Skip to content
Snippets Groups Projects
Commit 5738e7de authored by Hashim Sharif's avatar Hashim Sharif
Browse files

merging

parents 8e7c6a04 685d89c6
No related branches found
No related tags found
No related merge requests found
Hide whitespace changes
Inline Side-by-side
llvm/test/VISC/DNN_Benchmarks/benchmarks/mobilenet_shallow/src/mobilenet_shallow_promise.cpp 0 → 100644
+ 1225
− 0
View file @ 5738e7de
#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::PROMISE_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::PROMISE_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::PROMISE_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::PROMISE_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::PROMISE_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::PROMISE_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::PROMISE_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_mean(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::PROMISE_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::PROMISE_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("../../../../../../projects/hpvm-tensor-rt/model_params/mobilenet_shallow/");
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, 5000,3,32,32);
uint8_t* labels = readLabels(labels_path.c_str(), 5000);
__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, 5000, result);
return 0;
}
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment