From d0ac4c2fc559f6b0e1ffad66a3e8764c9384a3cc Mon Sep 17 00:00:00 2001
From: Hashim Sharif <hsharif3@tyler.cs.illinois.edu>
Date: Thu, 8 Aug 2019 21:01:32 -0500
Subject: [PATCH] Adding AlexNet CUDNN and PROMISE sources + Makefile

---
 .../benchmarks/alexnet/Makefile               |  36 +-
 .../benchmarks/alexnet/data/quant_ranges.txt  |   6 +
 .../benchmarks/alexnet/src/alexnet.cpp        |  28 +-
 .../alexnet/src/alexnet_promise.cpp           | 450 ++++++++++++++++++
 4 files changed, 492 insertions(+), 28 deletions(-)
 create mode 100644 llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/data/quant_ranges.txt
 create mode 100644 llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/src/alexnet_promise.cpp

diff --git a/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/Makefile b/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/Makefile
index 86e93cb809..1b4b75c89d 100644
--- a/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/Makefile
+++ b/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/Makefile
@@ -1,6 +1,6 @@
 DNN_BENCHMARK_ROOT = $(LLVM_SRC_ROOT)/test/VISC/DNN_Benchmarks
 # NOTE: can configure build directory
-HPVM_BUILD_DIR = $(LLVM_SRC_ROOT)/../build_fresh/
+HPVM_BUILD_DIR = $(LLVM_SRC_ROOT)/../build_hpvm/
 
 CC = $(HPVM_BUILD_DIR)/bin/clang++
 OPT = $(HPVM_BUILD_DIR)/bin/opt
@@ -8,7 +8,6 @@ LLVM_DIS = $(HPVM_BUILD_DIR)/bin/llvm-dis
 LLVM_LINK = $(HPVM_BUILD_DIR)/bin/llvm-link
 LLVM_INCLUDE_DIR = $(LLVM_SRC_ROOT)/include
 
-
 SRC_DIR = src
 BUILD_DIR = build
 APP = alexnet
@@ -23,11 +22,17 @@ CCFLAGS += -DDEVICE=CUDNN_TARGET
 LINKER_FLAGS = -lpthread -lcudart -lcurand -lcudnn -lcublas -lOpenCL
 
 HPVM_LIB_DIR = $(HPVM_BUILD_DIR)/lib
-#HPVM_LIB_DIR = /home/hsharif3/Gitlab/hpvm/build_new/lib
 
 
 VISC_OPTFLAGS = -load  $(HPVM_LIB_DIR)/LLVMBuildDFG.so -load $(HPVM_LIB_DIR)/LLVMInPlaceDFGAnalysis.so -load  $(HPVM_LIB_DIR)/LLVMDFG2LLVM_CUDNN.so -load  $(HPVM_LIB_DIR)/LLVMDFG2LLVM_X86.so -load  $(HPVM_LIB_DIR)/LLVMClearDFG.so -inplace -dfg2llvm-cudnn -dfg2llvm-x86 -clearDFG
 
+
+QUANT_FILE_PATH=/home/hsharif3/Gitlab/hpvm/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/data/quant_ranges.txt
+
+VISC_OPTFLAGS2 = -load  $(HPVM_LIB_DIR)/LLVMBuildDFG.so -load $(HPVM_LIB_DIR)/LLVMInPlaceDFGAnalysis.so -load  $(HPVM_LIB_DIR)/LLVMDFG2LLVM_PROMISE.so  -load  $(HPVM_LIB_DIR)/LLVMDFG2LLVM_CUDNN.so    -load  $(HPVM_LIB_DIR)/LLVMDFG2LLVM_X86.so -load  $(HPVM_LIB_DIR)/LLVMFuseHPVMTensorNodes.so  -load  $(HPVM_LIB_DIR)/LLVMClearDFG.so   -inplace -hpvm-fuse -dfg2llvm-promise  -quantization-levels-filename=$(QUANT_FILE_PATH) -dfg2llvm-cudnn  -dfg2llvm-x86 -clearDFG
+
+
+
 TARGET = $(BUILD_DIR)/$(APP).opt.bc
 SOURCES = $(SRC_DIR)/$(APP).cpp
 VISC_RT_PATH = $(LLVM_SRC_ROOT)/../build/projects/visc-rt/visc-rt.ll
@@ -38,17 +43,20 @@ default: $(BUILD_DIR) $(TARGET)
 
 
 $(BUILD_DIR)/%.ll: $(SRC_DIR)/%.cpp
-	$(CC) $(CC_FLAGS) -emit-llvm -S -o $@ $<
-
-#-visc-timers-gen
-$(BUILD_DIR)/%.visc.ll: $(BUILD_DIR)/%.ll
-	$(OPT) -load LLVMGenVISC.so -genvisc -globaldce  $< -S -o $@
-
-$(BUILD_DIR)/%.opt.bc: $(BUILD_DIR)/%.visc.ll
-	$(OPT) $(VISC_OPTFLAGS) $< -o $@
-	$(LLVM_LINK) $@ $(VISC_RT_PATH) -o $(BUILD_DIR)/$(APP)_linked.bc
-	$(CC) $(BUILD_DIR)/$(APP)_linked.bc $(TENSOR_LIB_DIR) -o $(BUILD_DIR)/$(APP)_linked $(LINKER_FLAGS)
-	$(CC) $(BUILD_DIR)/$(APP)_linked.bc $(TENSOR_AUTOTUNER_DIR) -o $(BUILD_DIR)/$(APP)_tune $(LINKER_FLAGS)
+	$(CC) $(CC_FLAGS) -emit-llvm src/$(APP).cpp -S -o  $(BUILD_DIR)/$(APP).ll  
+	$(CC) $(CC_FLAGS) -emit-llvm src/$(APP)_promise.cpp -S -o $(BUILD_DIR)/$(APP)_promise.ll
+
+
+$(BUILD_DIR)/%.opt.bc: $(BUILD_DIR)/%.ll
+	$(OPT) -load LLVMGenVISC.so -genvisc -globaldce  $(BUILD_DIR)/$(APP).ll -S -o  $(BUILD_DIR)/$(APP).visc.ll
+	$(OPT) -load LLVMGenVISC.so -genvisc -globaldce  $(BUILD_DIR)/$(APP)_promise.ll -S -o  $(BUILD_DIR)/$(APP)_promise.visc.ll
+	$(OPT) $(VISC_OPTFLAGS)  $(BUILD_DIR)/$(APP).visc.ll  -o  $(BUILD_DIR)/$(APP)_cudnn.bc
+	$(OPT) $(VISC_OPTFLAGS2) $(BUILD_DIR)/$(APP)_promise.visc.ll  -o  $(BUILD_DIR)/$(APP)_promise.bc
+	$(LLVM_LINK) $(BUILD_DIR)/$(APP)_cudnn.bc $(VISC_RT_PATH) -o $(BUILD_DIR)/$(APP)_cudnn_linked.bc
+	$(LLVM_LINK) $(BUILD_DIR)/$(APP)_promise.bc $(VISC_RT_PATH) -o $(BUILD_DIR)/$(APP)_promise_linked.bc
+	$(CC) $(BUILD_DIR)/$(APP)_cudnn_linked.bc $(TENSOR_LIB_DIR) -o $(BUILD_DIR)/$(APP)_cudnn_linked $(LINKER_FLAGS)
+	$(CC) $(BUILD_DIR)/$(APP)_promise_linked.bc $(TENSOR_LIB_DIR) -o $(BUILD_DIR)/$(APP)_promise_linked $(LINKER_FLAGS)
+	#$(CC) $(BUILD_DIR)/$(APP)_cudnn_linked.bc $(TENSOR_AUTOTUNER_DIR) -o $(BUILD_DIR)/lenet_tune $(LINKER_FLAGS)
 
 $(BUILD_DIR):
 	mkdir -p $@
diff --git a/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/data/quant_ranges.txt b/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/data/quant_ranges.txt
new file mode 100644
index 0000000000..789a4114a5
--- /dev/null
+++ b/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/data/quant_ranges.txt
@@ -0,0 +1,6 @@
+-1.88164262419 2.09340954985 -0.33087718 0.3323643 -0.7782218 0.6020472 -0.978641152382 0.998945295811 
+-0.978641152382 0.998945295811 -0.2095158 0.33543423 -0.45020863 0.30596754 -0.999703943729 0.999930202961 
+-0.999703943729 0.999930202961 -0.1715614 0.17037082 -0.6519161 0.5939945 -0.999933600426 0.999940037727 
+-0.999933600426 0.999940037727 -0.15575546 0.14456555 -0.55873865 0.4704539 -0.99999910593 0.999999344349 
+-0.99999910593 0.999999344349 -0.16108225 0.16864482 -0.22135437 0.10401678 -0.999434411526 0.999634206295 
+-0.999434411526 0.999634206295 -0.18183032 0.19018902 -0.07189204 0.106005594 -15.0765653801 19.4225852203 
diff --git a/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/src/alexnet.cpp b/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/src/alexnet.cpp
index ef6fda1d31..58c5bf380a 100644
--- a/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/src/alexnet.cpp
+++ b/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/src/alexnet.cpp
@@ -369,39 +369,39 @@ RootIn;
 
 int main(){ 
 
-  std::string dir_prefix = std::string("../../../../../../projects/hpvm-tensor-rt/model_params/alexnet_cifar10_front/");
-  //std::string dir_prefix = std::string("../../../../../../projects/hpvm-tensor-rt/model_params/alexnet_cifar10/"); 
+  std::string dir_prefix = std::string("../../../../../../projects/hpvm-tensor-rt/model_params/alexnet_cifar10_test/");
 
   std::string input_path =  dir_prefix + std::string("input.bin"); 
   void* input = readTrainedWeights(input_path.c_str(), 0,10000,3,32,32); 
   std::string labels_path =  dir_prefix + std::string("labels.bin"); 
   uint8_t* labels = readLabels(labels_path.c_str(),10000); 
-  std::string conv2d_1_w_path =  dir_prefix + std::string("conv0.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(), 0,64,3,11,11); 
-  std::string conv2d_1_b_path =  dir_prefix + std::string("conv_bias0.bin"); 
+  std::string conv2d_1_b_path =  dir_prefix + std::string("conv2d_1_b.bin"); 
   void* conv2d_1_b =  readTrainedWeights(conv2d_1_b_path.c_str(), 0,1,64,1,1); 
-  std::string conv2d_2_w_path =  dir_prefix + std::string("conv3.bin"); 
+  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(), 0,192,64,5,5); 
-  std::string conv2d_2_b_path =  dir_prefix + std::string("conv_bias3.bin"); 
+  std::string conv2d_2_b_path =  dir_prefix + std::string("conv2d_2_b.bin"); 
   void* conv2d_2_b =  readTrainedWeights(conv2d_2_b_path.c_str(), 0,1,192,1,1); 
-  std::string conv2d_3_w_path =  dir_prefix + std::string("conv6.bin"); 
+  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(), 0,384,192,3,3); 
-  std::string conv2d_3_b_path =  dir_prefix + std::string("conv_bias6.bin"); 
+  std::string conv2d_3_b_path =  dir_prefix + std::string("conv2d_3_b.bin"); 
   void* conv2d_3_b =  readTrainedWeights(conv2d_3_b_path.c_str(), 0,1,384,1,1); 
-  std::string conv2d_4_w_path =  dir_prefix + std::string("conv7.bin"); 
+  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(), 0,256,384,3,3); 
-  std::string conv2d_4_b_path =  dir_prefix + std::string("conv_bias7.bin"); 
+  std::string conv2d_4_b_path =  dir_prefix + std::string("conv2d_4_b.bin"); 
   void* conv2d_4_b =  readTrainedWeights(conv2d_4_b_path.c_str(), 0,1,256,1,1); 
-  std::string conv2d_5_w_path =  dir_prefix + std::string("conv8.bin"); 
+  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(), 0,256,256,3,3); 
-  std::string conv2d_5_b_path =  dir_prefix + std::string("conv_bias8.bin"); 
+  std::string conv2d_5_b_path =  dir_prefix + std::string("conv2d_5_b.bin"); 
   void* conv2d_5_b =  readTrainedWeights(conv2d_5_b_path.c_str(), 0,1,256,1,1); 
-  std::string dense_1_w_path =  dir_prefix + std::string("fc12.bin"); 
+  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(), 0,1,1,4096,10); 
-  std::string dense_1_b_path =  dir_prefix + std::string("fc_bias12.bin"); 
+  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); 
 
 
+
   __visc__init(); 
   RootIn* args = static_cast<RootIn*>(malloc(sizeof(RootIn))); 
 
diff --git a/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/src/alexnet_promise.cpp b/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/src/alexnet_promise.cpp
new file mode 100644
index 0000000000..9bff465223
--- /dev/null
+++ b/llvm/test/VISC/DNN_Benchmarks/benchmarks/alexnet/src/alexnet_promise.cpp
@@ -0,0 +1,450 @@
+
+#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, 5, 5, 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) { 
+  __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_2_node(void* t1, size_t bytes_t1) { 
+  __visc__hint(visc::PROMISE_TARGET); 
+  __visc__attributes(1, t1, 0); 
+
+  void* r = __visc__tensor_tanh(t1); 
+  __visc__return(2, r, (size_t) 0); 
+}
+
+void var_3_node(void* t1, size_t bytes_t1) { 
+  __visc__hint(visc::PROMISE_TARGET); 
+  __visc__attributes(1, t1, 0); 
+
+  void* r = __visc__tensor_pool_max(t1, 2, 2, 0, 0, 2, 2); 
+  __visc__return(2, r, (size_t) 0); 
+}
+
+void var_4_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, 2, 2, 1, 1); 
+  __visc__return(2, r, (size_t) 0); 
+}
+
+void var_5_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_6_node(void* t1, size_t bytes_t1) { 
+  __visc__hint(visc::PROMISE_TARGET); 
+  __visc__attributes(1, t1, 0); 
+
+  void* r = __visc__tensor_tanh(t1); 
+  __visc__return(2, r, (size_t) 0); 
+}
+
+void var_7_node(void* t1, size_t bytes_t1) { 
+  __visc__hint(visc::PROMISE_TARGET); 
+  __visc__attributes(1, t1, 0); 
+
+  void* r = __visc__tensor_pool_max(t1, 2, 2, 0, 0, 2, 2); 
+  __visc__return(2, r, (size_t) 0); 
+}
+
+void var_8_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_9_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_10_node(void* t1, size_t bytes_t1) { 
+  __visc__hint(visc::PROMISE_TARGET); 
+  __visc__attributes(1, t1, 0); 
+
+  void* r = __visc__tensor_tanh(t1); 
+  __visc__return(2, r, (size_t) 0); 
+}
+
+void var_11_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_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_add(t1, t2); 
+  __visc__return(2, r, (size_t) 0); 
+}
+
+void var_13_node(void* t1, size_t bytes_t1) { 
+  __visc__hint(visc::PROMISE_TARGET); 
+  __visc__attributes(1, t1, 0); 
+
+  void* r = __visc__tensor_tanh(t1); 
+  __visc__return(2, r, (size_t) 0); 
+}
+
+void var_14_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_15_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_16_node(void* t1, size_t bytes_t1) { 
+  __visc__hint(visc::PROMISE_TARGET); 
+  __visc__attributes(1, t1, 0); 
+
+  void* r = __visc__tensor_tanh(t1); 
+  __visc__return(2, r, (size_t) 0); 
+}
+
+void var_17_node(void* t1, size_t bytes_t1) { 
+  __visc__hint(visc::PROMISE_TARGET); 
+  __visc__attributes(1, t1, 0); 
+
+  void* r = __visc__tensor_pool_max(t1, 2, 2, 0, 0, 2, 2); 
+  __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_mul(t1, t2); 
+  __visc__return(2, r, (size_t) 0); 
+}
+
+void var_19_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_20_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* conv2d_1_b, size_t conv2d_1_b_bytes, 
+	  void* conv2d_2_w, size_t conv2d_2_w_bytes, 
+	  void* conv2d_2_b, size_t conv2d_2_b_bytes, 
+	  void* conv2d_3_w, size_t conv2d_3_w_bytes, 
+	  void* conv2d_3_b, size_t conv2d_3_b_bytes, 
+	  void* conv2d_4_w, size_t conv2d_4_w_bytes, 
+	  void* conv2d_4_b, size_t conv2d_4_b_bytes, 
+	  void* conv2d_5_w, size_t conv2d_5_w_bytes, 
+	  void* conv2d_5_b, size_t conv2d_5_b_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(13, input, conv2d_1_w, conv2d_1_b, conv2d_2_w, conv2d_2_b, conv2d_3_w, conv2d_3_b, conv2d_4_w, conv2d_4_b, conv2d_5_w, conv2d_5_b, 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); 
+
+  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); 
+
+  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, 6, 2, 0); 
+  __visc__bindIn(var_4, 7, 3, 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); 
+  __visc__bindIn(var_5, 8, 2, 0); 
+  __visc__bindIn(var_5, 9, 3, 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); 
+
+  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); 
