i++){
+
+int start = i * batch_size;
+int end = (i + 1) * batch_size;
+
+void* input = readInputBatch(input_path.c_str(),0,start,end,3,32,32);
+
+void* var_0 = tensorConvolution(input, conv2d_1_w, 1, 1, 1, 1, 1, 1);
+void* var_1 = tensorBatchNorm(var_0, batch_normalization_1_gamma, batch_normalization_1_beta, batch_normalization_1_mean, batch_normalization_1_variance, 0.001);
+void* var_2 = tensorRelu(var_1);
+void* var_4 = tensorConvolution(var_2, depthwise_conv2d_1_w, 1, 1, 1, 1, 1, 32);
+void* var_5 = tensorBatchNorm(var_4, batch_normalization_2_gamma, batch_normalization_2_beta, batch_normalization_2_mean, batch_normalization_2_variance, 0.001);
+void* var_6 = tensorRelu(var_5);
+void* var_7 = tensorConvolution(var_6, conv2d_2_w, 0, 0, 1, 1, 1, 1);
+void* var_8 = tensorBatchNorm(var_7, batch_normalization_3_gamma, batch_normalization_3_beta, batch_normalization_3_mean, batch_normalization_3_variance, 0.001);
+void* var_9 = tensorRelu(var_8);
+void* var_11 = tensorConvolution(var_9, depthwise_conv2d_2_w, 1, 1, 2, 2, 1, 64);
+void* var_12 = tensorBatchNorm(var_11, batch_normalization_4_gamma, batch_normalization_4_beta, batch_normalization_4_mean, batch_normalization_4_variance, 0.001);
+void* var_13 = tensorRelu(var_12);
+void* var_14 = tensorConvolution(var_13, conv2d_3_w, 0, 0, 1, 1, 1, 1);
+void* var_15 = tensorBatchNorm(var_14, batch_normalization_5_gamma, batch_normalization_5_beta, batch_normalization_5_mean, batch_normalization_5_variance, 0.001);
+void* var_16 = tensorRelu(var_15);
+void* var_18 = tensorConvolution(var_16, depthwise_conv2d_3_w, 1, 1, 1, 1, 1, 128);
+void* var_19 = tensorBatchNorm(var_18, batch_normalization_6_gamma, batch_normalization_6_beta, batch_normalization_6_mean, batch_normalization_6_variance, 0.001);
+void* var_20 = tensorRelu(var_19);
+void* var_21 = tensorConvolution(var_20, conv2d_4_w, 0, 0, 1, 1, 1, 1);
+void* var_22 = tensorBatchNorm(var_21, batch_normalization_7_gamma, batch_normalization_7_beta, batch_normalization_7_mean, batch_normalization_7_variance, 0.001);
+void* var_23 = tensorRelu(var_22);
+void* var_26 = tensorConvolution(var_23, depthwise_conv2d_4_w, 1, 1, 2, 2, 1, 128);
+void* var_27 = tensorBatchNorm(var_26, batch_normalization_8_gamma, batch_normalization_8_beta, batch_normalization_8_mean, batch_normalization_8_variance, 0.001);
+void* var_28 = tensorRelu(var_27);
+void* var_29 = tensorConvolution(var_28, conv2d_5_w, 0, 0, 1, 1, 1, 1);
+void* var_30 = tensorBatchNorm(var_29, batch_normalization_9_gamma, batch_normalization_9_beta, batch_normalization_9_mean, batch_normalization_9_variance, 0.001);
+void* var_31 = tensorRelu(var_30);
+void* var_33 = tensorConvolution(var_31, depthwise_conv2d_5_w, 1, 1, 1, 1, 1, 256);
+void* var_34 = tensorBatchNorm(var_33, batch_normalization_10_gamma, batch_normalization_10_beta, batch_normalization_10_mean, batch_normalization_10_variance, 0.001);
+void* var_35 = tensorRelu(var_34);
+void* var_36 = tensorConvolution(var_35, conv2d_6_w, 0, 0, 1, 1, 1, 1);
+void* var_37 = tensorBatchNorm(var_36, batch_normalization_11_gamma, batch_normalization_11_beta, batch_normalization_11_mean, batch_normalization_11_variance, 0.001);
+void* var_38 = tensorRelu(var_37);
+void* var_41 = tensorConvolution(var_38, depthwise_conv2d_6_w, 1, 1, 2, 2, 1, 256);
+void* var_42 = tensorBatchNorm(var_41, batch_normalization_12_gamma, batch_normalization_12_beta, batch_normalization_12_mean, batch_normalization_12_variance, 0.001);
+void* var_43 = tensorRelu(var_42);
+void* var_44 = tensorConvolution(var_43, conv2d_7_w, 0, 0, 1, 1, 1, 1);
+void* var_45 = tensorBatchNorm(var_44, batch_normalization_13_gamma, batch_normalization_13_beta, batch_normalization_13_mean, batch_normalization_13_variance, 0.001);
+void* var_46 = tensorRelu(var_45);
+void* var_48 = tensorConvolution(var_46, depthwise_conv2d_7_w, 1, 1, 1, 1, 1, 512);
+void* var_49 = tensorBatchNorm(var_48, batch_normalization_14_gamma, batch_normalization_14_beta, batch_normalization_14_mean, batch_normalization_14_variance, 0.001);
+void* var_50 = tensorRelu(var_49);
+void* var_51 = tensorConvolution(var_50, conv2d_8_w, 0, 0, 1, 1, 1, 1);
+void* var_52 = tensorBatchNorm(var_51, batch_normalization_15_gamma, batch_normalization_15_beta, batch_normalization_15_mean, batch_normalization_15_variance, 0.001);
+void* var_53 = tensorRelu(var_52);
+void* var_55 = tensorConvolution(var_53, depthwise_conv2d_8_w, 1, 1, 1, 1, 1, 512);
+void* var_56 = tensorBatchNorm(var_55, batch_normalization_16_gamma, batch_normalization_16_beta, batch_normalization_16_mean, batch_normalization_16_variance, 0.001);
+void* var_57 = tensorRelu(var_56);
+void* var_58 = tensorConvolution(var_57, conv2d_9_w, 0, 0, 1, 1, 1, 1);
+void* var_59 = tensorBatchNorm(var_58, batch_normalization_17_gamma, batch_normalization_17_beta, batch_normalization_17_mean, batch_normalization_17_variance, 0.001);
+void* var_60 = tensorRelu(var_59);
+void* var_63 = tensorConvolution(var_60, depthwise_conv2d_9_w, 1, 1, 1, 1, 1, 512);
+void* var_64 = tensorBatchNorm(var_63, batch_normalization_18_gamma, batch_normalization_18_beta, batch_normalization_18_mean, batch_normalization_18_variance, 0.001);
+void* var_65 = tensorRelu(var_64);
+void* var_66 = tensorConvolution(var_65, conv2d_10_w, 0, 0, 1, 1, 1, 1);
+void* var_67 = tensorBatchNorm(var_66, batch_normalization_19_gamma, batch_normalization_19_beta, batch_normalization_19_mean, batch_normalization_19_variance, 0.001);
+void* var_68 = tensorRelu(var_67);
+void* var_70 = tensorConvolution(var_68, depthwise_conv2d_10_w, 1, 1, 1, 1, 1, 512);
+void* var_71 = tensorBatchNorm(var_70, batch_normalization_20_gamma, batch_normalization_20_beta, batch_normalization_20_mean, batch_normalization_20_variance, 0.001);
+void* var_72 = tensorRelu(var_71);
+void* var_73 = tensorConvolution(var_72, conv2d_11_w, 0, 0, 1, 1, 1, 1);
+void* var_74 = tensorBatchNorm(var_73, batch_normalization_21_gamma, batch_normalization_21_beta, batch_normalization_21_mean, batch_normalization_21_variance, 0.001);
+void* var_75 = tensorRelu(var_74);
+void* var_77 = tensorConvolution(var_75, depthwise_conv2d_11_w, 1, 1, 1, 1, 1, 512);
+void* var_78 = tensorBatchNorm(var_77, batch_normalization_22_gamma, batch_normalization_22_beta, batch_normalization_22_mean, batch_normalization_22_variance, 0.001);
+void* var_79 = tensorRelu(var_78);
+void* var_80 = tensorConvolution(var_79, conv2d_12_w, 0, 0, 1, 1, 1, 1);
+void* var_81 = tensorBatchNorm(var_80, batch_normalization_23_gamma, batch_normalization_23_beta, batch_normalization_23_mean, batch_normalization_23_variance, 0.001);
+void* var_82 = tensorRelu(var_81);
+void* var_85 = tensorConvolution(var_82, depthwise_conv2d_12_w, 1, 1, 2, 2, 1, 512);
+void* var_86 = tensorBatchNorm(var_85, batch_normalization_24_gamma, batch_normalization_24_beta, batch_normalization_24_mean, batch_normalization_24_variance, 0.001);
+void* var_87 = tensorRelu(var_86);
+void* var_88 = tensorConvolution(var_87, conv2d_13_w, 0, 0, 1, 1, 1, 1);
+void* var_89 = tensorBatchNorm(var_88, batch_normalization_25_gamma, batch_normalization_25_beta, batch_normalization_25_mean, batch_normalization_25_variance, 0.001);
+void* var_90 = tensorRelu(var_89);
+void* var_92 = tensorConvolution(var_90, depthwise_conv2d_13_w, 1, 1, 1, 1, 1, 1024);
+void* var_93 = tensorBatchNorm(var_92, batch_normalization_26_gamma, batch_normalization_26_beta, batch_normalization_26_mean, batch_normalization_26_variance, 0.001);
+void* var_94 = tensorRelu(var_93);
+void* var_95 = tensorConvolution(var_94, conv2d_14_w, 0, 0, 1, 1, 1, 1);
+void* var_96 = tensorBatchNorm(var_95, batch_normalization_27_gamma, batch_normalization_27_beta, batch_normalization_27_mean, batch_normalization_27_variance, 0.001);
+void* var_97 = tensorRelu(var_96);
+void* var_99 = tensorPooling(var_97,1,2,2,0,0,2,2);
+void* var_101 = tensorGemmGPU(var_99, dense_1_w);
+void* var_102 = tensorAdd(var_101, dense_1_b);
+void* var_103 = tensorSoftmax(var_102);
+
+uint8_t* labels = readLabelsBatch(labels_path.c_str(),start,end);
+
+float accuracy = computeAccuracy2(labels, batch_size, var_103);
+final_accuracy += accuracy;
+freeBatchMemory();
+
+}
+
+final_accuracy = final_accuracy / batch_count;
+dumpFinalAccuracy(final_accuracy);
+
+
+llvm_hpvm_cleanupTensorRt();
+
+return 0;
+
+}
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/approxhpvm_src.cc b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/approxhpvm_src.cc
index eba282f00658fab8876f8cb1045d89decb4934ab..dc0c873c63333299981591cb5654cb38be9d4092 100644
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/approxhpvm_src.cc
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/approxhpvm_src.cc
@@ -133,7 +133,7 @@ void var_15_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
__visc__hint(visc::CUDNN_TARGET);
__visc__attributes(2, t1, t2, 0);
- void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 2, 2, 1, 64);
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 128);
__visc__return(2, r, (size_t) 0);
}
@@ -273,7 +273,55 @@ void var_32_node(void* t1, size_t bytes_t1) {
__visc__return(2, r, (size_t) 0);
}
-void var_33_node(void* t1, size_t bytes_t1) {
+void var_33_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 2, 2, 1, 256);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_34_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_35_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_36_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(2, t1, t2, 0);
+
+ void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_37_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(5, t1, t2, t3, t4, t5, 0);
+
+ void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_38_node(void* t1, size_t bytes_t1) {
+ __visc__hint(visc::CUDNN_TARGET);
+ __visc__attributes(1, t1, 0);
+
+ void* r = __visc__tensor_relu(t1);
+ __visc__return(2, r, (size_t) 0);
+}
+
+void var_39_node(void* t1, size_t bytes_t1) {
__visc__hint(visc::CUDNN_TARGET);
__visc__attributes(1, t1, 0);
@@ -281,7 +329,7 @@ void var_33_node(void* t1, size_t bytes_t1) {
__visc__return(2, r, (size_t) 0);
}
-void var_34_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+void var_40_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
__visc__hint(visc::CUDNN_TARGET);
__visc__attributes(2, t1, t2, 0);
@@ -289,7 +337,7 @@ void var_34_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
__visc__return(2, r, (size_t) 0);
}
-void var_35_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
+void var_41_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
__visc__hint(visc::CUDNN_TARGET);
__visc__attributes(2, t1, t2, 0);
@@ -297,7 +345,7 @@ void var_35_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
__visc__return(2, r, (size_t) 0);
}
-void var_36_node(void* t1, size_t bytes_t1) {
+void var_42_node(void* t1, size_t bytes_t1) {
__visc__hint(visc::CUDNN_TARGET);
__visc__attributes(1, t1, 0);
@@ -361,12 +409,22 @@ void root(void* input, size_t input_bytes,
void* batch_normalization_11_beta, size_t batch_normalization_11_beta_bytes,
void* batch_normalization_11_mean, size_t batch_normalization_11_mean_bytes,
void* batch_normalization_11_variance, size_t batch_normalization_11_variance_bytes,
+ void* depthwise_conv2d_6_w, size_t depthwise_conv2d_6_w_bytes,
+ void* batch_normalization_12_gamma, size_t batch_normalization_12_gamma_bytes,
+ void* batch_normalization_12_beta, size_t batch_normalization_12_beta_bytes,
+ void* batch_normalization_12_mean, size_t batch_normalization_12_mean_bytes,
+ void* batch_normalization_12_variance, size_t batch_normalization_12_variance_bytes,
+ void* conv2d_7_w, size_t conv2d_7_w_bytes,
+ void* batch_normalization_13_gamma, size_t batch_normalization_13_gamma_bytes,
+ void* batch_normalization_13_beta, size_t batch_normalization_13_beta_bytes,
+ void* batch_normalization_13_mean, size_t batch_normalization_13_mean_bytes,
+ void* batch_normalization_13_variance, size_t batch_normalization_13_variance_bytes,
void* dense_1_w, size_t dense_1_w_bytes,
void* dense_1_b, size_t dense_1_b_bytes){
__visc__hint(visc::CPU_TARGET);
- __visc__attributes(58, input, conv2d_1_w, batch_normalization_1_gamma, batch_normalization_1_beta, batch_normalization_1_mean, batch_normalization_1_variance, depthwise_conv2d_1_w, batch_normalization_2_gamma, batch_normalization_2_beta, batch_normalization_2_mean, batch_normalization_2_variance, conv2d_2_w, batch_normalization_3_gamma, batch_normalization_3_beta, batch_normalization_3_mean, batch_normalization_3_variance, depthwise_conv2d_2_w, batch_normalization_4_gamma, batch_normalization_4_beta, batch_normalization_4_mean, batch_normalization_4_variance, conv2d_3_w, batch_normalization_5_gamma, batch_normalization_5_beta, batch_normalization_5_mean, batch_normalization_5_variance, depthwise_conv2d_3_w, batch_normalization_6_gamma, batch_normalization_6_beta, batch_normalization_6_mean, batch_normalization_6_variance, conv2d_4_w, batch_normalization_7_gamma, batch_normalization_7_beta, batch_normalization_7_mean, batch_normalization_7_variance, depthwise_conv2d_4_w, batch_normalization_8_gamma, batch_normalization_8_beta, batch_normalization_8_mean, batch_normalization_8_variance, conv2d_5_w, batch_normalization_9_gamma, batch_normalization_9_beta, batch_normalization_9_mean, batch_normalization_9_variance, depthwise_conv2d_5_w, batch_normalization_10_gamma, batch_normalization_10_beta, batch_normalization_10_mean, batch_normalization_10_variance, conv2d_6_w, batch_normalization_11_gamma, batch_normalization_11_beta, batch_normalization_11_mean, batch_normalization_11_variance, dense_1_w, dense_1_b, 0);
+ __visc__attributes(68, input, conv2d_1_w, batch_normalization_1_gamma, batch_normalization_1_beta, batch_normalization_1_mean, batch_normalization_1_variance, depthwise_conv2d_1_w, batch_normalization_2_gamma, batch_normalization_2_beta, batch_normalization_2_mean, batch_normalization_2_variance, conv2d_2_w, batch_normalization_3_gamma, batch_normalization_3_beta, batch_normalization_3_mean, batch_normalization_3_variance, depthwise_conv2d_2_w, batch_normalization_4_gamma, batch_normalization_4_beta, batch_normalization_4_mean, batch_normalization_4_variance, conv2d_3_w, batch_normalization_5_gamma, batch_normalization_5_beta, batch_normalization_5_mean, batch_normalization_5_variance, depthwise_conv2d_3_w, batch_normalization_6_gamma, batch_normalization_6_beta, batch_normalization_6_mean, batch_normalization_6_variance, conv2d_4_w, batch_normalization_7_gamma, batch_normalization_7_beta, batch_normalization_7_mean, batch_normalization_7_variance, depthwise_conv2d_4_w, batch_normalization_8_gamma, batch_normalization_8_beta, batch_normalization_8_mean, batch_normalization_8_variance, conv2d_5_w, batch_normalization_9_gamma, batch_normalization_9_beta, batch_normalization_9_mean, batch_normalization_9_variance, depthwise_conv2d_5_w, batch_normalization_10_gamma, batch_normalization_10_beta, batch_normalization_10_mean, batch_normalization_10_variance, conv2d_6_w, batch_normalization_11_gamma, batch_normalization_11_beta, batch_normalization_11_mean, batch_normalization_11_variance, depthwise_conv2d_6_w, batch_normalization_12_gamma, batch_normalization_12_beta, batch_normalization_12_mean, batch_normalization_12_variance, conv2d_7_w, batch_normalization_13_gamma, batch_normalization_13_beta, batch_normalization_13_mean, batch_normalization_13_variance, dense_1_w, dense_1_b, 0);
void* var_0 = __visc__createNodeND(0, var_0_node);
@@ -648,28 +706,78 @@ void root(void* input, size_t input_bytes,
__visc__edge(var_32, var_33, 1, 0, 0, 0);
__visc__edge(var_32, var_33, 1, 1, 1, 0);
+ __visc__bindIn(var_33, 112, 2, 0);
+ __visc__bindIn(var_33, 113, 3, 0);
void* var_34 = __visc__createNodeND(0, var_34_node);
__visc__edge(var_33, var_34, 1, 0, 0, 0);
__visc__edge(var_33, var_34, 1, 1, 1, 0);
- __visc__bindIn(var_34, 112, 2, 0);
- __visc__bindIn(var_34, 113, 3, 0);
+ __visc__bindIn(var_34, 114, 2, 0);
+ __visc__bindIn(var_34, 115, 3, 0);
+ __visc__bindIn(var_34, 116, 4, 0);
+ __visc__bindIn(var_34, 117, 5, 0);
+ __visc__bindIn(var_34, 118, 6, 0);
+ __visc__bindIn(var_34, 119, 7, 0);
+ __visc__bindIn(var_34, 120, 8, 0);
+ __visc__bindIn(var_34, 121, 9, 0);
void* var_35 = __visc__createNodeND(0, var_35_node);
__visc__edge(var_34, var_35, 1, 0, 0, 0);
__visc__edge(var_34, var_35, 1, 1, 1, 0);
- __visc__bindIn(var_35, 114, 2, 0);
- __visc__bindIn(var_35, 115, 3, 0);
void* var_36 = __visc__createNodeND(0, var_36_node);
__visc__edge(var_35, var_36, 1, 0, 0, 0);
__visc__edge(var_35, var_36, 1, 1, 1, 0);
+ __visc__bindIn(var_36, 122, 2, 0);
+ __visc__bindIn(var_36, 123, 3, 0);
+
+ void* var_37 = __visc__createNodeND(0, var_37_node);
+
+ __visc__edge(var_36, var_37, 1, 0, 0, 0);
+ __visc__edge(var_36, var_37, 1, 1, 1, 0);
+ __visc__bindIn(var_37, 124, 2, 0);
+ __visc__bindIn(var_37, 125, 3, 0);
+ __visc__bindIn(var_37, 126, 4, 0);
+ __visc__bindIn(var_37, 127, 5, 0);
+ __visc__bindIn(var_37, 128, 6, 0);
+ __visc__bindIn(var_37, 129, 7, 0);
+ __visc__bindIn(var_37, 130, 8, 0);
+ __visc__bindIn(var_37, 131, 9, 0);
+
+ void* var_38 = __visc__createNodeND(0, var_38_node);
+
+ __visc__edge(var_37, var_38, 1, 0, 0, 0);
+ __visc__edge(var_37, var_38, 1, 1, 1, 0);
+
+ void* var_39 = __visc__createNodeND(0, var_39_node);
+
+ __visc__edge(var_38, var_39, 1, 0, 0, 0);
+ __visc__edge(var_38, var_39, 1, 1, 1, 0);
+
+ void* var_40 = __visc__createNodeND(0, var_40_node);
+
+ __visc__edge(var_39, var_40, 1, 0, 0, 0);
+ __visc__edge(var_39, var_40, 1, 1, 1, 0);
+ __visc__bindIn(var_40, 132, 2, 0);
+ __visc__bindIn(var_40, 133, 3, 0);
+
+ void* var_41 = __visc__createNodeND(0, var_41_node);
+
+ __visc__edge(var_40, var_41, 1, 0, 0, 0);
+ __visc__edge(var_40, var_41, 1, 1, 1, 0);
+ __visc__bindIn(var_41, 134, 2, 0);
+ __visc__bindIn(var_41, 135, 3, 0);
+
+ void* var_42 = __visc__createNodeND(0, var_42_node);
+
+ __visc__edge(var_41, var_42, 1, 0, 0, 0);
+ __visc__edge(var_41, var_42, 1, 1, 1, 0);
- __visc__bindOut(var_36, 0, 0, 0);
- __visc__bindOut(var_36, 1, 1, 0);
+ __visc__bindOut(var_42, 0, 0, 0);
+ __visc__bindOut(var_42, 1, 1, 0);
}
@@ -791,6 +899,26 @@ typedef struct __attribute__((__packed__)) {
size_t batch_normalization_11_mean_bytes;
void* batch_normalization_11_variance;
size_t batch_normalization_11_variance_bytes;
+ void* depthwise_conv2d_6_w;
+ size_t depthwise_conv2d_6_w_bytes;
+ void* batch_normalization_12_gamma;
+ size_t batch_normalization_12_gamma_bytes;
+ void* batch_normalization_12_beta;
+ size_t batch_normalization_12_beta_bytes;
+ void* batch_normalization_12_mean;
+ size_t batch_normalization_12_mean_bytes;
+ void* batch_normalization_12_variance;
+ size_t batch_normalization_12_variance_bytes;
+ void* conv2d_7_w;
+ size_t conv2d_7_w_bytes;
+ void* batch_normalization_13_gamma;
+ size_t batch_normalization_13_gamma_bytes;
+ void* batch_normalization_13_beta;
+ size_t batch_normalization_13_beta_bytes;
+ void* batch_normalization_13_mean;
+ size_t batch_normalization_13_mean_bytes;
+ void* batch_normalization_13_variance;
+ size_t batch_normalization_13_variance_bytes;
void* dense_1_w;
size_t dense_1_w_bytes;
void* dense_1_b;
@@ -802,7 +930,7 @@ RootIn;
int main(){
-std::string dir_prefix = std::string("data/mobilenet_shallow/");
+std::string dir_prefix = std::string("data/mobilenet_shallow_nathan/");
std::string input_path = dir_prefix + std::string("input.bin");
std::string labels_path = dir_prefix + std::string("labels.bin");
std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
@@ -846,27 +974,27 @@ void* batch_normalization_4_mean = readTrainedWeights(batch_normalization_4_mea
std::string batch_normalization_4_variance_path = dir_prefix + std::string("batch_normalization_4_variance.bin");
void* batch_normalization_4_variance = readTrainedWeights(batch_normalization_4_variance_path.c_str(), 0,1,64,1,1);
std::string conv2d_3_w_path = dir_prefix + std::string("conv2d_3_w.bin");
-void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,64,64,1,1);
+void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,128,64,1,1);
std::string batch_normalization_5_gamma_path = dir_prefix + std::string("batch_normalization_5_gamma.bin");
-void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_5_beta_path = dir_prefix + std::string("batch_normalization_5_beta.bin");
-void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_5_mean_path = dir_prefix + std::string("batch_normalization_5_mean.bin");
-void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_5_variance_path = dir_prefix + std::string("batch_normalization_5_variance.bin");
-void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,128,1,1);
std::string depthwise_conv2d_3_w_path = dir_prefix + std::string("depthwise_conv2d_3_w.bin");
-void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,64,1,3,3);
+void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,128,1,3,3);
std::string batch_normalization_6_gamma_path = dir_prefix + std::string("batch_normalization_6_gamma.bin");
-void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_6_beta_path = dir_prefix + std::string("batch_normalization_6_beta.bin");
-void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_6_mean_path = dir_prefix + std::string("batch_normalization_6_mean.bin");
-void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_6_variance_path = dir_prefix + std::string("batch_normalization_6_variance.bin");
-void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,128,1,1);
std::string conv2d_4_w_path = dir_prefix + std::string("conv2d_4_w.bin");
-void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,64,1,1);
+void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,128,1,1);
std::string batch_normalization_7_gamma_path = dir_prefix + std::string("batch_normalization_7_gamma.bin");
void* batch_normalization_7_gamma = readTrainedWeights(batch_normalization_7_gamma_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_7_beta_path = dir_prefix + std::string("batch_normalization_7_beta.bin");
@@ -915,8 +1043,28 @@ std::string batch_normalization_11_mean_path = dir_prefix + std::string("batch_
void* batch_normalization_11_mean = readTrainedWeights(batch_normalization_11_mean_path.c_str(), 0,1,256,1,1);
std::string batch_normalization_11_variance_path = dir_prefix + std::string("batch_normalization_11_variance.bin");
void* batch_normalization_11_variance = readTrainedWeights(batch_normalization_11_variance_path.c_str(), 0,1,256,1,1);
+std::string depthwise_conv2d_6_w_path = dir_prefix + std::string("depthwise_conv2d_6_w.bin");
+void* depthwise_conv2d_6_w = readTrainedWeights(depthwise_conv2d_6_w_path.c_str(), 0,256,1,3,3);
+std::string batch_normalization_12_gamma_path = dir_prefix + std::string("batch_normalization_12_gamma.bin");
+void* batch_normalization_12_gamma = readTrainedWeights(batch_normalization_12_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_beta_path = dir_prefix + std::string("batch_normalization_12_beta.bin");
+void* batch_normalization_12_beta = readTrainedWeights(batch_normalization_12_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_mean_path = dir_prefix + std::string("batch_normalization_12_mean.bin");
+void* batch_normalization_12_mean = readTrainedWeights(batch_normalization_12_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_variance_path = dir_prefix + std::string("batch_normalization_12_variance.bin");
+void* batch_normalization_12_variance = readTrainedWeights(batch_normalization_12_variance_path.c_str(), 0,1,256,1,1);
+std::string conv2d_7_w_path = dir_prefix + std::string("conv2d_7_w.bin");
+void* conv2d_7_w = readTrainedWeights(conv2d_7_w_path.c_str(), 0,512,256,1,1);
+std::string batch_normalization_13_gamma_path = dir_prefix + std::string("batch_normalization_13_gamma.bin");
+void* batch_normalization_13_gamma = readTrainedWeights(batch_normalization_13_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_beta_path = dir_prefix + std::string("batch_normalization_13_beta.bin");
+void* batch_normalization_13_beta = readTrainedWeights(batch_normalization_13_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_mean_path = dir_prefix + std::string("batch_normalization_13_mean.bin");
+void* batch_normalization_13_mean = readTrainedWeights(batch_normalization_13_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_variance_path = dir_prefix + std::string("batch_normalization_13_variance.bin");
+void* batch_normalization_13_variance = readTrainedWeights(batch_normalization_13_variance_path.c_str(), 0,1,512,1,1);
std::string dense_1_w_path = dir_prefix + std::string("dense_1_w.bin");
-void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,1024,10);
+void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,2048,10);
std::string dense_1_b_path = dir_prefix + std::string("dense_1_b.bin");
void* dense_1_b = readTrainedWeights(dense_1_b_path.c_str(), 0,1,10,1,1);
void* input = readTrainedWeights(input_path.c_str(), 0,10000,3,32,32);
@@ -1037,6 +1185,26 @@ args->batch_normalization_11_mean = batch_normalization_11_mean;
args->batch_normalization_11_mean_bytes = 0;
args->batch_normalization_11_variance = batch_normalization_11_variance;
args->batch_normalization_11_variance_bytes = 0;
+args->depthwise_conv2d_6_w = depthwise_conv2d_6_w;
+args->depthwise_conv2d_6_w_bytes = 0;
+args->batch_normalization_12_gamma = batch_normalization_12_gamma;
+args->batch_normalization_12_gamma_bytes = 0;
+args->batch_normalization_12_beta = batch_normalization_12_beta;
+args->batch_normalization_12_beta_bytes = 0;
+args->batch_normalization_12_mean = batch_normalization_12_mean;
+args->batch_normalization_12_mean_bytes = 0;
+args->batch_normalization_12_variance = batch_normalization_12_variance;
+args->batch_normalization_12_variance_bytes = 0;
+args->conv2d_7_w = conv2d_7_w;
+args->conv2d_7_w_bytes = 0;
+args->batch_normalization_13_gamma = batch_normalization_13_gamma;
+args->batch_normalization_13_gamma_bytes = 0;
+args->batch_normalization_13_beta = batch_normalization_13_beta;
+args->batch_normalization_13_beta_bytes = 0;
+args->batch_normalization_13_mean = batch_normalization_13_mean;
+args->batch_normalization_13_mean_bytes = 0;
+args->batch_normalization_13_variance = batch_normalization_13_variance;
+args->batch_normalization_13_variance_bytes = 0;
args->dense_1_w = dense_1_w;
args->dense_1_w_bytes = 0;
args->dense_1_b = dense_1_b;
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_10_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_10_beta.bin
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_10_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_10_mean.bin
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_11_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_11_beta.bin
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_11_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_11_mean.bin
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_11_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_11_variance.bin
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_12_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_12_beta.bin
similarity index 100%
rename from llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_12_beta.bin
rename to llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_12_beta.bin
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_12_gamma.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_12_gamma.bin
similarity index 100%
rename from llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_12_gamma.bin
rename to llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_12_gamma.bin
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_12_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_12_mean.bin
similarity index 100%
rename from llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_12_mean.bin
rename to llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_12_mean.bin
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_12_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_12_variance.bin
similarity index 100%
rename from llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_12_variance.bin
rename to llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_12_variance.bin
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_13_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_13_beta.bin
similarity index 100%
rename from llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_13_beta.bin
rename to llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_13_beta.bin
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_13_gamma.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_13_gamma.bin
similarity index 100%
rename from llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_13_gamma.bin
rename to llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_13_gamma.bin
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_13_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_13_mean.bin
similarity index 100%
rename from llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_13_mean.bin
rename to llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_13_mean.bin
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_13_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_13_variance.bin
similarity index 100%
rename from llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_13_variance.bin
rename to llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_13_variance.bin
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_beta.bin
index 061eb6cd640bc9c88fe979dc8e1af46fd129608d..05d61c8e00f196b83dde7de794cc9feff2929582 100644
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_gamma.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_gamma.bin
index 0044d748d3283e60ffd483d15b503095dc985e19..1aaaeaa110d8b9eb8108a1546302f8d5c1c12c35 100644
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_gamma.bin
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_gamma.bin
@@ -1,2 +1,2 @@
-ãÀT?ôU?±[?Ÿ/?¢½~?M9‚?€j*?~•ƒ?½V?øJ+?y‹‚?„‹€?«x{?/
-M?¿I?&õl?öT?Þðo?_þs?ööT?^^?èâ?·š~?̃e?_©q?Ä“ ?…w?±iq?c*?Ê)ò>Î{f?…?
\ No newline at end of file
+³]ƒ?Ç/?®0€?]…o?ƒ?ߌ?Vň?`Z?Gk„?±*`?žÐƒ?pÈ~?
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+u?Òü?Qƒ?|?š O??ä?K{?^5Œ?ÃÜ‚?£ ?…ØA?žTr?1 y?÷€?!56?&ñƒ?HWv?§^‚?
\ No newline at end of file
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_mean.bin
index c1775a36d6c27487934a0cf2014b8a76d06fd37d..ffcd3adfeac9b601872fa59caa42601fdc10494c 100644
Binary files a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_mean.bin and b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_mean.bin differ
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_variance.bin
index a54db7cefc93a268e2dc8de40053853ea4d0a771..f29dc5a9db7e4fe9783917749bd151ce80e40702 100644
Binary files a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_variance.bin and b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_1_variance.bin differ
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_beta.bin
index 757c9b270304e7be4b6c48bf07e14d01e6589358..ba12532332cec1d6ee20d16d04be81575a8f0802 100644
Binary files a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_beta.bin and b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_beta.bin differ
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_gamma.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_gamma.bin
index 11fe33ce32a25d64ca70a78d4171d5aaabbeac2c..bf0dd075d19280dfcda711fd95eeab6fb429b8f5 100644
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_gamma.bin
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_gamma.bin
@@ -1 +1 @@
-®a?Ÿ“?éa;?1_½?¡}"?TDa?ŠW?>ŸŽ?ån˜?Õn¬?}\[?dI&?ýÐn?ÂWJ?¯â ?c9?¬f@n3.?hWÝ>S>_??:?(?ÆF?7fa?($?—,k?öH?ô$?$í»?‰N?B-‚?ñ(O?
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+L¾ö>üiQ?-)]?!0?Lw_?`Ë…?ö%4?sÚ¢?²È7?œé`?Ò¿b?¬Y?hv?MC @\ÞY?ñ8P?”Ü\?»QI? ë8?ʤ‘?Ëîl?`¥&?,S?&›?wxr?Ãl_?@8l?k<,?6Ä…?Y={?YjC?2L>?
\ No newline at end of file
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_mean.bin
index 3404564f29df77809bca82309958aae2946ba53d..faec424f63fab99e4ba00101a005c1b84cb2f8f3 100644
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_mean.bin
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_mean.bin
@@ -1,2 +1,2 @@
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-K½vhá¾
\ No newline at end of file
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5[?&Ñ6>Ÿÿ.¿ýkn¾Ú4•>p%5¿Î(>" ×>Ù
+ ¿p²M>
\ No newline at end of file
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/batch_normalization_2_variance.bin
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/depthwise_conv2d_6_w.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/depthwise_conv2d_6_w.bin
similarity index 100%
rename from llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/depthwise_conv2d_6_w.bin
rename to llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/depthwise_conv2d_6_w.bin
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/layer_composition.txt b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/layer_composition.txt
index c072a337cce0887f50518088284081aca6428d1d..9b8b3f7e11a428a28fecbde2c204bf39b7e02703 100644
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/layer_composition.txt
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/layer_composition.txt
@@ -1,35 +1,41 @@
conv
-
+batchnorm
activation
-
-
+depthwise_conv
+batchnorm
activation
conv
-
+batchnorm
activation
-
-
+depthwise_conv
+batchnorm
activation
conv
-
+batchnorm
activation
-
-
+depthwise_conv
+batchnorm
activation
conv
-
+batchnorm
activation
-
-
+depthwise_conv
+batchnorm
activation
conv
-
+batchnorm
activation
-
-
+depthwise_conv
+batchnorm
activation
conv
-
+batchnorm
+activation
+depthwise_conv
+batchnorm
+activation
+conv
+batchnorm
activation
pool
dense add
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/layers.txt b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/layers.txt
index 8fc1f87c4d9eaf6306564e86dbd02f97774e300a..a9415755180a7ebdceb89b7e3e6d6cee258b18c4 100644
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/layers.txt
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/layers.txt
@@ -10,26 +10,32 @@ Conv2,10000,32,32,32,64,32,1,1
#tensorDepthwiseConv2
#tensorBatchNorm4
#tensorRelu4
-Conv3,10000,64,16,16,64,64,1,1
+Conv3,10000,64,16,16,128,64,1,1
#tensorBatchNorm5
#tensorRelu5
#tensorDepthwiseConv3
#tensorBatchNorm6
#tensorRelu6
-Conv4,10000,64,8,8,128,64,1,1
+Conv4,10000,128,16,16,128,128,1,1
#tensorBatchNorm7
#tensorRelu7
#tensorDepthwiseConv4
#tensorBatchNorm8
#tensorRelu8
-Conv5,10000,128,4,4,256,128,1,1
+Conv5,10000,128,8,8,256,128,1,1
#tensorBatchNorm9
#tensorRelu9
#tensorDepthwiseConv5
#tensorBatchNorm10
#tensorRelu10
-Conv6,10000,256,4,4,256,256,1,1
+Conv6,10000,256,8,8,256,256,1,1
#tensorBatchNorm11
#tensorRelu11
+#tensorDepthwiseConv6
+#tensorBatchNorm12
+#tensorRelu12
+Conv7,10000,256,4,4,512,256,1,1
+#tensorBatchNorm13
+#tensorRelu13
#tensorPooling1
-FC1,10000,1024,1024,10
+FC1,10000,2048,2048,10
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/approxhpvm_src.cc b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/approxhpvm_src.cc
deleted file mode 100644
index dc0c873c63333299981591cb5654cb38be9d4092..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/approxhpvm_src.cc
+++ /dev/null
@@ -1,1224 +0,0 @@
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <unistd.h>
-#include <fcntl.h>
-#include <sys/stat.h>
-#include <cstring>
-#include <visc.h>
-#include <tensorTypes.h>
-#include <tensorUtils.h>
-
-void var_0_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_convolution(t1, t2, 1, 1, 1, 1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_1_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_2_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_3_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 32);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_4_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_5_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_6_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_7_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_8_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_9_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 2, 2, 1, 64);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_10_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_11_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_12_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_13_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_14_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_15_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 128);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_16_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_17_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_18_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_19_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_20_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_21_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 2, 2, 1, 128);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_22_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_23_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_24_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_25_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_26_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_27_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 1, 1, 1, 256);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_28_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_29_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_30_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_31_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_32_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_33_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_group_convolution(t1, t2, 1, 1, 2, 2, 1, 256);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_34_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_35_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_36_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_convolution(t1, t2, 0, 0, 1, 1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_37_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2, void* t3, size_t bytes_t3, void* t4, size_t bytes_t4, void* t5, size_t bytes_t5) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(5, t1, t2, t3, t4, t5, 0);
-
- void *r = __visc__tensor_batchnorm(t1, t2, t3, t4, t5, 0.001);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_38_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_relu(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_39_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_pool_avg(t1, 2, 2, 0, 0, 2, 2);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_40_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_mul(t1, t2);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_41_node(void* t1, size_t bytes_t1, void* t2, size_t bytes_t2) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(2, t1, t2, 0);
-
- void *r = __visc__tensor_add(t1, t2);
- __visc__return(2, r, (size_t) 0);
-}
-
-void var_42_node(void* t1, size_t bytes_t1) {
- __visc__hint(visc::CUDNN_TARGET);
- __visc__attributes(1, t1, 0);
-
- void* r = __visc__tensor_softmax(t1);
- __visc__return(2, r, (size_t) 0);
-}
-
-void root(void* input, size_t input_bytes,
- void* conv2d_1_w, size_t conv2d_1_w_bytes,
- void* batch_normalization_1_gamma, size_t batch_normalization_1_gamma_bytes,
- void* batch_normalization_1_beta, size_t batch_normalization_1_beta_bytes,
- void* batch_normalization_1_mean, size_t batch_normalization_1_mean_bytes,
- void* batch_normalization_1_variance, size_t batch_normalization_1_variance_bytes,
- void* depthwise_conv2d_1_w, size_t depthwise_conv2d_1_w_bytes,
- void* batch_normalization_2_gamma, size_t batch_normalization_2_gamma_bytes,
- void* batch_normalization_2_beta, size_t batch_normalization_2_beta_bytes,
- void* batch_normalization_2_mean, size_t batch_normalization_2_mean_bytes,
- void* batch_normalization_2_variance, size_t batch_normalization_2_variance_bytes,
- void* conv2d_2_w, size_t conv2d_2_w_bytes,
- void* batch_normalization_3_gamma, size_t batch_normalization_3_gamma_bytes,
- void* batch_normalization_3_beta, size_t batch_normalization_3_beta_bytes,
- void* batch_normalization_3_mean, size_t batch_normalization_3_mean_bytes,
- void* batch_normalization_3_variance, size_t batch_normalization_3_variance_bytes,
- void* depthwise_conv2d_2_w, size_t depthwise_conv2d_2_w_bytes,
- void* batch_normalization_4_gamma, size_t batch_normalization_4_gamma_bytes,
- void* batch_normalization_4_beta, size_t batch_normalization_4_beta_bytes,
- void* batch_normalization_4_mean, size_t batch_normalization_4_mean_bytes,
- void* batch_normalization_4_variance, size_t batch_normalization_4_variance_bytes,
- void* conv2d_3_w, size_t conv2d_3_w_bytes,
- void* batch_normalization_5_gamma, size_t batch_normalization_5_gamma_bytes,
- void* batch_normalization_5_beta, size_t batch_normalization_5_beta_bytes,
- void* batch_normalization_5_mean, size_t batch_normalization_5_mean_bytes,
- void* batch_normalization_5_variance, size_t batch_normalization_5_variance_bytes,
- void* depthwise_conv2d_3_w, size_t depthwise_conv2d_3_w_bytes,
- void* batch_normalization_6_gamma, size_t batch_normalization_6_gamma_bytes,
- void* batch_normalization_6_beta, size_t batch_normalization_6_beta_bytes,
- void* batch_normalization_6_mean, size_t batch_normalization_6_mean_bytes,
- void* batch_normalization_6_variance, size_t batch_normalization_6_variance_bytes,
- void* conv2d_4_w, size_t conv2d_4_w_bytes,
- void* batch_normalization_7_gamma, size_t batch_normalization_7_gamma_bytes,
- void* batch_normalization_7_beta, size_t batch_normalization_7_beta_bytes,
- void* batch_normalization_7_mean, size_t batch_normalization_7_mean_bytes,
- void* batch_normalization_7_variance, size_t batch_normalization_7_variance_bytes,
- void* depthwise_conv2d_4_w, size_t depthwise_conv2d_4_w_bytes,
- void* batch_normalization_8_gamma, size_t batch_normalization_8_gamma_bytes,
- void* batch_normalization_8_beta, size_t batch_normalization_8_beta_bytes,
- void* batch_normalization_8_mean, size_t batch_normalization_8_mean_bytes,
- void* batch_normalization_8_variance, size_t batch_normalization_8_variance_bytes,
- void* conv2d_5_w, size_t conv2d_5_w_bytes,
- void* batch_normalization_9_gamma, size_t batch_normalization_9_gamma_bytes,
- void* batch_normalization_9_beta, size_t batch_normalization_9_beta_bytes,
- void* batch_normalization_9_mean, size_t batch_normalization_9_mean_bytes,
- void* batch_normalization_9_variance, size_t batch_normalization_9_variance_bytes,
- void* depthwise_conv2d_5_w, size_t depthwise_conv2d_5_w_bytes,
- void* batch_normalization_10_gamma, size_t batch_normalization_10_gamma_bytes,
- void* batch_normalization_10_beta, size_t batch_normalization_10_beta_bytes,
- void* batch_normalization_10_mean, size_t batch_normalization_10_mean_bytes,
- void* batch_normalization_10_variance, size_t batch_normalization_10_variance_bytes,
- void* conv2d_6_w, size_t conv2d_6_w_bytes,
- void* batch_normalization_11_gamma, size_t batch_normalization_11_gamma_bytes,
- void* batch_normalization_11_beta, size_t batch_normalization_11_beta_bytes,
- void* batch_normalization_11_mean, size_t batch_normalization_11_mean_bytes,
- void* batch_normalization_11_variance, size_t batch_normalization_11_variance_bytes,
- void* depthwise_conv2d_6_w, size_t depthwise_conv2d_6_w_bytes,
- void* batch_normalization_12_gamma, size_t batch_normalization_12_gamma_bytes,
- void* batch_normalization_12_beta, size_t batch_normalization_12_beta_bytes,
- void* batch_normalization_12_mean, size_t batch_normalization_12_mean_bytes,
- void* batch_normalization_12_variance, size_t batch_normalization_12_variance_bytes,
- void* conv2d_7_w, size_t conv2d_7_w_bytes,
- void* batch_normalization_13_gamma, size_t batch_normalization_13_gamma_bytes,
- void* batch_normalization_13_beta, size_t batch_normalization_13_beta_bytes,
- void* batch_normalization_13_mean, size_t batch_normalization_13_mean_bytes,
- void* batch_normalization_13_variance, size_t batch_normalization_13_variance_bytes,
- void* dense_1_w, size_t dense_1_w_bytes,
- void* dense_1_b, size_t dense_1_b_bytes){
-
-
- __visc__hint(visc::CPU_TARGET);
- __visc__attributes(68, input, conv2d_1_w, batch_normalization_1_gamma, batch_normalization_1_beta, batch_normalization_1_mean, batch_normalization_1_variance, depthwise_conv2d_1_w, batch_normalization_2_gamma, batch_normalization_2_beta, batch_normalization_2_mean, batch_normalization_2_variance, conv2d_2_w, batch_normalization_3_gamma, batch_normalization_3_beta, batch_normalization_3_mean, batch_normalization_3_variance, depthwise_conv2d_2_w, batch_normalization_4_gamma, batch_normalization_4_beta, batch_normalization_4_mean, batch_normalization_4_variance, conv2d_3_w, batch_normalization_5_gamma, batch_normalization_5_beta, batch_normalization_5_mean, batch_normalization_5_variance, depthwise_conv2d_3_w, batch_normalization_6_gamma, batch_normalization_6_beta, batch_normalization_6_mean, batch_normalization_6_variance, conv2d_4_w, batch_normalization_7_gamma, batch_normalization_7_beta, batch_normalization_7_mean, batch_normalization_7_variance, depthwise_conv2d_4_w, batch_normalization_8_gamma, batch_normalization_8_beta, batch_normalization_8_mean, batch_normalization_8_variance, conv2d_5_w, batch_normalization_9_gamma, batch_normalization_9_beta, batch_normalization_9_mean, batch_normalization_9_variance, depthwise_conv2d_5_w, batch_normalization_10_gamma, batch_normalization_10_beta, batch_normalization_10_mean, batch_normalization_10_variance, conv2d_6_w, batch_normalization_11_gamma, batch_normalization_11_beta, batch_normalization_11_mean, batch_normalization_11_variance, depthwise_conv2d_6_w, batch_normalization_12_gamma, batch_normalization_12_beta, batch_normalization_12_mean, batch_normalization_12_variance, conv2d_7_w, batch_normalization_13_gamma, batch_normalization_13_beta, batch_normalization_13_mean, batch_normalization_13_variance, dense_1_w, dense_1_b, 0);
-
-
- void* var_0 = __visc__createNodeND(0, var_0_node);
-
- __visc__bindIn(var_0, 0, 0, 0);
- __visc__bindIn(var_0, 1, 1, 0);
- __visc__bindIn(var_0, 2, 2, 0);
- __visc__bindIn(var_0, 3, 3, 0);
-
- void* var_1 = __visc__createNodeND(0, var_1_node);
-
- __visc__edge(var_0, var_1, 1, 0, 0, 0);
- __visc__edge(var_0, var_1, 1, 1, 1, 0);
- __visc__bindIn(var_1, 4, 2, 0);
- __visc__bindIn(var_1, 5, 3, 0);
- __visc__bindIn(var_1, 6, 4, 0);
- __visc__bindIn(var_1, 7, 5, 0);
- __visc__bindIn(var_1, 8, 6, 0);
- __visc__bindIn(var_1, 9, 7, 0);
- __visc__bindIn(var_1, 10, 8, 0);
- __visc__bindIn(var_1, 11, 9, 0);
-
- void* var_2 = __visc__createNodeND(0, var_2_node);
-
- __visc__edge(var_1, var_2, 1, 0, 0, 0);
- __visc__edge(var_1, var_2, 1, 1, 1, 0);
-
- void* var_3 = __visc__createNodeND(0, var_3_node);
-
- __visc__edge(var_2, var_3, 1, 0, 0, 0);
- __visc__edge(var_2, var_3, 1, 1, 1, 0);
- __visc__bindIn(var_3, 12, 2, 0);
- __visc__bindIn(var_3, 13, 3, 0);
-
- void* var_4 = __visc__createNodeND(0, var_4_node);
-
- __visc__edge(var_3, var_4, 1, 0, 0, 0);
- __visc__edge(var_3, var_4, 1, 1, 1, 0);
- __visc__bindIn(var_4, 14, 2, 0);
- __visc__bindIn(var_4, 15, 3, 0);
- __visc__bindIn(var_4, 16, 4, 0);
- __visc__bindIn(var_4, 17, 5, 0);
- __visc__bindIn(var_4, 18, 6, 0);
- __visc__bindIn(var_4, 19, 7, 0);
- __visc__bindIn(var_4, 20, 8, 0);
- __visc__bindIn(var_4, 21, 9, 0);
-
- void* var_5 = __visc__createNodeND(0, var_5_node);
-
- __visc__edge(var_4, var_5, 1, 0, 0, 0);
- __visc__edge(var_4, var_5, 1, 1, 1, 0);
-
- void* var_6 = __visc__createNodeND(0, var_6_node);
-
- __visc__edge(var_5, var_6, 1, 0, 0, 0);
- __visc__edge(var_5, var_6, 1, 1, 1, 0);
- __visc__bindIn(var_6, 22, 2, 0);
- __visc__bindIn(var_6, 23, 3, 0);
-
- void* var_7 = __visc__createNodeND(0, var_7_node);
-
- __visc__edge(var_6, var_7, 1, 0, 0, 0);
- __visc__edge(var_6, var_7, 1, 1, 1, 0);
- __visc__bindIn(var_7, 24, 2, 0);
- __visc__bindIn(var_7, 25, 3, 0);
- __visc__bindIn(var_7, 26, 4, 0);
- __visc__bindIn(var_7, 27, 5, 0);
- __visc__bindIn(var_7, 28, 6, 0);
- __visc__bindIn(var_7, 29, 7, 0);
- __visc__bindIn(var_7, 30, 8, 0);
- __visc__bindIn(var_7, 31, 9, 0);
-
- void* var_8 = __visc__createNodeND(0, var_8_node);
-
- __visc__edge(var_7, var_8, 1, 0, 0, 0);
- __visc__edge(var_7, var_8, 1, 1, 1, 0);
-
- void* var_9 = __visc__createNodeND(0, var_9_node);
-
- __visc__edge(var_8, var_9, 1, 0, 0, 0);
- __visc__edge(var_8, var_9, 1, 1, 1, 0);
- __visc__bindIn(var_9, 32, 2, 0);
- __visc__bindIn(var_9, 33, 3, 0);
-
- void* var_10 = __visc__createNodeND(0, var_10_node);
-
- __visc__edge(var_9, var_10, 1, 0, 0, 0);
- __visc__edge(var_9, var_10, 1, 1, 1, 0);
- __visc__bindIn(var_10, 34, 2, 0);
- __visc__bindIn(var_10, 35, 3, 0);
- __visc__bindIn(var_10, 36, 4, 0);
- __visc__bindIn(var_10, 37, 5, 0);
- __visc__bindIn(var_10, 38, 6, 0);
- __visc__bindIn(var_10, 39, 7, 0);
- __visc__bindIn(var_10, 40, 8, 0);
- __visc__bindIn(var_10, 41, 9, 0);
-
- void* var_11 = __visc__createNodeND(0, var_11_node);
-
- __visc__edge(var_10, var_11, 1, 0, 0, 0);
- __visc__edge(var_10, var_11, 1, 1, 1, 0);
-
- void* var_12 = __visc__createNodeND(0, var_12_node);
-
- __visc__edge(var_11, var_12, 1, 0, 0, 0);
- __visc__edge(var_11, var_12, 1, 1, 1, 0);
- __visc__bindIn(var_12, 42, 2, 0);
- __visc__bindIn(var_12, 43, 3, 0);
-
- void* var_13 = __visc__createNodeND(0, var_13_node);
-
- __visc__edge(var_12, var_13, 1, 0, 0, 0);
- __visc__edge(var_12, var_13, 1, 1, 1, 0);
- __visc__bindIn(var_13, 44, 2, 0);
- __visc__bindIn(var_13, 45, 3, 0);
- __visc__bindIn(var_13, 46, 4, 0);
- __visc__bindIn(var_13, 47, 5, 0);
- __visc__bindIn(var_13, 48, 6, 0);
- __visc__bindIn(var_13, 49, 7, 0);
- __visc__bindIn(var_13, 50, 8, 0);
- __visc__bindIn(var_13, 51, 9, 0);
-
- void* var_14 = __visc__createNodeND(0, var_14_node);
-
- __visc__edge(var_13, var_14, 1, 0, 0, 0);
- __visc__edge(var_13, var_14, 1, 1, 1, 0);
-
- void* var_15 = __visc__createNodeND(0, var_15_node);
-
- __visc__edge(var_14, var_15, 1, 0, 0, 0);
- __visc__edge(var_14, var_15, 1, 1, 1, 0);
- __visc__bindIn(var_15, 52, 2, 0);
- __visc__bindIn(var_15, 53, 3, 0);
-
- void* var_16 = __visc__createNodeND(0, var_16_node);
-
- __visc__edge(var_15, var_16, 1, 0, 0, 0);
- __visc__edge(var_15, var_16, 1, 1, 1, 0);
- __visc__bindIn(var_16, 54, 2, 0);
- __visc__bindIn(var_16, 55, 3, 0);
- __visc__bindIn(var_16, 56, 4, 0);
- __visc__bindIn(var_16, 57, 5, 0);
- __visc__bindIn(var_16, 58, 6, 0);
- __visc__bindIn(var_16, 59, 7, 0);
- __visc__bindIn(var_16, 60, 8, 0);
- __visc__bindIn(var_16, 61, 9, 0);
-
- void* var_17 = __visc__createNodeND(0, var_17_node);
-
- __visc__edge(var_16, var_17, 1, 0, 0, 0);
- __visc__edge(var_16, var_17, 1, 1, 1, 0);
-
- void* var_18 = __visc__createNodeND(0, var_18_node);
-
- __visc__edge(var_17, var_18, 1, 0, 0, 0);
- __visc__edge(var_17, var_18, 1, 1, 1, 0);
- __visc__bindIn(var_18, 62, 2, 0);
- __visc__bindIn(var_18, 63, 3, 0);
-
- void* var_19 = __visc__createNodeND(0, var_19_node);
-
- __visc__edge(var_18, var_19, 1, 0, 0, 0);
- __visc__edge(var_18, var_19, 1, 1, 1, 0);
- __visc__bindIn(var_19, 64, 2, 0);
- __visc__bindIn(var_19, 65, 3, 0);
- __visc__bindIn(var_19, 66, 4, 0);
- __visc__bindIn(var_19, 67, 5, 0);
- __visc__bindIn(var_19, 68, 6, 0);
- __visc__bindIn(var_19, 69, 7, 0);
- __visc__bindIn(var_19, 70, 8, 0);
- __visc__bindIn(var_19, 71, 9, 0);
-
- void* var_20 = __visc__createNodeND(0, var_20_node);
-
- __visc__edge(var_19, var_20, 1, 0, 0, 0);
- __visc__edge(var_19, var_20, 1, 1, 1, 0);
-
- void* var_21 = __visc__createNodeND(0, var_21_node);
-
- __visc__edge(var_20, var_21, 1, 0, 0, 0);
- __visc__edge(var_20, var_21, 1, 1, 1, 0);
- __visc__bindIn(var_21, 72, 2, 0);
- __visc__bindIn(var_21, 73, 3, 0);
-
- void* var_22 = __visc__createNodeND(0, var_22_node);
-
- __visc__edge(var_21, var_22, 1, 0, 0, 0);
- __visc__edge(var_21, var_22, 1, 1, 1, 0);
- __visc__bindIn(var_22, 74, 2, 0);
- __visc__bindIn(var_22, 75, 3, 0);
- __visc__bindIn(var_22, 76, 4, 0);
- __visc__bindIn(var_22, 77, 5, 0);
- __visc__bindIn(var_22, 78, 6, 0);
- __visc__bindIn(var_22, 79, 7, 0);
- __visc__bindIn(var_22, 80, 8, 0);
- __visc__bindIn(var_22, 81, 9, 0);
-
- void* var_23 = __visc__createNodeND(0, var_23_node);
-
- __visc__edge(var_22, var_23, 1, 0, 0, 0);
- __visc__edge(var_22, var_23, 1, 1, 1, 0);
-
- void* var_24 = __visc__createNodeND(0, var_24_node);
-
- __visc__edge(var_23, var_24, 1, 0, 0, 0);
- __visc__edge(var_23, var_24, 1, 1, 1, 0);
- __visc__bindIn(var_24, 82, 2, 0);
- __visc__bindIn(var_24, 83, 3, 0);
-
- void* var_25 = __visc__createNodeND(0, var_25_node);
-
- __visc__edge(var_24, var_25, 1, 0, 0, 0);
- __visc__edge(var_24, var_25, 1, 1, 1, 0);
- __visc__bindIn(var_25, 84, 2, 0);
- __visc__bindIn(var_25, 85, 3, 0);
- __visc__bindIn(var_25, 86, 4, 0);
- __visc__bindIn(var_25, 87, 5, 0);
- __visc__bindIn(var_25, 88, 6, 0);
- __visc__bindIn(var_25, 89, 7, 0);
- __visc__bindIn(var_25, 90, 8, 0);
- __visc__bindIn(var_25, 91, 9, 0);
-
- void* var_26 = __visc__createNodeND(0, var_26_node);
-
- __visc__edge(var_25, var_26, 1, 0, 0, 0);
- __visc__edge(var_25, var_26, 1, 1, 1, 0);
-
- void* var_27 = __visc__createNodeND(0, var_27_node);
-
- __visc__edge(var_26, var_27, 1, 0, 0, 0);
- __visc__edge(var_26, var_27, 1, 1, 1, 0);
- __visc__bindIn(var_27, 92, 2, 0);
- __visc__bindIn(var_27, 93, 3, 0);
-
- void* var_28 = __visc__createNodeND(0, var_28_node);
-
- __visc__edge(var_27, var_28, 1, 0, 0, 0);
- __visc__edge(var_27, var_28, 1, 1, 1, 0);
- __visc__bindIn(var_28, 94, 2, 0);
- __visc__bindIn(var_28, 95, 3, 0);
- __visc__bindIn(var_28, 96, 4, 0);
- __visc__bindIn(var_28, 97, 5, 0);
- __visc__bindIn(var_28, 98, 6, 0);
- __visc__bindIn(var_28, 99, 7, 0);
- __visc__bindIn(var_28, 100, 8, 0);
- __visc__bindIn(var_28, 101, 9, 0);
-
- void* var_29 = __visc__createNodeND(0, var_29_node);
-
- __visc__edge(var_28, var_29, 1, 0, 0, 0);
- __visc__edge(var_28, var_29, 1, 1, 1, 0);
-
- void* var_30 = __visc__createNodeND(0, var_30_node);
-
- __visc__edge(var_29, var_30, 1, 0, 0, 0);
- __visc__edge(var_29, var_30, 1, 1, 1, 0);
- __visc__bindIn(var_30, 102, 2, 0);
- __visc__bindIn(var_30, 103, 3, 0);
-
- void* var_31 = __visc__createNodeND(0, var_31_node);
-
- __visc__edge(var_30, var_31, 1, 0, 0, 0);
- __visc__edge(var_30, var_31, 1, 1, 1, 0);
- __visc__bindIn(var_31, 104, 2, 0);
- __visc__bindIn(var_31, 105, 3, 0);
- __visc__bindIn(var_31, 106, 4, 0);
- __visc__bindIn(var_31, 107, 5, 0);
- __visc__bindIn(var_31, 108, 6, 0);
- __visc__bindIn(var_31, 109, 7, 0);
- __visc__bindIn(var_31, 110, 8, 0);
- __visc__bindIn(var_31, 111, 9, 0);
-
- void* var_32 = __visc__createNodeND(0, var_32_node);
-
- __visc__edge(var_31, var_32, 1, 0, 0, 0);
- __visc__edge(var_31, var_32, 1, 1, 1, 0);
-
- void* var_33 = __visc__createNodeND(0, var_33_node);
-
- __visc__edge(var_32, var_33, 1, 0, 0, 0);
- __visc__edge(var_32, var_33, 1, 1, 1, 0);
- __visc__bindIn(var_33, 112, 2, 0);
- __visc__bindIn(var_33, 113, 3, 0);
-
- void* var_34 = __visc__createNodeND(0, var_34_node);
-
- __visc__edge(var_33, var_34, 1, 0, 0, 0);
- __visc__edge(var_33, var_34, 1, 1, 1, 0);
- __visc__bindIn(var_34, 114, 2, 0);
- __visc__bindIn(var_34, 115, 3, 0);
- __visc__bindIn(var_34, 116, 4, 0);
- __visc__bindIn(var_34, 117, 5, 0);
- __visc__bindIn(var_34, 118, 6, 0);
- __visc__bindIn(var_34, 119, 7, 0);
- __visc__bindIn(var_34, 120, 8, 0);
- __visc__bindIn(var_34, 121, 9, 0);
-
- void* var_35 = __visc__createNodeND(0, var_35_node);
-
- __visc__edge(var_34, var_35, 1, 0, 0, 0);
- __visc__edge(var_34, var_35, 1, 1, 1, 0);
-
- void* var_36 = __visc__createNodeND(0, var_36_node);
-
- __visc__edge(var_35, var_36, 1, 0, 0, 0);
- __visc__edge(var_35, var_36, 1, 1, 1, 0);
- __visc__bindIn(var_36, 122, 2, 0);
- __visc__bindIn(var_36, 123, 3, 0);
-
- void* var_37 = __visc__createNodeND(0, var_37_node);
-
- __visc__edge(var_36, var_37, 1, 0, 0, 0);
- __visc__edge(var_36, var_37, 1, 1, 1, 0);
- __visc__bindIn(var_37, 124, 2, 0);
- __visc__bindIn(var_37, 125, 3, 0);
- __visc__bindIn(var_37, 126, 4, 0);
- __visc__bindIn(var_37, 127, 5, 0);
- __visc__bindIn(var_37, 128, 6, 0);
- __visc__bindIn(var_37, 129, 7, 0);
- __visc__bindIn(var_37, 130, 8, 0);
- __visc__bindIn(var_37, 131, 9, 0);
-
- void* var_38 = __visc__createNodeND(0, var_38_node);
-
- __visc__edge(var_37, var_38, 1, 0, 0, 0);
- __visc__edge(var_37, var_38, 1, 1, 1, 0);
-
- void* var_39 = __visc__createNodeND(0, var_39_node);
-
- __visc__edge(var_38, var_39, 1, 0, 0, 0);
- __visc__edge(var_38, var_39, 1, 1, 1, 0);
-
- void* var_40 = __visc__createNodeND(0, var_40_node);
-
- __visc__edge(var_39, var_40, 1, 0, 0, 0);
- __visc__edge(var_39, var_40, 1, 1, 1, 0);
- __visc__bindIn(var_40, 132, 2, 0);
- __visc__bindIn(var_40, 133, 3, 0);
-
- void* var_41 = __visc__createNodeND(0, var_41_node);
-
- __visc__edge(var_40, var_41, 1, 0, 0, 0);
- __visc__edge(var_40, var_41, 1, 1, 1, 0);
- __visc__bindIn(var_41, 134, 2, 0);
- __visc__bindIn(var_41, 135, 3, 0);
-
- void* var_42 = __visc__createNodeND(0, var_42_node);
-
- __visc__edge(var_41, var_42, 1, 0, 0, 0);
- __visc__edge(var_41, var_42, 1, 1, 1, 0);
-
- __visc__bindOut(var_42, 0, 0, 0);
- __visc__bindOut(var_42, 1, 1, 0);
-
-}
-
-struct ret_t {
- void* tensor;
- size_t bytes;
-};
-
-typedef struct __attribute__((__packed__)) {
- void* input;
- size_t input_bytes;
- void* conv2d_1_w;
- size_t conv2d_1_w_bytes;
- void* batch_normalization_1_gamma;
- size_t batch_normalization_1_gamma_bytes;
- void* batch_normalization_1_beta;
- size_t batch_normalization_1_beta_bytes;
- void* batch_normalization_1_mean;
- size_t batch_normalization_1_mean_bytes;
- void* batch_normalization_1_variance;
- size_t batch_normalization_1_variance_bytes;
- void* depthwise_conv2d_1_w;
- size_t depthwise_conv2d_1_w_bytes;
- void* batch_normalization_2_gamma;
- size_t batch_normalization_2_gamma_bytes;
- void* batch_normalization_2_beta;
- size_t batch_normalization_2_beta_bytes;
- void* batch_normalization_2_mean;
- size_t batch_normalization_2_mean_bytes;
- void* batch_normalization_2_variance;
- size_t batch_normalization_2_variance_bytes;
- void* conv2d_2_w;
- size_t conv2d_2_w_bytes;
- void* batch_normalization_3_gamma;
- size_t batch_normalization_3_gamma_bytes;
- void* batch_normalization_3_beta;
- size_t batch_normalization_3_beta_bytes;
- void* batch_normalization_3_mean;
- size_t batch_normalization_3_mean_bytes;
- void* batch_normalization_3_variance;
- size_t batch_normalization_3_variance_bytes;
- void* depthwise_conv2d_2_w;
- size_t depthwise_conv2d_2_w_bytes;
- void* batch_normalization_4_gamma;
- size_t batch_normalization_4_gamma_bytes;
- void* batch_normalization_4_beta;
- size_t batch_normalization_4_beta_bytes;
- void* batch_normalization_4_mean;
- size_t batch_normalization_4_mean_bytes;
- void* batch_normalization_4_variance;
- size_t batch_normalization_4_variance_bytes;
- void* conv2d_3_w;
- size_t conv2d_3_w_bytes;
- void* batch_normalization_5_gamma;
- size_t batch_normalization_5_gamma_bytes;
- void* batch_normalization_5_beta;
- size_t batch_normalization_5_beta_bytes;
- void* batch_normalization_5_mean;
- size_t batch_normalization_5_mean_bytes;
- void* batch_normalization_5_variance;
- size_t batch_normalization_5_variance_bytes;
- void* depthwise_conv2d_3_w;
- size_t depthwise_conv2d_3_w_bytes;
- void* batch_normalization_6_gamma;
- size_t batch_normalization_6_gamma_bytes;
- void* batch_normalization_6_beta;
- size_t batch_normalization_6_beta_bytes;
- void* batch_normalization_6_mean;
- size_t batch_normalization_6_mean_bytes;
- void* batch_normalization_6_variance;
- size_t batch_normalization_6_variance_bytes;
- void* conv2d_4_w;
- size_t conv2d_4_w_bytes;
- void* batch_normalization_7_gamma;
- size_t batch_normalization_7_gamma_bytes;
- void* batch_normalization_7_beta;
- size_t batch_normalization_7_beta_bytes;
- void* batch_normalization_7_mean;
- size_t batch_normalization_7_mean_bytes;
- void* batch_normalization_7_variance;
- size_t batch_normalization_7_variance_bytes;
- void* depthwise_conv2d_4_w;
- size_t depthwise_conv2d_4_w_bytes;
- void* batch_normalization_8_gamma;
- size_t batch_normalization_8_gamma_bytes;
- void* batch_normalization_8_beta;
- size_t batch_normalization_8_beta_bytes;
- void* batch_normalization_8_mean;
- size_t batch_normalization_8_mean_bytes;
- void* batch_normalization_8_variance;
- size_t batch_normalization_8_variance_bytes;
- void* conv2d_5_w;
- size_t conv2d_5_w_bytes;
- void* batch_normalization_9_gamma;
- size_t batch_normalization_9_gamma_bytes;
- void* batch_normalization_9_beta;
- size_t batch_normalization_9_beta_bytes;
- void* batch_normalization_9_mean;
- size_t batch_normalization_9_mean_bytes;
- void* batch_normalization_9_variance;
- size_t batch_normalization_9_variance_bytes;
- void* depthwise_conv2d_5_w;
- size_t depthwise_conv2d_5_w_bytes;
- void* batch_normalization_10_gamma;
- size_t batch_normalization_10_gamma_bytes;
- void* batch_normalization_10_beta;
- size_t batch_normalization_10_beta_bytes;
- void* batch_normalization_10_mean;
- size_t batch_normalization_10_mean_bytes;
- void* batch_normalization_10_variance;
- size_t batch_normalization_10_variance_bytes;
- void* conv2d_6_w;
- size_t conv2d_6_w_bytes;
- void* batch_normalization_11_gamma;
- size_t batch_normalization_11_gamma_bytes;
- void* batch_normalization_11_beta;
- size_t batch_normalization_11_beta_bytes;
- void* batch_normalization_11_mean;
- size_t batch_normalization_11_mean_bytes;
- void* batch_normalization_11_variance;
- size_t batch_normalization_11_variance_bytes;
- void* depthwise_conv2d_6_w;
- size_t depthwise_conv2d_6_w_bytes;
- void* batch_normalization_12_gamma;
- size_t batch_normalization_12_gamma_bytes;
- void* batch_normalization_12_beta;
- size_t batch_normalization_12_beta_bytes;
- void* batch_normalization_12_mean;
- size_t batch_normalization_12_mean_bytes;
- void* batch_normalization_12_variance;
- size_t batch_normalization_12_variance_bytes;
- void* conv2d_7_w;
- size_t conv2d_7_w_bytes;
- void* batch_normalization_13_gamma;
- size_t batch_normalization_13_gamma_bytes;
- void* batch_normalization_13_beta;
- size_t batch_normalization_13_beta_bytes;
- void* batch_normalization_13_mean;
- size_t batch_normalization_13_mean_bytes;
- void* batch_normalization_13_variance;
- size_t batch_normalization_13_variance_bytes;
- void* dense_1_w;
- size_t dense_1_w_bytes;
- void* dense_1_b;
- size_t dense_1_b_bytes;
-
- struct ret_t r;
-}
-RootIn;
-
-int main(){
-
-std::string dir_prefix = std::string("data/mobilenet_shallow_nathan/");
-std::string input_path = dir_prefix + std::string("input.bin");
-std::string labels_path = dir_prefix + std::string("labels.bin");
-std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
-void* conv2d_1_w = readTrainedWeights(conv2d_1_w_path.c_str(), 0,32,3,3,3);
-std::string batch_normalization_1_gamma_path = dir_prefix + std::string("batch_normalization_1_gamma.bin");
-void* batch_normalization_1_gamma = readTrainedWeights(batch_normalization_1_gamma_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_1_beta_path = dir_prefix + std::string("batch_normalization_1_beta.bin");
-void* batch_normalization_1_beta = readTrainedWeights(batch_normalization_1_beta_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_1_mean_path = dir_prefix + std::string("batch_normalization_1_mean.bin");
-void* batch_normalization_1_mean = readTrainedWeights(batch_normalization_1_mean_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_1_variance_path = dir_prefix + std::string("batch_normalization_1_variance.bin");
-void* batch_normalization_1_variance = readTrainedWeights(batch_normalization_1_variance_path.c_str(), 0,1,32,1,1);
-std::string depthwise_conv2d_1_w_path = dir_prefix + std::string("depthwise_conv2d_1_w.bin");
-void* depthwise_conv2d_1_w = readTrainedWeights(depthwise_conv2d_1_w_path.c_str(), 0,32,1,3,3);
-std::string batch_normalization_2_gamma_path = dir_prefix + std::string("batch_normalization_2_gamma.bin");
-void* batch_normalization_2_gamma = readTrainedWeights(batch_normalization_2_gamma_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_2_beta_path = dir_prefix + std::string("batch_normalization_2_beta.bin");
-void* batch_normalization_2_beta = readTrainedWeights(batch_normalization_2_beta_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_2_mean_path = dir_prefix + std::string("batch_normalization_2_mean.bin");
-void* batch_normalization_2_mean = readTrainedWeights(batch_normalization_2_mean_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_2_variance_path = dir_prefix + std::string("batch_normalization_2_variance.bin");
-void* batch_normalization_2_variance = readTrainedWeights(batch_normalization_2_variance_path.c_str(), 0,1,32,1,1);
-std::string conv2d_2_w_path = dir_prefix + std::string("conv2d_2_w.bin");
-void* conv2d_2_w = readTrainedWeights(conv2d_2_w_path.c_str(), 0,64,32,1,1);
-std::string batch_normalization_3_gamma_path = dir_prefix + std::string("batch_normalization_3_gamma.bin");
-void* batch_normalization_3_gamma = readTrainedWeights(batch_normalization_3_gamma_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_3_beta_path = dir_prefix + std::string("batch_normalization_3_beta.bin");
-void* batch_normalization_3_beta = readTrainedWeights(batch_normalization_3_beta_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_3_mean_path = dir_prefix + std::string("batch_normalization_3_mean.bin");
-void* batch_normalization_3_mean = readTrainedWeights(batch_normalization_3_mean_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_3_variance_path = dir_prefix + std::string("batch_normalization_3_variance.bin");
-void* batch_normalization_3_variance = readTrainedWeights(batch_normalization_3_variance_path.c_str(), 0,1,64,1,1);
-std::string depthwise_conv2d_2_w_path = dir_prefix + std::string("depthwise_conv2d_2_w.bin");
-void* depthwise_conv2d_2_w = readTrainedWeights(depthwise_conv2d_2_w_path.c_str(), 0,64,1,3,3);
-std::string batch_normalization_4_gamma_path = dir_prefix + std::string("batch_normalization_4_gamma.bin");
-void* batch_normalization_4_gamma = readTrainedWeights(batch_normalization_4_gamma_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_4_beta_path = dir_prefix + std::string("batch_normalization_4_beta.bin");
-void* batch_normalization_4_beta = readTrainedWeights(batch_normalization_4_beta_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_4_mean_path = dir_prefix + std::string("batch_normalization_4_mean.bin");
-void* batch_normalization_4_mean = readTrainedWeights(batch_normalization_4_mean_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_4_variance_path = dir_prefix + std::string("batch_normalization_4_variance.bin");
-void* batch_normalization_4_variance = readTrainedWeights(batch_normalization_4_variance_path.c_str(), 0,1,64,1,1);
-std::string conv2d_3_w_path = dir_prefix + std::string("conv2d_3_w.bin");
-void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,128,64,1,1);
-std::string batch_normalization_5_gamma_path = dir_prefix + std::string("batch_normalization_5_gamma.bin");
-void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_5_beta_path = dir_prefix + std::string("batch_normalization_5_beta.bin");
-void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_5_mean_path = dir_prefix + std::string("batch_normalization_5_mean.bin");
-void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_5_variance_path = dir_prefix + std::string("batch_normalization_5_variance.bin");
-void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,128,1,1);
-std::string depthwise_conv2d_3_w_path = dir_prefix + std::string("depthwise_conv2d_3_w.bin");
-void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,128,1,3,3);
-std::string batch_normalization_6_gamma_path = dir_prefix + std::string("batch_normalization_6_gamma.bin");
-void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_6_beta_path = dir_prefix + std::string("batch_normalization_6_beta.bin");
-void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_6_mean_path = dir_prefix + std::string("batch_normalization_6_mean.bin");
-void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_6_variance_path = dir_prefix + std::string("batch_normalization_6_variance.bin");
-void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,128,1,1);
-std::string conv2d_4_w_path = dir_prefix + std::string("conv2d_4_w.bin");
-void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,128,1,1);
-std::string batch_normalization_7_gamma_path = dir_prefix + std::string("batch_normalization_7_gamma.bin");
-void* batch_normalization_7_gamma = readTrainedWeights(batch_normalization_7_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_7_beta_path = dir_prefix + std::string("batch_normalization_7_beta.bin");
-void* batch_normalization_7_beta = readTrainedWeights(batch_normalization_7_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_7_mean_path = dir_prefix + std::string("batch_normalization_7_mean.bin");
-void* batch_normalization_7_mean = readTrainedWeights(batch_normalization_7_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_7_variance_path = dir_prefix + std::string("batch_normalization_7_variance.bin");
-void* batch_normalization_7_variance = readTrainedWeights(batch_normalization_7_variance_path.c_str(), 0,1,128,1,1);
-std::string depthwise_conv2d_4_w_path = dir_prefix + std::string("depthwise_conv2d_4_w.bin");
-void* depthwise_conv2d_4_w = readTrainedWeights(depthwise_conv2d_4_w_path.c_str(), 0,128,1,3,3);
-std::string batch_normalization_8_gamma_path = dir_prefix + std::string("batch_normalization_8_gamma.bin");
-void* batch_normalization_8_gamma = readTrainedWeights(batch_normalization_8_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_8_beta_path = dir_prefix + std::string("batch_normalization_8_beta.bin");
-void* batch_normalization_8_beta = readTrainedWeights(batch_normalization_8_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_8_mean_path = dir_prefix + std::string("batch_normalization_8_mean.bin");
-void* batch_normalization_8_mean = readTrainedWeights(batch_normalization_8_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_8_variance_path = dir_prefix + std::string("batch_normalization_8_variance.bin");
-void* batch_normalization_8_variance = readTrainedWeights(batch_normalization_8_variance_path.c_str(), 0,1,128,1,1);
-std::string conv2d_5_w_path = dir_prefix + std::string("conv2d_5_w.bin");
-void* conv2d_5_w = readTrainedWeights(conv2d_5_w_path.c_str(), 0,256,128,1,1);
-std::string batch_normalization_9_gamma_path = dir_prefix + std::string("batch_normalization_9_gamma.bin");
-void* batch_normalization_9_gamma = readTrainedWeights(batch_normalization_9_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_9_beta_path = dir_prefix + std::string("batch_normalization_9_beta.bin");
-void* batch_normalization_9_beta = readTrainedWeights(batch_normalization_9_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_9_mean_path = dir_prefix + std::string("batch_normalization_9_mean.bin");
-void* batch_normalization_9_mean = readTrainedWeights(batch_normalization_9_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_9_variance_path = dir_prefix + std::string("batch_normalization_9_variance.bin");
-void* batch_normalization_9_variance = readTrainedWeights(batch_normalization_9_variance_path.c_str(), 0,1,256,1,1);
-std::string depthwise_conv2d_5_w_path = dir_prefix + std::string("depthwise_conv2d_5_w.bin");
-void* depthwise_conv2d_5_w = readTrainedWeights(depthwise_conv2d_5_w_path.c_str(), 0,256,1,3,3);
-std::string batch_normalization_10_gamma_path = dir_prefix + std::string("batch_normalization_10_gamma.bin");
-void* batch_normalization_10_gamma = readTrainedWeights(batch_normalization_10_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_10_beta_path = dir_prefix + std::string("batch_normalization_10_beta.bin");
-void* batch_normalization_10_beta = readTrainedWeights(batch_normalization_10_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_10_mean_path = dir_prefix + std::string("batch_normalization_10_mean.bin");
-void* batch_normalization_10_mean = readTrainedWeights(batch_normalization_10_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_10_variance_path = dir_prefix + std::string("batch_normalization_10_variance.bin");
-void* batch_normalization_10_variance = readTrainedWeights(batch_normalization_10_variance_path.c_str(), 0,1,256,1,1);
-std::string conv2d_6_w_path = dir_prefix + std::string("conv2d_6_w.bin");
-void* conv2d_6_w = readTrainedWeights(conv2d_6_w_path.c_str(), 0,256,256,1,1);
-std::string batch_normalization_11_gamma_path = dir_prefix + std::string("batch_normalization_11_gamma.bin");
-void* batch_normalization_11_gamma = readTrainedWeights(batch_normalization_11_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_11_beta_path = dir_prefix + std::string("batch_normalization_11_beta.bin");
-void* batch_normalization_11_beta = readTrainedWeights(batch_normalization_11_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_11_mean_path = dir_prefix + std::string("batch_normalization_11_mean.bin");
-void* batch_normalization_11_mean = readTrainedWeights(batch_normalization_11_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_11_variance_path = dir_prefix + std::string("batch_normalization_11_variance.bin");
-void* batch_normalization_11_variance = readTrainedWeights(batch_normalization_11_variance_path.c_str(), 0,1,256,1,1);
-std::string depthwise_conv2d_6_w_path = dir_prefix + std::string("depthwise_conv2d_6_w.bin");
-void* depthwise_conv2d_6_w = readTrainedWeights(depthwise_conv2d_6_w_path.c_str(), 0,256,1,3,3);
-std::string batch_normalization_12_gamma_path = dir_prefix + std::string("batch_normalization_12_gamma.bin");
-void* batch_normalization_12_gamma = readTrainedWeights(batch_normalization_12_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_12_beta_path = dir_prefix + std::string("batch_normalization_12_beta.bin");
-void* batch_normalization_12_beta = readTrainedWeights(batch_normalization_12_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_12_mean_path = dir_prefix + std::string("batch_normalization_12_mean.bin");
-void* batch_normalization_12_mean = readTrainedWeights(batch_normalization_12_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_12_variance_path = dir_prefix + std::string("batch_normalization_12_variance.bin");
-void* batch_normalization_12_variance = readTrainedWeights(batch_normalization_12_variance_path.c_str(), 0,1,256,1,1);
-std::string conv2d_7_w_path = dir_prefix + std::string("conv2d_7_w.bin");
-void* conv2d_7_w = readTrainedWeights(conv2d_7_w_path.c_str(), 0,512,256,1,1);
-std::string batch_normalization_13_gamma_path = dir_prefix + std::string("batch_normalization_13_gamma.bin");
-void* batch_normalization_13_gamma = readTrainedWeights(batch_normalization_13_gamma_path.c_str(), 0,1,512,1,1);
-std::string batch_normalization_13_beta_path = dir_prefix + std::string("batch_normalization_13_beta.bin");
-void* batch_normalization_13_beta = readTrainedWeights(batch_normalization_13_beta_path.c_str(), 0,1,512,1,1);
-std::string batch_normalization_13_mean_path = dir_prefix + std::string("batch_normalization_13_mean.bin");
-void* batch_normalization_13_mean = readTrainedWeights(batch_normalization_13_mean_path.c_str(), 0,1,512,1,1);
-std::string batch_normalization_13_variance_path = dir_prefix + std::string("batch_normalization_13_variance.bin");
-void* batch_normalization_13_variance = readTrainedWeights(batch_normalization_13_variance_path.c_str(), 0,1,512,1,1);
-std::string dense_1_w_path = dir_prefix + std::string("dense_1_w.bin");
-void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,2048,10);
-std::string dense_1_b_path = dir_prefix + std::string("dense_1_b.bin");
-void* dense_1_b = readTrainedWeights(dense_1_b_path.c_str(), 0,1,10,1,1);
-void* input = readTrainedWeights(input_path.c_str(), 0,10000,3,32,32);
-uint8_t* labels = readLabels(labels_path.c_str(),10000);
-
-__visc__init();
-RootIn* args = static_cast<RootIn*>(malloc(sizeof(RootIn)));
-
-args->input = input;
-args->input_bytes = 0;
-args->conv2d_1_w = conv2d_1_w;
-args->conv2d_1_w_bytes = 0;
-args->batch_normalization_1_gamma = batch_normalization_1_gamma;
-args->batch_normalization_1_gamma_bytes = 0;
-args->batch_normalization_1_beta = batch_normalization_1_beta;
-args->batch_normalization_1_beta_bytes = 0;
-args->batch_normalization_1_mean = batch_normalization_1_mean;
-args->batch_normalization_1_mean_bytes = 0;
-args->batch_normalization_1_variance = batch_normalization_1_variance;
-args->batch_normalization_1_variance_bytes = 0;
-args->depthwise_conv2d_1_w = depthwise_conv2d_1_w;
-args->depthwise_conv2d_1_w_bytes = 0;
-args->batch_normalization_2_gamma = batch_normalization_2_gamma;
-args->batch_normalization_2_gamma_bytes = 0;
-args->batch_normalization_2_beta = batch_normalization_2_beta;
-args->batch_normalization_2_beta_bytes = 0;
-args->batch_normalization_2_mean = batch_normalization_2_mean;
-args->batch_normalization_2_mean_bytes = 0;
-args->batch_normalization_2_variance = batch_normalization_2_variance;
-args->batch_normalization_2_variance_bytes = 0;
-args->conv2d_2_w = conv2d_2_w;
-args->conv2d_2_w_bytes = 0;
-args->batch_normalization_3_gamma = batch_normalization_3_gamma;
-args->batch_normalization_3_gamma_bytes = 0;
-args->batch_normalization_3_beta = batch_normalization_3_beta;
-args->batch_normalization_3_beta_bytes = 0;
-args->batch_normalization_3_mean = batch_normalization_3_mean;
-args->batch_normalization_3_mean_bytes = 0;
-args->batch_normalization_3_variance = batch_normalization_3_variance;
-args->batch_normalization_3_variance_bytes = 0;
-args->depthwise_conv2d_2_w = depthwise_conv2d_2_w;
-args->depthwise_conv2d_2_w_bytes = 0;
-args->batch_normalization_4_gamma = batch_normalization_4_gamma;
-args->batch_normalization_4_gamma_bytes = 0;
-args->batch_normalization_4_beta = batch_normalization_4_beta;
-args->batch_normalization_4_beta_bytes = 0;
-args->batch_normalization_4_mean = batch_normalization_4_mean;
-args->batch_normalization_4_mean_bytes = 0;
-args->batch_normalization_4_variance = batch_normalization_4_variance;
-args->batch_normalization_4_variance_bytes = 0;
-args->conv2d_3_w = conv2d_3_w;
-args->conv2d_3_w_bytes = 0;
-args->batch_normalization_5_gamma = batch_normalization_5_gamma;
-args->batch_normalization_5_gamma_bytes = 0;
-args->batch_normalization_5_beta = batch_normalization_5_beta;
-args->batch_normalization_5_beta_bytes = 0;
-args->batch_normalization_5_mean = batch_normalization_5_mean;
-args->batch_normalization_5_mean_bytes = 0;
-args->batch_normalization_5_variance = batch_normalization_5_variance;
-args->batch_normalization_5_variance_bytes = 0;
-args->depthwise_conv2d_3_w = depthwise_conv2d_3_w;
-args->depthwise_conv2d_3_w_bytes = 0;
-args->batch_normalization_6_gamma = batch_normalization_6_gamma;
-args->batch_normalization_6_gamma_bytes = 0;
-args->batch_normalization_6_beta = batch_normalization_6_beta;
-args->batch_normalization_6_beta_bytes = 0;
-args->batch_normalization_6_mean = batch_normalization_6_mean;
-args->batch_normalization_6_mean_bytes = 0;
-args->batch_normalization_6_variance = batch_normalization_6_variance;
-args->batch_normalization_6_variance_bytes = 0;
-args->conv2d_4_w = conv2d_4_w;
-args->conv2d_4_w_bytes = 0;
-args->batch_normalization_7_gamma = batch_normalization_7_gamma;
-args->batch_normalization_7_gamma_bytes = 0;
-args->batch_normalization_7_beta = batch_normalization_7_beta;
-args->batch_normalization_7_beta_bytes = 0;
-args->batch_normalization_7_mean = batch_normalization_7_mean;
-args->batch_normalization_7_mean_bytes = 0;
-args->batch_normalization_7_variance = batch_normalization_7_variance;
-args->batch_normalization_7_variance_bytes = 0;
-args->depthwise_conv2d_4_w = depthwise_conv2d_4_w;
-args->depthwise_conv2d_4_w_bytes = 0;
-args->batch_normalization_8_gamma = batch_normalization_8_gamma;
-args->batch_normalization_8_gamma_bytes = 0;
-args->batch_normalization_8_beta = batch_normalization_8_beta;
-args->batch_normalization_8_beta_bytes = 0;
-args->batch_normalization_8_mean = batch_normalization_8_mean;
-args->batch_normalization_8_mean_bytes = 0;
-args->batch_normalization_8_variance = batch_normalization_8_variance;
-args->batch_normalization_8_variance_bytes = 0;
-args->conv2d_5_w = conv2d_5_w;
-args->conv2d_5_w_bytes = 0;
-args->batch_normalization_9_gamma = batch_normalization_9_gamma;
-args->batch_normalization_9_gamma_bytes = 0;
-args->batch_normalization_9_beta = batch_normalization_9_beta;
-args->batch_normalization_9_beta_bytes = 0;
-args->batch_normalization_9_mean = batch_normalization_9_mean;
-args->batch_normalization_9_mean_bytes = 0;
-args->batch_normalization_9_variance = batch_normalization_9_variance;
-args->batch_normalization_9_variance_bytes = 0;
-args->depthwise_conv2d_5_w = depthwise_conv2d_5_w;
-args->depthwise_conv2d_5_w_bytes = 0;
-args->batch_normalization_10_gamma = batch_normalization_10_gamma;
-args->batch_normalization_10_gamma_bytes = 0;
-args->batch_normalization_10_beta = batch_normalization_10_beta;
-args->batch_normalization_10_beta_bytes = 0;
-args->batch_normalization_10_mean = batch_normalization_10_mean;
-args->batch_normalization_10_mean_bytes = 0;
-args->batch_normalization_10_variance = batch_normalization_10_variance;
-args->batch_normalization_10_variance_bytes = 0;
-args->conv2d_6_w = conv2d_6_w;
-args->conv2d_6_w_bytes = 0;
-args->batch_normalization_11_gamma = batch_normalization_11_gamma;
-args->batch_normalization_11_gamma_bytes = 0;
-args->batch_normalization_11_beta = batch_normalization_11_beta;
-args->batch_normalization_11_beta_bytes = 0;
-args->batch_normalization_11_mean = batch_normalization_11_mean;
-args->batch_normalization_11_mean_bytes = 0;
-args->batch_normalization_11_variance = batch_normalization_11_variance;
-args->batch_normalization_11_variance_bytes = 0;
-args->depthwise_conv2d_6_w = depthwise_conv2d_6_w;
-args->depthwise_conv2d_6_w_bytes = 0;
-args->batch_normalization_12_gamma = batch_normalization_12_gamma;
-args->batch_normalization_12_gamma_bytes = 0;
-args->batch_normalization_12_beta = batch_normalization_12_beta;
-args->batch_normalization_12_beta_bytes = 0;
-args->batch_normalization_12_mean = batch_normalization_12_mean;
-args->batch_normalization_12_mean_bytes = 0;
-args->batch_normalization_12_variance = batch_normalization_12_variance;
-args->batch_normalization_12_variance_bytes = 0;
-args->conv2d_7_w = conv2d_7_w;
-args->conv2d_7_w_bytes = 0;
-args->batch_normalization_13_gamma = batch_normalization_13_gamma;
-args->batch_normalization_13_gamma_bytes = 0;
-args->batch_normalization_13_beta = batch_normalization_13_beta;
-args->batch_normalization_13_beta_bytes = 0;
-args->batch_normalization_13_mean = batch_normalization_13_mean;
-args->batch_normalization_13_mean_bytes = 0;
-args->batch_normalization_13_variance = batch_normalization_13_variance;
-args->batch_normalization_13_variance_bytes = 0;
-args->dense_1_w = dense_1_w;
-args->dense_1_w_bytes = 0;
-args->dense_1_b = dense_1_b;
-args->dense_1_b_bytes = 0;
-
-void* dfg = __visc__launch(0, root, (void*) args);
-
-__visc__wait(dfg);
-
-void *result = static_cast<RootIn*>(args)->input;
-hpvm_request_tensor(result, 0);
-
-__visc__cleanup();
- computeAccuracy2(labels, 10000, result);
-return 0;
-
-}
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_10_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_10_beta.bin
deleted file mode 100644
index 5d9a0d95865637cfb783fb9a56d3ff2ecb57e868..0000000000000000000000000000000000000000
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_10_gamma.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_10_gamma.bin
deleted file mode 100644
index 71147ba51b53f9b5f8ed84d3e12b3f60d04e88f0..0000000000000000000000000000000000000000
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_10_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_10_mean.bin
deleted file mode 100644
index f75ef27a6bde8cf45607b0e7957603ad5c767928..0000000000000000000000000000000000000000
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_10_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_10_variance.bin
deleted file mode 100644
index cdbb02d6dcc67a983c949224e5ef2356cbed70ec..0000000000000000000000000000000000000000
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_11_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_11_beta.bin
deleted file mode 100644
index a6d770acd50df688be127899d5ebc76a6b660108..0000000000000000000000000000000000000000
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_11_gamma.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_11_gamma.bin
deleted file mode 100644
index 7d2add83b878940a6e83ff33ac8328b08218b036..0000000000000000000000000000000000000000
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_11_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_11_mean.bin
deleted file mode 100644
index 481fa2d212a171377d79b38765b42481939abd0f..0000000000000000000000000000000000000000
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_11_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_11_variance.bin
deleted file mode 100644
index 99b00e0a82730dbf49cc6112379b6106b3538f24..0000000000000000000000000000000000000000
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_beta.bin
deleted file mode 100644
index 05d61c8e00f196b83dde7de794cc9feff2929582..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_beta.bin
+++ /dev/null
@@ -1,2 +0,0 @@
-êâ®>@Hx>„jb¾Çå>:Ù*>YR¡>nÍ>ù}u?ýæ>¤ÌB?|¾bç&?ÇO?e=”?¿‹¸¾f'e¾8ƒ¸½è‹Î;Éï:?Ó
-‹?ˆþ„>½»>ŸÞ>î‚?˜5A?|6žàÒ>²•Ý¼Þ>?Ä1?nŸ¾u‡‚>
\ No newline at end of file
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_gamma.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_gamma.bin
deleted file mode 100644
index 1aaaeaa110d8b9eb8108a1546302f8d5c1c12c35..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_gamma.bin
+++ /dev/null
@@ -1,2 +0,0 @@
-³]ƒ?Ç/?®0€?]…o?ƒ?ߌ?Vň?`Z?Gk„?±*`?žÐƒ?pÈ~?
*?+g ?4
-u?Òü?Qƒ?|?š O??ä?K{?^5Œ?ÃÜ‚?£ ?…ØA?žTr?1 y?÷€?!56?&ñƒ?HWv?§^‚?
\ No newline at end of file
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_mean.bin
deleted file mode 100644
index ffcd3adfeac9b601872fa59caa42601fdc10494c..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_mean.bin
+++ /dev/null
@@ -1 +0,0 @@
-ˆG¢¹$ =ã®Ý;9Oü¼ø-'<p;K<
à»Þâ€;žcé¼K!¼“¿œ<õön¼M9 ;¬…;’½î3ì<¯Á ;¨`…<|¾¼þæ:¼;ÿ%=÷»L¶Z»)z·»ªfºS:Œ<j*>»¾M<¨u» û ;%;þ;ñ&J:
\ No newline at end of file
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_variance.bin
deleted file mode 100644
index f29dc5a9db7e4fe9783917749bd151ce80e40702..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_1_variance.bin
+++ /dev/null
@@ -1 +0,0 @@
-ÃÅn@éA²£š?ä +@ "@9ÛÞ@áÀ(@•¹÷>Ò¢Á@ƒ'E@)¡@øˆ+@œZž>«Ç?A?¤A˜x°A0ªª?®¯#AÿΕ@«Vì>~ÑÅAg«“@VúAÿ>;j @š”@j¯ø?.AB¾>œê;@ø#û?Q ~@
\ No newline at end of file
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_2_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_2_beta.bin
deleted file mode 100644
index ba12532332cec1d6ee20d16d04be81575a8f0802..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_2_beta.bin
+++ /dev/null
@@ -1 +0,0 @@
-N ?¶k©¾¬r>{_?kÙy¾ R?fÀ?ä%Q?“k¾åœ?—õ^½g o?=9L>A†?ím½Ôm ¿†Ç½R?²¾íO‡?àhv?ìt4¾ÙN?cá~?i«Ÿ?¹[ ?•ï¾<M_ >Êõö¾>ðn½rÞ¾? Ž?¼êªE=
\ No newline at end of file
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_2_gamma.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_2_gamma.bin
deleted file mode 100644
index bf0dd075d19280dfcda711fd95eeab6fb429b8f5..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_2_gamma.bin
+++ /dev/null
@@ -1 +0,0 @@
-L¾ö>üiQ?-)]?!0?Lw_?`Ë…?ö%4?sÚ¢?²È7?œé`?Ò¿b?¬Y?hv?MC @\ÞY?ñ8P?”Ü\?»QI? ë8?ʤ‘?Ëîl?`¥&?,S?&›?wxr?Ãl_?@8l?k<,?6Ä…?Y={?YjC?2L>?
\ No newline at end of file
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_2_mean.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_2_mean.bin
deleted file mode 100644
index faec424f63fab99e4ba00101a005c1b84cb2f8f3..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_2_mean.bin
+++ /dev/null
@@ -1,2 +0,0 @@
-’D´¿h J¿úVN¿ŠÊ>?Ú%8¿¶œf?U_C¾]º¤½†Ã?çv=Ü"¾Ï6¾g½&¾òß[>`"¿0Õ8>•¿Fô¦¾i³?Z?=鯿‰\TÀ
5[?&Ñ6>Ÿÿ.¿ýkn¾Ú4•>p%5¿Î(>" ×>Ù
- ¿p²M>
\ No newline at end of file
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_2_variance.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_2_variance.bin
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diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_3_beta.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_3_beta.bin
deleted file mode 100644
index 0a7e5127f93e4f3e77893c02209dd34f92fcde00..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_3_beta.bin
+++ /dev/null
@@ -1,2 +0,0 @@
-ùEͽý¨½õž9¾pÊ>Ûàÿ½›³>Ÿÿ²>£f>’ë¾Ó‹Ý¹"å>¼½–¾
-ð~¾½¼¾Üöý==Á‹=ä!>D >°©>’çn>£ç;(+Ö=Ÿ‡?Üÿl? m¾$0`>¥¡<¸Ïy?Vál?‚ ?(Ò'½Y ?o>uƒ@> €q>…ö>ë}î>fÓW?K>¿»
?) ?F¿¾Ÿ¯Y¾Ý¯ ?·°—>YdL¾–ZC?þÕ÷=?pUV?þV]>›Â©¾å=9{/>É’Ž½«U>¸ŠÖ½*Ï&>1Í;Mj1¾B‡A=™¾ü½æ…)?! 3?
\ No newline at end of file
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_3_gamma.bin b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/batch_normalization_3_gamma.bin
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-conv
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-activation
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-batchnorm
-activation
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-batchnorm
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-conv
-batchnorm
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-depthwise_conv
-batchnorm
-activation
-conv
-batchnorm
-activation
-depthwise_conv
-batchnorm
-activation
-conv
-batchnorm
-activation
-pool
-dense add
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/layers.txt b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/layers.txt
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index a9415755180a7ebdceb89b7e3e6d6cee258b18c4..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/layers.txt
+++ /dev/null
@@ -1,41 +0,0 @@
-Conv1,10000,3,32,32,32,3,3,3
-#tensorBatchNorm1
-#tensorRelu1
-#tensorDepthwiseConv1
-#tensorBatchNorm2
-#tensorRelu2
-Conv2,10000,32,32,32,64,32,1,1
-#tensorBatchNorm3
-#tensorRelu3
-#tensorDepthwiseConv2
-#tensorBatchNorm4
-#tensorRelu4
-Conv3,10000,64,16,16,128,64,1,1
-#tensorBatchNorm5
-#tensorRelu5
-#tensorDepthwiseConv3
-#tensorBatchNorm6
-#tensorRelu6
-Conv4,10000,128,16,16,128,128,1,1
-#tensorBatchNorm7
-#tensorRelu7
-#tensorDepthwiseConv4
-#tensorBatchNorm8
-#tensorRelu8
-Conv5,10000,128,8,8,256,128,1,1
-#tensorBatchNorm9
-#tensorRelu9
-#tensorDepthwiseConv5
-#tensorBatchNorm10
-#tensorRelu10
-Conv6,10000,256,8,8,256,256,1,1
-#tensorBatchNorm11
-#tensorRelu11
-#tensorDepthwiseConv6
-#tensorBatchNorm12
-#tensorRelu12
-Conv7,10000,256,4,4,512,256,1,1
-#tensorBatchNorm13
-#tensorRelu13
-#tensorPooling1
-FC1,10000,2048,2048,10
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/promise_src.cc b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/promise_src.cc
deleted file mode 100644
index c5fd3606da51281bc2c583e98f024bd2f54f837b..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/promise_src.cc
+++ /dev/null
@@ -1,238 +0,0 @@
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <unistd.h>
-#include <fcntl.h>
-#include <sys/types.h>
-#include <sys/stat.h>
-#include <string.h>
-#include "../../../tensor_runtime/include/tensor_runtime.h"
-#include "../../include/utils.h"
-
-int main(){
-
-llvm_hpvm_initTensorRt(0);
-
-int total_runs = 100;
-for (int i = 0 ; i < total_runs; i++){
-
-
-startMemTracking();
-
-int test_input_size = 10000;
-int batch_size = 10000;
-int batch_count = test_input_size / batch_size;
-float final_accuracy = 0.0;
-
-for(int i = 0; i < batch_count; i++){
-
-
-
-std::string dir_prefix = std::string("data/mobilenet_shallow_nathan/");
-std::string input_path = dir_prefix + std::string("input.bin");
-std::string labels_path = dir_prefix + std::string("labels.bin");
-std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
-void* conv2d_1_w = readTrainedWeights(conv2d_1_w_path.c_str(), 0,32,3,3,3);
-std::string batch_normalization_1_gamma_path = dir_prefix + std::string("batch_normalization_1_gamma.bin");
-void* batch_normalization_1_gamma = readTrainedWeights(batch_normalization_1_gamma_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_1_beta_path = dir_prefix + std::string("batch_normalization_1_beta.bin");
-void* batch_normalization_1_beta = readTrainedWeights(batch_normalization_1_beta_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_1_mean_path = dir_prefix + std::string("batch_normalization_1_mean.bin");
-void* batch_normalization_1_mean = readTrainedWeights(batch_normalization_1_mean_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_1_variance_path = dir_prefix + std::string("batch_normalization_1_variance.bin");
-void* batch_normalization_1_variance = readTrainedWeights(batch_normalization_1_variance_path.c_str(), 0,1,32,1,1);
-std::string depthwise_conv2d_1_w_path = dir_prefix + std::string("depthwise_conv2d_1_w.bin");
-void* depthwise_conv2d_1_w = readTrainedWeights(depthwise_conv2d_1_w_path.c_str(), 0,32,1,3,3);
-std::string batch_normalization_2_gamma_path = dir_prefix + std::string("batch_normalization_2_gamma.bin");
-void* batch_normalization_2_gamma = readTrainedWeights(batch_normalization_2_gamma_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_2_beta_path = dir_prefix + std::string("batch_normalization_2_beta.bin");
-void* batch_normalization_2_beta = readTrainedWeights(batch_normalization_2_beta_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_2_mean_path = dir_prefix + std::string("batch_normalization_2_mean.bin");
-void* batch_normalization_2_mean = readTrainedWeights(batch_normalization_2_mean_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_2_variance_path = dir_prefix + std::string("batch_normalization_2_variance.bin");
-void* batch_normalization_2_variance = readTrainedWeights(batch_normalization_2_variance_path.c_str(), 0,1,32,1,1);
-std::string conv2d_2_w_path = dir_prefix + std::string("conv2d_2_w.bin");
-void* conv2d_2_w = readTrainedWeights(conv2d_2_w_path.c_str(), 0,64,32,1,1);
-std::string batch_normalization_3_gamma_path = dir_prefix + std::string("batch_normalization_3_gamma.bin");
-void* batch_normalization_3_gamma = readTrainedWeights(batch_normalization_3_gamma_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_3_beta_path = dir_prefix + std::string("batch_normalization_3_beta.bin");
-void* batch_normalization_3_beta = readTrainedWeights(batch_normalization_3_beta_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_3_mean_path = dir_prefix + std::string("batch_normalization_3_mean.bin");
-void* batch_normalization_3_mean = readTrainedWeights(batch_normalization_3_mean_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_3_variance_path = dir_prefix + std::string("batch_normalization_3_variance.bin");
-void* batch_normalization_3_variance = readTrainedWeights(batch_normalization_3_variance_path.c_str(), 0,1,64,1,1);
-std::string depthwise_conv2d_2_w_path = dir_prefix + std::string("depthwise_conv2d_2_w.bin");
-void* depthwise_conv2d_2_w = readTrainedWeights(depthwise_conv2d_2_w_path.c_str(), 0,64,1,3,3);
-std::string batch_normalization_4_gamma_path = dir_prefix + std::string("batch_normalization_4_gamma.bin");
-void* batch_normalization_4_gamma = readTrainedWeights(batch_normalization_4_gamma_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_4_beta_path = dir_prefix + std::string("batch_normalization_4_beta.bin");
-void* batch_normalization_4_beta = readTrainedWeights(batch_normalization_4_beta_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_4_mean_path = dir_prefix + std::string("batch_normalization_4_mean.bin");
-void* batch_normalization_4_mean = readTrainedWeights(batch_normalization_4_mean_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_4_variance_path = dir_prefix + std::string("batch_normalization_4_variance.bin");
-void* batch_normalization_4_variance = readTrainedWeights(batch_normalization_4_variance_path.c_str(), 0,1,64,1,1);
-std::string conv2d_3_w_path = dir_prefix + std::string("conv2d_3_w.bin");
-void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,128,64,1,1);
-std::string batch_normalization_5_gamma_path = dir_prefix + std::string("batch_normalization_5_gamma.bin");
-void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_5_beta_path = dir_prefix + std::string("batch_normalization_5_beta.bin");
-void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_5_mean_path = dir_prefix + std::string("batch_normalization_5_mean.bin");
-void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_5_variance_path = dir_prefix + std::string("batch_normalization_5_variance.bin");
-void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,128,1,1);
-std::string depthwise_conv2d_3_w_path = dir_prefix + std::string("depthwise_conv2d_3_w.bin");
-void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,128,1,3,3);
-std::string batch_normalization_6_gamma_path = dir_prefix + std::string("batch_normalization_6_gamma.bin");
-void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_6_beta_path = dir_prefix + std::string("batch_normalization_6_beta.bin");
-void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_6_mean_path = dir_prefix + std::string("batch_normalization_6_mean.bin");
-void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_6_variance_path = dir_prefix + std::string("batch_normalization_6_variance.bin");
-void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,128,1,1);
-std::string conv2d_4_w_path = dir_prefix + std::string("conv2d_4_w.bin");
-void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,128,1,1);
-std::string batch_normalization_7_gamma_path = dir_prefix + std::string("batch_normalization_7_gamma.bin");
-void* batch_normalization_7_gamma = readTrainedWeights(batch_normalization_7_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_7_beta_path = dir_prefix + std::string("batch_normalization_7_beta.bin");
-void* batch_normalization_7_beta = readTrainedWeights(batch_normalization_7_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_7_mean_path = dir_prefix + std::string("batch_normalization_7_mean.bin");
-void* batch_normalization_7_mean = readTrainedWeights(batch_normalization_7_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_7_variance_path = dir_prefix + std::string("batch_normalization_7_variance.bin");
-void* batch_normalization_7_variance = readTrainedWeights(batch_normalization_7_variance_path.c_str(), 0,1,128,1,1);
-std::string depthwise_conv2d_4_w_path = dir_prefix + std::string("depthwise_conv2d_4_w.bin");
-void* depthwise_conv2d_4_w = readTrainedWeights(depthwise_conv2d_4_w_path.c_str(), 0,128,1,3,3);
-std::string batch_normalization_8_gamma_path = dir_prefix + std::string("batch_normalization_8_gamma.bin");
-void* batch_normalization_8_gamma = readTrainedWeights(batch_normalization_8_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_8_beta_path = dir_prefix + std::string("batch_normalization_8_beta.bin");
-void* batch_normalization_8_beta = readTrainedWeights(batch_normalization_8_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_8_mean_path = dir_prefix + std::string("batch_normalization_8_mean.bin");
-void* batch_normalization_8_mean = readTrainedWeights(batch_normalization_8_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_8_variance_path = dir_prefix + std::string("batch_normalization_8_variance.bin");
-void* batch_normalization_8_variance = readTrainedWeights(batch_normalization_8_variance_path.c_str(), 0,1,128,1,1);
-std::string conv2d_5_w_path = dir_prefix + std::string("conv2d_5_w.bin");
-void* conv2d_5_w = readTrainedWeights(conv2d_5_w_path.c_str(), 0,256,128,1,1);
-std::string batch_normalization_9_gamma_path = dir_prefix + std::string("batch_normalization_9_gamma.bin");
-void* batch_normalization_9_gamma = readTrainedWeights(batch_normalization_9_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_9_beta_path = dir_prefix + std::string("batch_normalization_9_beta.bin");
-void* batch_normalization_9_beta = readTrainedWeights(batch_normalization_9_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_9_mean_path = dir_prefix + std::string("batch_normalization_9_mean.bin");
-void* batch_normalization_9_mean = readTrainedWeights(batch_normalization_9_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_9_variance_path = dir_prefix + std::string("batch_normalization_9_variance.bin");
-void* batch_normalization_9_variance = readTrainedWeights(batch_normalization_9_variance_path.c_str(), 0,1,256,1,1);
-std::string depthwise_conv2d_5_w_path = dir_prefix + std::string("depthwise_conv2d_5_w.bin");
-void* depthwise_conv2d_5_w = readTrainedWeights(depthwise_conv2d_5_w_path.c_str(), 0,256,1,3,3);
-std::string batch_normalization_10_gamma_path = dir_prefix + std::string("batch_normalization_10_gamma.bin");
-void* batch_normalization_10_gamma = readTrainedWeights(batch_normalization_10_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_10_beta_path = dir_prefix + std::string("batch_normalization_10_beta.bin");
-void* batch_normalization_10_beta = readTrainedWeights(batch_normalization_10_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_10_mean_path = dir_prefix + std::string("batch_normalization_10_mean.bin");
-void* batch_normalization_10_mean = readTrainedWeights(batch_normalization_10_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_10_variance_path = dir_prefix + std::string("batch_normalization_10_variance.bin");
-void* batch_normalization_10_variance = readTrainedWeights(batch_normalization_10_variance_path.c_str(), 0,1,256,1,1);
-std::string conv2d_6_w_path = dir_prefix + std::string("conv2d_6_w.bin");
-void* conv2d_6_w = readTrainedWeights(conv2d_6_w_path.c_str(), 0,256,256,1,1);
-std::string batch_normalization_11_gamma_path = dir_prefix + std::string("batch_normalization_11_gamma.bin");
-void* batch_normalization_11_gamma = readTrainedWeights(batch_normalization_11_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_11_beta_path = dir_prefix + std::string("batch_normalization_11_beta.bin");
-void* batch_normalization_11_beta = readTrainedWeights(batch_normalization_11_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_11_mean_path = dir_prefix + std::string("batch_normalization_11_mean.bin");
-void* batch_normalization_11_mean = readTrainedWeights(batch_normalization_11_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_11_variance_path = dir_prefix + std::string("batch_normalization_11_variance.bin");
-void* batch_normalization_11_variance = readTrainedWeights(batch_normalization_11_variance_path.c_str(), 0,1,256,1,1);
-std::string depthwise_conv2d_6_w_path = dir_prefix + std::string("depthwise_conv2d_6_w.bin");
-void* depthwise_conv2d_6_w = readTrainedWeights(depthwise_conv2d_6_w_path.c_str(), 0,256,1,3,3);
-std::string batch_normalization_12_gamma_path = dir_prefix + std::string("batch_normalization_12_gamma.bin");
-void* batch_normalization_12_gamma = readTrainedWeights(batch_normalization_12_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_12_beta_path = dir_prefix + std::string("batch_normalization_12_beta.bin");
-void* batch_normalization_12_beta = readTrainedWeights(batch_normalization_12_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_12_mean_path = dir_prefix + std::string("batch_normalization_12_mean.bin");
-void* batch_normalization_12_mean = readTrainedWeights(batch_normalization_12_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_12_variance_path = dir_prefix + std::string("batch_normalization_12_variance.bin");
-void* batch_normalization_12_variance = readTrainedWeights(batch_normalization_12_variance_path.c_str(), 0,1,256,1,1);
-std::string conv2d_7_w_path = dir_prefix + std::string("conv2d_7_w.bin");
-void* conv2d_7_w = readTrainedWeights(conv2d_7_w_path.c_str(), 0,512,256,1,1);
-std::string batch_normalization_13_gamma_path = dir_prefix + std::string("batch_normalization_13_gamma.bin");
-void* batch_normalization_13_gamma = readTrainedWeights(batch_normalization_13_gamma_path.c_str(), 0,1,512,1,1);
-std::string batch_normalization_13_beta_path = dir_prefix + std::string("batch_normalization_13_beta.bin");
-void* batch_normalization_13_beta = readTrainedWeights(batch_normalization_13_beta_path.c_str(), 0,1,512,1,1);
-std::string batch_normalization_13_mean_path = dir_prefix + std::string("batch_normalization_13_mean.bin");
-void* batch_normalization_13_mean = readTrainedWeights(batch_normalization_13_mean_path.c_str(), 0,1,512,1,1);
-std::string batch_normalization_13_variance_path = dir_prefix + std::string("batch_normalization_13_variance.bin");
-void* batch_normalization_13_variance = readTrainedWeights(batch_normalization_13_variance_path.c_str(), 0,1,512,1,1);
-std::string dense_1_w_path = dir_prefix + std::string("dense_1_w.bin");
-void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,2048,10);
-std::string dense_1_b_path = dir_prefix + std::string("dense_1_b.bin");
-void* dense_1_b = readTrainedWeights(dense_1_b_path.c_str(), 0,1,10,1,1);
-
-
-int start = i * batch_size;
-int end = (i + 1) * batch_size;
-
-void* input = readInputBatch(input_path.c_str(),0,start,end,3,32,32);
-
-void* var_0 = ConvLayer_PROMISE(input, -1.9892114, 2.126797, conv2d_1_w, -1.5164621164798737, 1.6472081774473288, NULL, 0, 0, 1, 1, 1, 1, -1, 0, -1, -9.868980642318725, 10.560956018447879, 9);
-void* var_1 = tensorBatchNorm(var_0, batch_normalization_1_gamma, batch_normalization_1_beta, batch_normalization_1_mean, batch_normalization_1_variance, 0.001);
-void* var_2 = tensorRelu(var_1);
-void* var_3 = tensorConvolution(var_2, depthwise_conv2d_1_w, 1, 1, 1, 1, 1, 32);
-void* var_4 = tensorBatchNorm(var_3, batch_normalization_2_gamma, batch_normalization_2_beta, batch_normalization_2_mean, batch_normalization_2_variance, 0.001);
-void* var_5 = tensorRelu(var_4);
-void* var_6 = ConvLayer_PROMISE(var_5, 0.0, 6.821381127357554, conv2d_2_w, -1.1834390873908995, 1.2731596627235617, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -9.875998497009277, 7.51305247974393, 9);
-void* var_7 = tensorBatchNorm(var_6, batch_normalization_3_gamma, batch_normalization_3_beta, batch_normalization_3_mean, batch_normalization_3_variance, 0.001);
-void* var_8 = tensorRelu(var_7);
-void* var_9 = tensorConvolution(var_8, depthwise_conv2d_2_w, 1, 1, 2, 2, 1, 64);
-void* var_10 = tensorBatchNorm(var_9, batch_normalization_4_gamma, batch_normalization_4_beta, batch_normalization_4_mean, batch_normalization_4_variance, 0.001);
-void* var_11 = tensorRelu(var_10);
-void* var_12 = ConvLayer_PROMISE(var_11, 0.0, 4.826067455768602, conv2d_3_w, -0.599876856982708, 0.6812073457241064, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -5.633289833068848, 5.177892235755925, 9);
-void* var_13 = tensorBatchNorm(var_12, batch_normalization_5_gamma, batch_normalization_5_beta, batch_normalization_5_mean, batch_normalization_5_variance, 0.001);
-void* var_14 = tensorRelu(var_13);
-void* var_15 = tensorConvolution(var_14, depthwise_conv2d_3_w, 1, 1, 1, 1, 1, 128);
-void* var_16 = tensorBatchNorm(var_15, batch_normalization_6_gamma, batch_normalization_6_beta, batch_normalization_6_mean, batch_normalization_6_variance, 0.001);
-void* var_17 = tensorRelu(var_16);
-void* var_18 = ConvLayer_PROMISE(var_17, 0.0, 4.02646304416659, conv2d_4_w, -0.4555967862010002, 0.4942613914608956, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -5.316803941726685, 4.605850250244146, 9);
-void* var_19 = tensorBatchNorm(var_18, batch_normalization_7_gamma, batch_normalization_7_beta, batch_normalization_7_mean, batch_normalization_7_variance, 0.001);
-void* var_20 = tensorRelu(var_19);
-void* var_21 = tensorConvolution(var_20, depthwise_conv2d_4_w, 1, 1, 2, 2, 1, 128);
-void* var_22 = tensorBatchNorm(var_21, batch_normalization_8_gamma, batch_normalization_8_beta, batch_normalization_8_mean, batch_normalization_8_variance, 0.001);
-void* var_23 = tensorRelu(var_22);
-void* var_24 = ConvLayer_PROMISE(var_23, 0.0, 4.532649063110355, conv2d_5_w, -0.35657615590095515, 0.3382165088057521, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -6.1012511816024775, 4.3630500688553, 9);
-void* var_25 = tensorBatchNorm(var_24, batch_normalization_9_gamma, batch_normalization_9_beta, batch_normalization_9_mean, batch_normalization_9_variance, 0.001);
-void* var_26 = tensorRelu(var_25);
-void* var_27 = tensorConvolution(var_26, depthwise_conv2d_5_w, 1, 1, 1, 1, 1, 256);
-void* var_28 = tensorBatchNorm(var_27, batch_normalization_10_gamma, batch_normalization_10_beta, batch_normalization_10_mean, batch_normalization_10_variance, 0.001);
-void* var_29 = tensorRelu(var_28);
-void* var_30 = ConvLayer_PROMISE(var_29, 0.0, 3.9874704387188977, conv2d_6_w, -0.28502783328294756, 0.28604640334844594, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -4.243851703643799, 3.486250406742097, 9);
-void* var_31 = tensorBatchNorm(var_30, batch_normalization_11_gamma, batch_normalization_11_beta, batch_normalization_11_mean, batch_normalization_11_variance, 0.001);
-void* var_32 = tensorRelu(var_31);
-void* var_33 = tensorConvolution(var_32, depthwise_conv2d_6_w, 1, 1, 2, 2, 1, 256);
-void* var_34 = tensorBatchNorm(var_33, batch_normalization_12_gamma, batch_normalization_12_beta, batch_normalization_12_mean, batch_normalization_12_variance, 0.001);
-void* var_35 = tensorRelu(var_34);
-void* var_36 = ConvLayer_PROMISE(var_35, 0.0, 6.563065901756522, conv2d_7_w, -0.18946402323246003, 0.19012390717864017, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -4.938115713119507, 3.538363476753238, 9);
-void* var_37 = tensorBatchNorm(var_36, batch_normalization_13_gamma, batch_normalization_13_beta, batch_normalization_13_mean, batch_normalization_13_variance, 0.001);
-void* var_38 = tensorRelu(var_37);
-void* var_39 = tensorPooling(var_38,1,2,2,0,0,2,2);
-void* var_40 = FCLayer_PROMISE(var_39, 0.0, 1.8908388000727185, dense_1_w, -0.35140394401550296, 0.422872786462307, dense_1_b, -0.23878151, 0.26507422, -1, -14.630816223144532, 27.27252123260504, 9);
-void* var_41 = tensorSoftmax(var_40);
-
-uint8_t* labels = readLabelsBatch(labels_path.c_str(),start,end);
-
-float accuracy = computeAccuracy2(labels, batch_size, var_41);
-final_accuracy += accuracy;
-freeBatchMemory();
-
-}
-
-final_accuracy = final_accuracy / batch_count;
-dumpFinalAccuracy(final_accuracy);
-
-
-}
-
-dumpExecutionAccuracies();
-
-llvm_hpvm_cleanupTensorRt();
-
-return 0;
-
-}
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/src.cc b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/src.cc
deleted file mode 100644
index 6599f7d0ea0be6a76c4154d25b3a7be2c6724115..0000000000000000000000000000000000000000
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/mobilenet_shallow_nathan/src.cc
+++ /dev/null
@@ -1,231 +0,0 @@
-
-#include <stdio.h>
-#include <stdlib.h>
-#include <unistd.h>
-#include <fcntl.h>
-#include <sys/types.h>
-#include <sys/stat.h>
-#include <string.h>
-#include "../../tensor_runtime/include/tensor_runtime.h"
-#include "../include/utils.h"
-
-int main(){
-
-llvm_hpvm_initTensorRt(0);
-
-
-std::string dir_prefix = std::string("data/mobilenet_shallow_nathan/");
-std::string input_path = dir_prefix + std::string("input.bin");
-std::string labels_path = dir_prefix + std::string("labels.bin");
-std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
-void* conv2d_1_w = readTrainedWeights(conv2d_1_w_path.c_str(), 0,32,3,3,3);
-std::string batch_normalization_1_gamma_path = dir_prefix + std::string("batch_normalization_1_gamma.bin");
-void* batch_normalization_1_gamma = readTrainedWeights(batch_normalization_1_gamma_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_1_beta_path = dir_prefix + std::string("batch_normalization_1_beta.bin");
-void* batch_normalization_1_beta = readTrainedWeights(batch_normalization_1_beta_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_1_mean_path = dir_prefix + std::string("batch_normalization_1_mean.bin");
-void* batch_normalization_1_mean = readTrainedWeights(batch_normalization_1_mean_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_1_variance_path = dir_prefix + std::string("batch_normalization_1_variance.bin");
-void* batch_normalization_1_variance = readTrainedWeights(batch_normalization_1_variance_path.c_str(), 0,1,32,1,1);
-std::string depthwise_conv2d_1_w_path = dir_prefix + std::string("depthwise_conv2d_1_w.bin");
-void* depthwise_conv2d_1_w = readTrainedWeights(depthwise_conv2d_1_w_path.c_str(), 0,32,1,3,3);
-std::string batch_normalization_2_gamma_path = dir_prefix + std::string("batch_normalization_2_gamma.bin");
-void* batch_normalization_2_gamma = readTrainedWeights(batch_normalization_2_gamma_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_2_beta_path = dir_prefix + std::string("batch_normalization_2_beta.bin");
-void* batch_normalization_2_beta = readTrainedWeights(batch_normalization_2_beta_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_2_mean_path = dir_prefix + std::string("batch_normalization_2_mean.bin");
-void* batch_normalization_2_mean = readTrainedWeights(batch_normalization_2_mean_path.c_str(), 0,1,32,1,1);
-std::string batch_normalization_2_variance_path = dir_prefix + std::string("batch_normalization_2_variance.bin");
-void* batch_normalization_2_variance = readTrainedWeights(batch_normalization_2_variance_path.c_str(), 0,1,32,1,1);
-std::string conv2d_2_w_path = dir_prefix + std::string("conv2d_2_w.bin");
-void* conv2d_2_w = readTrainedWeights(conv2d_2_w_path.c_str(), 0,64,32,1,1);
-std::string batch_normalization_3_gamma_path = dir_prefix + std::string("batch_normalization_3_gamma.bin");
-void* batch_normalization_3_gamma = readTrainedWeights(batch_normalization_3_gamma_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_3_beta_path = dir_prefix + std::string("batch_normalization_3_beta.bin");
-void* batch_normalization_3_beta = readTrainedWeights(batch_normalization_3_beta_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_3_mean_path = dir_prefix + std::string("batch_normalization_3_mean.bin");
-void* batch_normalization_3_mean = readTrainedWeights(batch_normalization_3_mean_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_3_variance_path = dir_prefix + std::string("batch_normalization_3_variance.bin");
-void* batch_normalization_3_variance = readTrainedWeights(batch_normalization_3_variance_path.c_str(), 0,1,64,1,1);
-std::string depthwise_conv2d_2_w_path = dir_prefix + std::string("depthwise_conv2d_2_w.bin");
-void* depthwise_conv2d_2_w = readTrainedWeights(depthwise_conv2d_2_w_path.c_str(), 0,64,1,3,3);
-std::string batch_normalization_4_gamma_path = dir_prefix + std::string("batch_normalization_4_gamma.bin");
-void* batch_normalization_4_gamma = readTrainedWeights(batch_normalization_4_gamma_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_4_beta_path = dir_prefix + std::string("batch_normalization_4_beta.bin");
-void* batch_normalization_4_beta = readTrainedWeights(batch_normalization_4_beta_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_4_mean_path = dir_prefix + std::string("batch_normalization_4_mean.bin");
-void* batch_normalization_4_mean = readTrainedWeights(batch_normalization_4_mean_path.c_str(), 0,1,64,1,1);
-std::string batch_normalization_4_variance_path = dir_prefix + std::string("batch_normalization_4_variance.bin");
-void* batch_normalization_4_variance = readTrainedWeights(batch_normalization_4_variance_path.c_str(), 0,1,64,1,1);
-std::string conv2d_3_w_path = dir_prefix + std::string("conv2d_3_w.bin");
-void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,128,64,1,1);
-std::string batch_normalization_5_gamma_path = dir_prefix + std::string("batch_normalization_5_gamma.bin");
-void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_5_beta_path = dir_prefix + std::string("batch_normalization_5_beta.bin");
-void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_5_mean_path = dir_prefix + std::string("batch_normalization_5_mean.bin");
-void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_5_variance_path = dir_prefix + std::string("batch_normalization_5_variance.bin");
-void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,128,1,1);
-std::string depthwise_conv2d_3_w_path = dir_prefix + std::string("depthwise_conv2d_3_w.bin");
-void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,128,1,3,3);
-std::string batch_normalization_6_gamma_path = dir_prefix + std::string("batch_normalization_6_gamma.bin");
-void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_6_beta_path = dir_prefix + std::string("batch_normalization_6_beta.bin");
-void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_6_mean_path = dir_prefix + std::string("batch_normalization_6_mean.bin");
-void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_6_variance_path = dir_prefix + std::string("batch_normalization_6_variance.bin");
-void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,128,1,1);
-std::string conv2d_4_w_path = dir_prefix + std::string("conv2d_4_w.bin");
-void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,128,1,1);
-std::string batch_normalization_7_gamma_path = dir_prefix + std::string("batch_normalization_7_gamma.bin");
-void* batch_normalization_7_gamma = readTrainedWeights(batch_normalization_7_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_7_beta_path = dir_prefix + std::string("batch_normalization_7_beta.bin");
-void* batch_normalization_7_beta = readTrainedWeights(batch_normalization_7_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_7_mean_path = dir_prefix + std::string("batch_normalization_7_mean.bin");
-void* batch_normalization_7_mean = readTrainedWeights(batch_normalization_7_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_7_variance_path = dir_prefix + std::string("batch_normalization_7_variance.bin");
-void* batch_normalization_7_variance = readTrainedWeights(batch_normalization_7_variance_path.c_str(), 0,1,128,1,1);
-std::string depthwise_conv2d_4_w_path = dir_prefix + std::string("depthwise_conv2d_4_w.bin");
-void* depthwise_conv2d_4_w = readTrainedWeights(depthwise_conv2d_4_w_path.c_str(), 0,128,1,3,3);
-std::string batch_normalization_8_gamma_path = dir_prefix + std::string("batch_normalization_8_gamma.bin");
-void* batch_normalization_8_gamma = readTrainedWeights(batch_normalization_8_gamma_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_8_beta_path = dir_prefix + std::string("batch_normalization_8_beta.bin");
-void* batch_normalization_8_beta = readTrainedWeights(batch_normalization_8_beta_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_8_mean_path = dir_prefix + std::string("batch_normalization_8_mean.bin");
-void* batch_normalization_8_mean = readTrainedWeights(batch_normalization_8_mean_path.c_str(), 0,1,128,1,1);
-std::string batch_normalization_8_variance_path = dir_prefix + std::string("batch_normalization_8_variance.bin");
-void* batch_normalization_8_variance = readTrainedWeights(batch_normalization_8_variance_path.c_str(), 0,1,128,1,1);
-std::string conv2d_5_w_path = dir_prefix + std::string("conv2d_5_w.bin");
-void* conv2d_5_w = readTrainedWeights(conv2d_5_w_path.c_str(), 0,256,128,1,1);
-std::string batch_normalization_9_gamma_path = dir_prefix + std::string("batch_normalization_9_gamma.bin");
-void* batch_normalization_9_gamma = readTrainedWeights(batch_normalization_9_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_9_beta_path = dir_prefix + std::string("batch_normalization_9_beta.bin");
-void* batch_normalization_9_beta = readTrainedWeights(batch_normalization_9_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_9_mean_path = dir_prefix + std::string("batch_normalization_9_mean.bin");
-void* batch_normalization_9_mean = readTrainedWeights(batch_normalization_9_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_9_variance_path = dir_prefix + std::string("batch_normalization_9_variance.bin");
-void* batch_normalization_9_variance = readTrainedWeights(batch_normalization_9_variance_path.c_str(), 0,1,256,1,1);
-std::string depthwise_conv2d_5_w_path = dir_prefix + std::string("depthwise_conv2d_5_w.bin");
-void* depthwise_conv2d_5_w = readTrainedWeights(depthwise_conv2d_5_w_path.c_str(), 0,256,1,3,3);
-std::string batch_normalization_10_gamma_path = dir_prefix + std::string("batch_normalization_10_gamma.bin");
-void* batch_normalization_10_gamma = readTrainedWeights(batch_normalization_10_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_10_beta_path = dir_prefix + std::string("batch_normalization_10_beta.bin");
-void* batch_normalization_10_beta = readTrainedWeights(batch_normalization_10_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_10_mean_path = dir_prefix + std::string("batch_normalization_10_mean.bin");
-void* batch_normalization_10_mean = readTrainedWeights(batch_normalization_10_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_10_variance_path = dir_prefix + std::string("batch_normalization_10_variance.bin");
-void* batch_normalization_10_variance = readTrainedWeights(batch_normalization_10_variance_path.c_str(), 0,1,256,1,1);
-std::string conv2d_6_w_path = dir_prefix + std::string("conv2d_6_w.bin");
-void* conv2d_6_w = readTrainedWeights(conv2d_6_w_path.c_str(), 0,256,256,1,1);
-std::string batch_normalization_11_gamma_path = dir_prefix + std::string("batch_normalization_11_gamma.bin");
-void* batch_normalization_11_gamma = readTrainedWeights(batch_normalization_11_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_11_beta_path = dir_prefix + std::string("batch_normalization_11_beta.bin");
-void* batch_normalization_11_beta = readTrainedWeights(batch_normalization_11_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_11_mean_path = dir_prefix + std::string("batch_normalization_11_mean.bin");
-void* batch_normalization_11_mean = readTrainedWeights(batch_normalization_11_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_11_variance_path = dir_prefix + std::string("batch_normalization_11_variance.bin");
-void* batch_normalization_11_variance = readTrainedWeights(batch_normalization_11_variance_path.c_str(), 0,1,256,1,1);
-std::string depthwise_conv2d_6_w_path = dir_prefix + std::string("depthwise_conv2d_6_w.bin");
-void* depthwise_conv2d_6_w = readTrainedWeights(depthwise_conv2d_6_w_path.c_str(), 0,256,1,3,3);
-std::string batch_normalization_12_gamma_path = dir_prefix + std::string("batch_normalization_12_gamma.bin");
-void* batch_normalization_12_gamma = readTrainedWeights(batch_normalization_12_gamma_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_12_beta_path = dir_prefix + std::string("batch_normalization_12_beta.bin");
-void* batch_normalization_12_beta = readTrainedWeights(batch_normalization_12_beta_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_12_mean_path = dir_prefix + std::string("batch_normalization_12_mean.bin");
-void* batch_normalization_12_mean = readTrainedWeights(batch_normalization_12_mean_path.c_str(), 0,1,256,1,1);
-std::string batch_normalization_12_variance_path = dir_prefix + std::string("batch_normalization_12_variance.bin");
-void* batch_normalization_12_variance = readTrainedWeights(batch_normalization_12_variance_path.c_str(), 0,1,256,1,1);
-std::string conv2d_7_w_path = dir_prefix + std::string("conv2d_7_w.bin");
-void* conv2d_7_w = readTrainedWeights(conv2d_7_w_path.c_str(), 0,512,256,1,1);
-std::string batch_normalization_13_gamma_path = dir_prefix + std::string("batch_normalization_13_gamma.bin");
-void* batch_normalization_13_gamma = readTrainedWeights(batch_normalization_13_gamma_path.c_str(), 0,1,512,1,1);
-std::string batch_normalization_13_beta_path = dir_prefix + std::string("batch_normalization_13_beta.bin");
-void* batch_normalization_13_beta = readTrainedWeights(batch_normalization_13_beta_path.c_str(), 0,1,512,1,1);
-std::string batch_normalization_13_mean_path = dir_prefix + std::string("batch_normalization_13_mean.bin");
-void* batch_normalization_13_mean = readTrainedWeights(batch_normalization_13_mean_path.c_str(), 0,1,512,1,1);
-std::string batch_normalization_13_variance_path = dir_prefix + std::string("batch_normalization_13_variance.bin");
-void* batch_normalization_13_variance = readTrainedWeights(batch_normalization_13_variance_path.c_str(), 0,1,512,1,1);
-std::string dense_1_w_path = dir_prefix + std::string("dense_1_w.bin");
-void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,2048,10);
-std::string dense_1_b_path = dir_prefix + std::string("dense_1_b.bin");
-void* dense_1_b = readTrainedWeights(dense_1_b_path.c_str(), 0,1,10,1,1);
-
-
-
-startMemTracking();
-
-int test_input_size = 10000;
-int batch_size = 10000;
-int batch_count = test_input_size / batch_size;
-float final_accuracy = 0.0;
-
-for(int i = 0; i < batch_count; i++){
-
-int start = i * batch_size;
-int end = (i + 1) * batch_size;
-
-void* input = readInputBatch(input_path.c_str(),0,start,end,3,32,32);
-
-void* var_0 = tensorConvolution(input, conv2d_1_w, 1, 1, 1, 1, 1, 1);
-void* var_1 = tensorBatchNorm(var_0, batch_normalization_1_gamma, batch_normalization_1_beta, batch_normalization_1_mean, batch_normalization_1_variance, 0.001);
-void* var_2 = tensorRelu(var_1);
-void* var_4 = tensorConvolution(var_2, depthwise_conv2d_1_w, 1, 1, 1, 1, 1, 32);
-void* var_5 = tensorBatchNorm(var_4, batch_normalization_2_gamma, batch_normalization_2_beta, batch_normalization_2_mean, batch_normalization_2_variance, 0.001);
-void* var_6 = tensorRelu(var_5);
-void* var_7 = tensorConvolution(var_6, conv2d_2_w, 0, 0, 1, 1, 1, 1);
-void* var_8 = tensorBatchNorm(var_7, batch_normalization_3_gamma, batch_normalization_3_beta, batch_normalization_3_mean, batch_normalization_3_variance, 0.001);
-void* var_9 = tensorRelu(var_8);
-void* var_11 = tensorConvolution(var_9, depthwise_conv2d_2_w, 1, 1, 2, 2, 1, 64);
-void* var_12 = tensorBatchNorm(var_11, batch_normalization_4_gamma, batch_normalization_4_beta, batch_normalization_4_mean, batch_normalization_4_variance, 0.001);
-void* var_13 = tensorRelu(var_12);
-void* var_14 = tensorConvolution(var_13, conv2d_3_w, 0, 0, 1, 1, 1, 1);
-void* var_15 = tensorBatchNorm(var_14, batch_normalization_5_gamma, batch_normalization_5_beta, batch_normalization_5_mean, batch_normalization_5_variance, 0.001);
-void* var_16 = tensorRelu(var_15);
-void* var_18 = tensorConvolution(var_16, depthwise_conv2d_3_w, 1, 1, 1, 1, 1, 128);
-void* var_19 = tensorBatchNorm(var_18, batch_normalization_6_gamma, batch_normalization_6_beta, batch_normalization_6_mean, batch_normalization_6_variance, 0.001);
-void* var_20 = tensorRelu(var_19);
-void* var_21 = tensorConvolution(var_20, conv2d_4_w, 0, 0, 1, 1, 1, 1);
-void* var_22 = tensorBatchNorm(var_21, batch_normalization_7_gamma, batch_normalization_7_beta, batch_normalization_7_mean, batch_normalization_7_variance, 0.001);
-void* var_23 = tensorRelu(var_22);
-void* var_26 = tensorConvolution(var_23, depthwise_conv2d_4_w, 1, 1, 2, 2, 1, 128);
-void* var_27 = tensorBatchNorm(var_26, batch_normalization_8_gamma, batch_normalization_8_beta, batch_normalization_8_mean, batch_normalization_8_variance, 0.001);
-void* var_28 = tensorRelu(var_27);
-void* var_29 = tensorConvolution(var_28, conv2d_5_w, 0, 0, 1, 1, 1, 1);
-void* var_30 = tensorBatchNorm(var_29, batch_normalization_9_gamma, batch_normalization_9_beta, batch_normalization_9_mean, batch_normalization_9_variance, 0.001);
-void* var_31 = tensorRelu(var_30);
-void* var_33 = tensorConvolution(var_31, depthwise_conv2d_5_w, 1, 1, 1, 1, 1, 256);
-void* var_34 = tensorBatchNorm(var_33, batch_normalization_10_gamma, batch_normalization_10_beta, batch_normalization_10_mean, batch_normalization_10_variance, 0.001);
-void* var_35 = tensorRelu(var_34);
-void* var_36 = tensorConvolution(var_35, conv2d_6_w, 0, 0, 1, 1, 1, 1);
-void* var_37 = tensorBatchNorm(var_36, batch_normalization_11_gamma, batch_normalization_11_beta, batch_normalization_11_mean, batch_normalization_11_variance, 0.001);
-void* var_38 = tensorRelu(var_37);
-void* var_41 = tensorConvolution(var_38, depthwise_conv2d_6_w, 1, 1, 2, 2, 1, 256);
-void* var_42 = tensorBatchNorm(var_41, batch_normalization_12_gamma, batch_normalization_12_beta, batch_normalization_12_mean, batch_normalization_12_variance, 0.001);
-void* var_43 = tensorRelu(var_42);
-void* var_44 = tensorConvolution(var_43, conv2d_7_w, 0, 0, 1, 1, 1, 1);
-void* var_45 = tensorBatchNorm(var_44, batch_normalization_13_gamma, batch_normalization_13_beta, batch_normalization_13_mean, batch_normalization_13_variance, 0.001);
-void* var_46 = tensorRelu(var_45);
-void* var_47 = tensorPooling(var_46,1,2,2,0,0,2,2);
-void* var_49 = tensorGemmGPU(var_47, dense_1_w);
-void* var_50 = tensorAdd(var_49, dense_1_b);
-void* var_51 = tensorSoftmax(var_50);
-
-uint8_t* labels = readLabelsBatch(labels_path.c_str(),start,end);
-
-float accuracy = computeAccuracy2(labels, batch_size, var_51);
-final_accuracy += accuracy;
-freeBatchMemory();
-
-}
-
-final_accuracy = final_accuracy / batch_count;
-dumpFinalAccuracy(final_accuracy);
-
-
-llvm_hpvm_cleanupTensorRt();
-
-return 0;
-
-}
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/promise_src.cc b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/promise_src.cc
index 4cd8415fff51a7d4e01aef615995a15d099b2cda..c5fd3606da51281bc2c583e98f024bd2f54f837b 100644
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/promise_src.cc
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/promise_src.cc
@@ -28,7 +28,7 @@ for(int i = 0; i < batch_count; i++){
-std::string dir_prefix = std::string("data/mobilenet_shallow/");
+std::string dir_prefix = std::string("data/mobilenet_shallow_nathan/");
std::string input_path = dir_prefix + std::string("input.bin");
std::string labels_path = dir_prefix + std::string("labels.bin");
std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
@@ -72,27 +72,27 @@ void* batch_normalization_4_mean = readTrainedWeights(batch_normalization_4_mea
std::string batch_normalization_4_variance_path = dir_prefix + std::string("batch_normalization_4_variance.bin");
void* batch_normalization_4_variance = readTrainedWeights(batch_normalization_4_variance_path.c_str(), 0,1,64,1,1);
std::string conv2d_3_w_path = dir_prefix + std::string("conv2d_3_w.bin");
-void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,64,64,1,1);
+void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,128,64,1,1);
std::string batch_normalization_5_gamma_path = dir_prefix + std::string("batch_normalization_5_gamma.bin");
-void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_5_beta_path = dir_prefix + std::string("batch_normalization_5_beta.bin");