+
+  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); 
+  __visc__bindIn(var_8, 10, 2, 0); 
+  __visc__bindIn(var_8, 11, 3, 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, 12, 2, 0); 
+  __visc__bindIn(var_9, 13, 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); 
+
+  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); 
+  __visc__bindIn(var_11, 14, 2, 0); 
+  __visc__bindIn(var_11, 15, 3, 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, 16, 2, 0); 
+  __visc__bindIn(var_12, 17, 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); 
+
+  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); 
+  __visc__bindIn(var_14, 18, 2, 0); 
+  __visc__bindIn(var_14, 19, 3, 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, 20, 2, 0); 
+  __visc__bindIn(var_15, 21, 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); 
+
+  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, 22, 2, 0); 
+  __visc__bindIn(var_18, 23, 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, 24, 2, 0); 
+  __visc__bindIn(var_19, 25, 3, 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); 
+
+  __visc__bindOut(var_20, 0, 0, 0); 
+  __visc__bindOut(var_20, 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* conv2d_1_b; 
+  size_t conv2d_1_b_bytes; 
+  void* conv2d_2_w; 
+  size_t conv2d_2_w_bytes; 
+  void* conv2d_2_b; 
+  size_t conv2d_2_b_bytes; 
+  void* conv2d_3_w; 
+  size_t conv2d_3_w_bytes; 
+  void* conv2d_3_b; 
+  size_t conv2d_3_b_bytes; 
+  void* conv2d_4_w; 
+  size_t conv2d_4_w_bytes; 
+  void* conv2d_4_b; 
+  size_t conv2d_4_b_bytes; 
+  void* conv2d_5_w; 
+  size_t conv2d_5_w_bytes; 
+  void* conv2d_5_b; 
+  size_t conv2d_5_b_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/alexnet_cifar10_test/");
+
+  std::string input_path =  dir_prefix + std::string("input.bin"); 
+  void* input = readTrainedWeights(input_path.c_str(), 0,5000,3,32,32); 
+  std::string labels_path =  dir_prefix + std::string("labels.bin"); 
+  uint8_t* labels = readLabels(labels_path.c_str(),5000); 
+  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(), 0,64,3,11,11); 
+  std::string conv2d_1_b_path =  dir_prefix + std::string("conv2d_1_b.bin"); 
+  void* conv2d_1_b =  readTrainedWeights(conv2d_1_b_path.c_str(), 0,1,64,1,1); 
+  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(), 0,192,64,5,5); 
+  std::string conv2d_2_b_path =  dir_prefix + std::string("conv2d_2_b.bin"); 
+  void* conv2d_2_b =  readTrainedWeights(conv2d_2_b_path.c_str(), 0,1,192,1,1); 
+  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(), 0,384,192,3,3); 
+  std::string conv2d_3_b_path =  dir_prefix + std::string("conv2d_3_b.bin"); 
+  void* conv2d_3_b =  readTrainedWeights(conv2d_3_b_path.c_str(), 0,1,384,1,1); 
+  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(), 0,256,384,3,3); 
+  std::string conv2d_4_b_path =  dir_prefix + std::string("conv2d_4_b.bin"); 
+  void* conv2d_4_b =  readTrainedWeights(conv2d_4_b_path.c_str(), 0,1,256,1,1); 
+  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(), 0,256,256,3,3); 
+  std::string conv2d_5_b_path =  dir_prefix + std::string("conv2d_5_b.bin"); 
+  void* conv2d_5_b =  readTrainedWeights(conv2d_5_b_path.c_str(), 0,1,256,1,1); 
+  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(), 0,1,1,4096,10); 
+  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); 
+
+
+
+  __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->conv2d_1_b = conv2d_1_b; 
+  args->conv2d_1_b_bytes = 0; 
+  args->conv2d_2_w = conv2d_2_w; 
+  args->conv2d_2_w_bytes = 0; 
+  args->conv2d_2_b = conv2d_2_b; 
+  args->conv2d_2_b_bytes = 0; 
+  args->conv2d_3_w = conv2d_3_w; 
+  args->conv2d_3_w_bytes = 0; 
+  args->conv2d_3_b = conv2d_3_b; 
+  args->conv2d_3_b_bytes = 0; 
+  args->conv2d_4_w = conv2d_4_w; 
+  args->conv2d_4_w_bytes = 0; 
+  args->conv2d_4_b = conv2d_4_b; 
+  args->conv2d_4_b_bytes = 0; 
+  args->conv2d_5_w = conv2d_5_w; 
+  args->conv2d_5_w_bytes = 0; 
+  args->conv2d_5_b = conv2d_5_b; 
+  args->conv2d_5_b_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; 
+
+} 
-- 
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