-void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_5_mean_path = dir_prefix + std::string("batch_normalization_5_mean.bin");
-void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_5_variance_path = dir_prefix + std::string("batch_normalization_5_variance.bin");
-void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,128,1,1);
std::string depthwise_conv2d_3_w_path = dir_prefix + std::string("depthwise_conv2d_3_w.bin");
-void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,64,1,3,3);
+void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,128,1,3,3);
std::string batch_normalization_6_gamma_path = dir_prefix + std::string("batch_normalization_6_gamma.bin");
-void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_6_beta_path = dir_prefix + std::string("batch_normalization_6_beta.bin");
-void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_6_mean_path = dir_prefix + std::string("batch_normalization_6_mean.bin");
-void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_6_variance_path = dir_prefix + std::string("batch_normalization_6_variance.bin");
-void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,128,1,1);
std::string conv2d_4_w_path = dir_prefix + std::string("conv2d_4_w.bin");
-void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,64,1,1);
+void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,128,1,1);
std::string batch_normalization_7_gamma_path = dir_prefix + std::string("batch_normalization_7_gamma.bin");
void* batch_normalization_7_gamma = readTrainedWeights(batch_normalization_7_gamma_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_7_beta_path = dir_prefix + std::string("batch_normalization_7_beta.bin");
@@ -141,8 +141,28 @@ std::string batch_normalization_11_mean_path = dir_prefix + std::string("batch_
void* batch_normalization_11_mean = readTrainedWeights(batch_normalization_11_mean_path.c_str(), 0,1,256,1,1);
std::string batch_normalization_11_variance_path = dir_prefix + std::string("batch_normalization_11_variance.bin");
void* batch_normalization_11_variance = readTrainedWeights(batch_normalization_11_variance_path.c_str(), 0,1,256,1,1);
+std::string depthwise_conv2d_6_w_path = dir_prefix + std::string("depthwise_conv2d_6_w.bin");
+void* depthwise_conv2d_6_w = readTrainedWeights(depthwise_conv2d_6_w_path.c_str(), 0,256,1,3,3);
+std::string batch_normalization_12_gamma_path = dir_prefix + std::string("batch_normalization_12_gamma.bin");
+void* batch_normalization_12_gamma = readTrainedWeights(batch_normalization_12_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_beta_path = dir_prefix + std::string("batch_normalization_12_beta.bin");
+void* batch_normalization_12_beta = readTrainedWeights(batch_normalization_12_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_mean_path = dir_prefix + std::string("batch_normalization_12_mean.bin");
+void* batch_normalization_12_mean = readTrainedWeights(batch_normalization_12_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_variance_path = dir_prefix + std::string("batch_normalization_12_variance.bin");
+void* batch_normalization_12_variance = readTrainedWeights(batch_normalization_12_variance_path.c_str(), 0,1,256,1,1);
+std::string conv2d_7_w_path = dir_prefix + std::string("conv2d_7_w.bin");
+void* conv2d_7_w = readTrainedWeights(conv2d_7_w_path.c_str(), 0,512,256,1,1);
+std::string batch_normalization_13_gamma_path = dir_prefix + std::string("batch_normalization_13_gamma.bin");
+void* batch_normalization_13_gamma = readTrainedWeights(batch_normalization_13_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_beta_path = dir_prefix + std::string("batch_normalization_13_beta.bin");
+void* batch_normalization_13_beta = readTrainedWeights(batch_normalization_13_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_mean_path = dir_prefix + std::string("batch_normalization_13_mean.bin");
+void* batch_normalization_13_mean = readTrainedWeights(batch_normalization_13_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_variance_path = dir_prefix + std::string("batch_normalization_13_variance.bin");
+void* batch_normalization_13_variance = readTrainedWeights(batch_normalization_13_variance_path.c_str(), 0,1,512,1,1);
std::string dense_1_w_path = dir_prefix + std::string("dense_1_w.bin");
-void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,1024,10);
+void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,2048,10);
std::string dense_1_b_path = dir_prefix + std::string("dense_1_b.bin");
void* dense_1_b = readTrainedWeights(dense_1_b_path.c_str(), 0,1,10,1,1);
@@ -152,46 +172,52 @@ int end = (i + 1) * batch_size;
void* input = readInputBatch(input_path.c_str(),0,start,end,3,32,32);
-void* var_0 = ConvLayer_PROMISE(input, -1.9892114, 2.126797, conv2d_1_w, -1.340709443449974, 1.3555025291442875, NULL, 0, 0, 1, 1, 1, 1, -1, 0, -1, -7.2273098745346065, 8.197232282638556, 9);
+void* var_0 = ConvLayer_PROMISE(input, -1.9892114, 2.126797, conv2d_1_w, -1.5164621164798737, 1.6472081774473288, NULL, 0, 0, 1, 1, 1, 1, -1, 0, -1, -9.868980642318725, 10.560956018447879, 9);
void* var_1 = tensorBatchNorm(var_0, batch_normalization_1_gamma, batch_normalization_1_beta, batch_normalization_1_mean, batch_normalization_1_variance, 0.001);
void* var_2 = tensorRelu(var_1);
void* var_3 = tensorConvolution(var_2, depthwise_conv2d_1_w, 1, 1, 1, 1, 1, 32);
void* var_4 = tensorBatchNorm(var_3, batch_normalization_2_gamma, batch_normalization_2_beta, batch_normalization_2_mean, batch_normalization_2_variance, 0.001);
void* var_5 = tensorRelu(var_4);
-void* var_6 = ConvLayer_PROMISE(var_5, 0.0, 6.053754347324407, conv2d_2_w, -1.1412922372817993, 0.9433415410518639, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -6.87497807598114, 5.3558874282836655, 9);
+void* var_6 = ConvLayer_PROMISE(var_5, 0.0, 6.821381127357554, conv2d_2_w, -1.1834390873908995, 1.2731596627235617, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -9.875998497009277, 7.51305247974393, 9);
void* var_7 = tensorBatchNorm(var_6, batch_normalization_3_gamma, batch_normalization_3_beta, batch_normalization_3_mean, batch_normalization_3_variance, 0.001);
void* var_8 = tensorRelu(var_7);
void* var_9 = tensorConvolution(var_8, depthwise_conv2d_2_w, 1, 1, 2, 2, 1, 64);
void* var_10 = tensorBatchNorm(var_9, batch_normalization_4_gamma, batch_normalization_4_beta, batch_normalization_4_mean, batch_normalization_4_variance, 0.001);
void* var_11 = tensorRelu(var_10);
-void* var_12 = ConvLayer_PROMISE(var_11, 0.0, 4.144686742782682, conv2d_3_w, -0.6453772538900375, 0.6694499132037164, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -5.349411018371582, 4.33332164001466, 9);
+void* var_12 = ConvLayer_PROMISE(var_11, 0.0, 4.826067455768602, conv2d_3_w, -0.599876856982708, 0.6812073457241064, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -5.633289833068848, 5.177892235755925, 9);
void* var_13 = tensorBatchNorm(var_12, batch_normalization_5_gamma, batch_normalization_5_beta, batch_normalization_5_mean, batch_normalization_5_variance, 0.001);
void* var_14 = tensorRelu(var_13);
-void* var_15 = tensorConvolution(var_14, depthwise_conv2d_3_w, 1, 1, 2, 2, 1, 64);
+void* var_15 = tensorConvolution(var_14, depthwise_conv2d_3_w, 1, 1, 1, 1, 1, 128);
void* var_16 = tensorBatchNorm(var_15, batch_normalization_6_gamma, batch_normalization_6_beta, batch_normalization_6_mean, batch_normalization_6_variance, 0.001);
void* var_17 = tensorRelu(var_16);
-void* var_18 = ConvLayer_PROMISE(var_17, 0.0, 4.248231422424324, conv2d_4_w, -0.44596208560466766, 0.49276923143864204, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -3.3628717079162596, 3.058014160633088, 9);
+void* var_18 = ConvLayer_PROMISE(var_17, 0.0, 4.02646304416659, conv2d_4_w, -0.4555967862010002, 0.4942613914608956, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -5.316803941726685, 4.605850250244146, 9);
void* var_19 = tensorBatchNorm(var_18, batch_normalization_7_gamma, batch_normalization_7_beta, batch_normalization_7_mean, batch_normalization_7_variance, 0.001);
void* var_20 = tensorRelu(var_19);
void* var_21 = tensorConvolution(var_20, depthwise_conv2d_4_w, 1, 1, 2, 2, 1, 128);
void* var_22 = tensorBatchNorm(var_21, batch_normalization_8_gamma, batch_normalization_8_beta, batch_normalization_8_mean, batch_normalization_8_variance, 0.001);
void* var_23 = tensorRelu(var_22);
-void* var_24 = ConvLayer_PROMISE(var_23, 0.0, 5.569213481903169, conv2d_5_w, -0.3239764194488525, 0.2983359285593033, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -5.473401127815246, 4.425663429260224, 9);
+void* var_24 = ConvLayer_PROMISE(var_23, 0.0, 4.532649063110355, conv2d_5_w, -0.35657615590095515, 0.3382165088057521, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -6.1012511816024775, 4.3630500688553, 9);
void* var_25 = tensorBatchNorm(var_24, batch_normalization_9_gamma, batch_normalization_9_beta, batch_normalization_9_mean, batch_normalization_9_variance, 0.001);
void* var_26 = tensorRelu(var_25);
void* var_27 = tensorConvolution(var_26, depthwise_conv2d_5_w, 1, 1, 1, 1, 1, 256);
void* var_28 = tensorBatchNorm(var_27, batch_normalization_10_gamma, batch_normalization_10_beta, batch_normalization_10_mean, batch_normalization_10_variance, 0.001);
void* var_29 = tensorRelu(var_28);
-void* var_30 = ConvLayer_PROMISE(var_29, 0.0, 3.728998669862753, conv2d_6_w, -0.2290773878991604, 0.22830345794558554, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -3.1163714165687564, 2.065946404457088, 9);
+void* var_30 = ConvLayer_PROMISE(var_29, 0.0, 3.9874704387188977, conv2d_6_w, -0.28502783328294756, 0.28604640334844594, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -4.243851703643799, 3.486250406742097, 9);
void* var_31 = tensorBatchNorm(var_30, batch_normalization_11_gamma, batch_normalization_11_beta, batch_normalization_11_mean, batch_normalization_11_variance, 0.001);
void* var_32 = tensorRelu(var_31);
-void* var_33 = tensorPooling(var_32,1,2,2,0,0,2,2);
-void* var_34 = FCLayer_PROMISE(var_33, 0.0, 2.191649281263443, dense_1_w, -0.3627079802751541, 0.3849146918058397, dense_1_b, -0.37858343, 0.377391, -1, -11.424064125061035, 18.695249080657973, 9);
-void* var_35 = tensorSoftmax(var_34);
+void* var_33 = tensorConvolution(var_32, depthwise_conv2d_6_w, 1, 1, 2, 2, 1, 256);
+void* var_34 = tensorBatchNorm(var_33, batch_normalization_12_gamma, batch_normalization_12_beta, batch_normalization_12_mean, batch_normalization_12_variance, 0.001);
+void* var_35 = tensorRelu(var_34);
+void* var_36 = ConvLayer_PROMISE(var_35, 0.0, 6.563065901756522, conv2d_7_w, -0.18946402323246003, 0.19012390717864017, NULL, 0, 0, 0, 0, 1, 1, -1, 0, -1, -4.938115713119507, 3.538363476753238, 9);
+void* var_37 = tensorBatchNorm(var_36, batch_normalization_13_gamma, batch_normalization_13_beta, batch_normalization_13_mean, batch_normalization_13_variance, 0.001);
+void* var_38 = tensorRelu(var_37);
+void* var_39 = tensorPooling(var_38,1,2,2,0,0,2,2);
+void* var_40 = FCLayer_PROMISE(var_39, 0.0, 1.8908388000727185, dense_1_w, -0.35140394401550296, 0.422872786462307, dense_1_b, -0.23878151, 0.26507422, -1, -14.630816223144532, 27.27252123260504, 9);
+void* var_41 = tensorSoftmax(var_40);
uint8_t* labels = readLabelsBatch(labels_path.c_str(),start,end);
-float accuracy = computeAccuracy2(labels, batch_size, var_35);
+float accuracy = computeAccuracy2(labels, batch_size, var_41);
final_accuracy += accuracy;
freeBatchMemory();
diff --git a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/src.cc b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/src.cc
index 62104d7fe36e72a189cb1d12f44b77ed3032f9fd..6599f7d0ea0be6a76c4154d25b3a7be2c6724115 100644
--- a/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/src.cc
+++ b/llvm/projects/hpvm-tensor-rt/model_params/mobilenet_shallow/src.cc
@@ -14,7 +14,7 @@ int main(){
llvm_hpvm_initTensorRt(0);
-std::string dir_prefix = std::string("data/mobilenet_shallow/");
+std::string dir_prefix = std::string("data/mobilenet_shallow_nathan/");
std::string input_path = dir_prefix + std::string("input.bin");
std::string labels_path = dir_prefix + std::string("labels.bin");
std::string conv2d_1_w_path = dir_prefix + std::string("conv2d_1_w.bin");
@@ -58,27 +58,27 @@ void* batch_normalization_4_mean = readTrainedWeights(batch_normalization_4_mea
std::string batch_normalization_4_variance_path = dir_prefix + std::string("batch_normalization_4_variance.bin");
void* batch_normalization_4_variance = readTrainedWeights(batch_normalization_4_variance_path.c_str(), 0,1,64,1,1);
std::string conv2d_3_w_path = dir_prefix + std::string("conv2d_3_w.bin");
-void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,64,64,1,1);
+void* conv2d_3_w = readTrainedWeights(conv2d_3_w_path.c_str(), 0,128,64,1,1);
std::string batch_normalization_5_gamma_path = dir_prefix + std::string("batch_normalization_5_gamma.bin");
-void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_gamma = readTrainedWeights(batch_normalization_5_gamma_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_5_beta_path = dir_prefix + std::string("batch_normalization_5_beta.bin");
-void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_beta = readTrainedWeights(batch_normalization_5_beta_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_5_mean_path = dir_prefix + std::string("batch_normalization_5_mean.bin");
-void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_mean = readTrainedWeights(batch_normalization_5_mean_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_5_variance_path = dir_prefix + std::string("batch_normalization_5_variance.bin");
-void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_5_variance = readTrainedWeights(batch_normalization_5_variance_path.c_str(), 0,1,128,1,1);
std::string depthwise_conv2d_3_w_path = dir_prefix + std::string("depthwise_conv2d_3_w.bin");
-void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,64,1,3,3);
+void* depthwise_conv2d_3_w = readTrainedWeights(depthwise_conv2d_3_w_path.c_str(), 0,128,1,3,3);
std::string batch_normalization_6_gamma_path = dir_prefix + std::string("batch_normalization_6_gamma.bin");
-void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_gamma = readTrainedWeights(batch_normalization_6_gamma_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_6_beta_path = dir_prefix + std::string("batch_normalization_6_beta.bin");
-void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_beta = readTrainedWeights(batch_normalization_6_beta_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_6_mean_path = dir_prefix + std::string("batch_normalization_6_mean.bin");
-void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_mean = readTrainedWeights(batch_normalization_6_mean_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_6_variance_path = dir_prefix + std::string("batch_normalization_6_variance.bin");
-void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,64,1,1);
+void* batch_normalization_6_variance = readTrainedWeights(batch_normalization_6_variance_path.c_str(), 0,1,128,1,1);
std::string conv2d_4_w_path = dir_prefix + std::string("conv2d_4_w.bin");
-void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,64,1,1);
+void* conv2d_4_w = readTrainedWeights(conv2d_4_w_path.c_str(), 0,128,128,1,1);
std::string batch_normalization_7_gamma_path = dir_prefix + std::string("batch_normalization_7_gamma.bin");
void* batch_normalization_7_gamma = readTrainedWeights(batch_normalization_7_gamma_path.c_str(), 0,1,128,1,1);
std::string batch_normalization_7_beta_path = dir_prefix + std::string("batch_normalization_7_beta.bin");
@@ -127,8 +127,28 @@ std::string batch_normalization_11_mean_path = dir_prefix + std::string("batch_
void* batch_normalization_11_mean = readTrainedWeights(batch_normalization_11_mean_path.c_str(), 0,1,256,1,1);
std::string batch_normalization_11_variance_path = dir_prefix + std::string("batch_normalization_11_variance.bin");
void* batch_normalization_11_variance = readTrainedWeights(batch_normalization_11_variance_path.c_str(), 0,1,256,1,1);
+std::string depthwise_conv2d_6_w_path = dir_prefix + std::string("depthwise_conv2d_6_w.bin");
+void* depthwise_conv2d_6_w = readTrainedWeights(depthwise_conv2d_6_w_path.c_str(), 0,256,1,3,3);
+std::string batch_normalization_12_gamma_path = dir_prefix + std::string("batch_normalization_12_gamma.bin");
+void* batch_normalization_12_gamma = readTrainedWeights(batch_normalization_12_gamma_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_beta_path = dir_prefix + std::string("batch_normalization_12_beta.bin");
+void* batch_normalization_12_beta = readTrainedWeights(batch_normalization_12_beta_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_mean_path = dir_prefix + std::string("batch_normalization_12_mean.bin");
+void* batch_normalization_12_mean = readTrainedWeights(batch_normalization_12_mean_path.c_str(), 0,1,256,1,1);
+std::string batch_normalization_12_variance_path = dir_prefix + std::string("batch_normalization_12_variance.bin");
+void* batch_normalization_12_variance = readTrainedWeights(batch_normalization_12_variance_path.c_str(), 0,1,256,1,1);
+std::string conv2d_7_w_path = dir_prefix + std::string("conv2d_7_w.bin");
+void* conv2d_7_w = readTrainedWeights(conv2d_7_w_path.c_str(), 0,512,256,1,1);
+std::string batch_normalization_13_gamma_path = dir_prefix + std::string("batch_normalization_13_gamma.bin");
+void* batch_normalization_13_gamma = readTrainedWeights(batch_normalization_13_gamma_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_beta_path = dir_prefix + std::string("batch_normalization_13_beta.bin");
+void* batch_normalization_13_beta = readTrainedWeights(batch_normalization_13_beta_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_mean_path = dir_prefix + std::string("batch_normalization_13_mean.bin");
+void* batch_normalization_13_mean = readTrainedWeights(batch_normalization_13_mean_path.c_str(), 0,1,512,1,1);
+std::string batch_normalization_13_variance_path = dir_prefix + std::string("batch_normalization_13_variance.bin");
+void* batch_normalization_13_variance = readTrainedWeights(batch_normalization_13_variance_path.c_str(), 0,1,512,1,1);
std::string dense_1_w_path = dir_prefix + std::string("dense_1_w.bin");
-void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,1024,10);
+void* dense_1_w = readTrainedWeights(dense_1_w_path.c_str(), 0,1,1,2048,10);
std::string dense_1_b_path = dir_prefix + std::string("dense_1_b.bin");
void* dense_1_b = readTrainedWeights(dense_1_b_path.c_str(), 0,1,10,1,1);
@@ -163,7 +183,7 @@ void* var_13 = tensorRelu(var_12);
void* var_14 = tensorConvolution(var_13, conv2d_3_w, 0, 0, 1, 1, 1, 1);
void* var_15 = tensorBatchNorm(var_14, batch_normalization_5_gamma, batch_normalization_5_beta, batch_normalization_5_mean, batch_normalization_5_variance, 0.001);
void* var_16 = tensorRelu(var_15);
-void* var_18 = tensorConvolution(var_16, depthwise_conv2d_3_w, 1, 1, 2, 2, 1, 64);
+void* var_18 = tensorConvolution(var_16, depthwise_conv2d_3_w, 1, 1, 1, 1, 1, 128);
void* var_19 = tensorBatchNorm(var_18, batch_normalization_6_gamma, batch_normalization_6_beta, batch_normalization_6_mean, batch_normalization_6_variance, 0.001);
void* var_20 = tensorRelu(var_19);
void* var_21 = tensorConvolution(var_20, conv2d_4_w, 0, 0, 1, 1, 1, 1);
@@ -181,14 +201,20 @@ void* var_35 = tensorRelu(var_34);
void* var_36 = tensorConvolution(var_35, conv2d_6_w, 0, 0, 1, 1, 1, 1);
void* var_37 = tensorBatchNorm(var_36, batch_normalization_11_gamma, batch_normalization_11_beta, batch_normalization_11_mean, batch_normalization_11_variance, 0.001);
void* var_38 = tensorRelu(var_37);
-void* var_40 = tensorPooling(var_38,1,2,2,0,0,2,2);
-void* var_42 = tensorGemmGPU(var_40, dense_1_w);
-void* var_43 = tensorAdd(var_42, dense_1_b);
-void* var_44 = tensorSoftmax(var_43);
+void* var_41 = tensorConvolution(var_38, depthwise_conv2d_6_w, 1, 1, 2, 2, 1, 256);
+void* var_42 = tensorBatchNorm(var_41, batch_normalization_12_gamma, batch_normalization_12_beta, batch_normalization_12_mean, batch_normalization_12_variance, 0.001);
+void* var_43 = tensorRelu(var_42);
+void* var_44 = tensorConvolution(var_43, conv2d_7_w, 0, 0, 1, 1, 1, 1);
+void* var_45 = tensorBatchNorm(var_44, batch_normalization_13_gamma, batch_normalization_13_beta, batch_normalization_13_mean, batch_normalization_13_variance, 0.001);
+void* var_46 = tensorRelu(var_45);
+void* var_47 = tensorPooling(var_46,1,2,2,0,0,2,2);
+void* var_49 = tensorGemmGPU(var_47, dense_1_w);
+void* var_50 = tensorAdd(var_49, dense_1_b);
+void* var_51 = tensorSoftmax(var_50);
uint8_t* labels = readLabelsBatch(labels_path.c_str(),start,end);
-float accuracy = computeAccuracy2(labels, batch_size, var_44);
+float accuracy = computeAccuracy2(labels, batch_size, var_51);
final_accuracy += accuracy;
freeBatchMemory();