Fixing ResNet18 TensorRT sources

hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp16/resnet18_cifar10_half.cc

@@ -7,13 +7,12 @@ int main() {
 
   llvm_hpvm_initTensorRt(0);
 
-  std::string dir_prefix =
-      model_params_path + std::string("/resnet18_cifar10/");
-  std::string input_path = dir_prefix + std::string("input.bin");
-  // void* input = readTrainedWeights(input_path.c_str(), 0,
-  // batch_size,3,32,32);
-  std::string labels_path = dir_prefix + std::string("labels.bin");
-  // uint8_t* labels = readLabels(labels_path.c_str(), batch_size);
+  std::string dir_prefix =  model_params_path + std::string("/resnet18_cifar10/");
+
+  std::string input_path = dir_prefix + std::string("test_input.bin");
+  
+  std::string labels_path = dir_prefix + std::string("test_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, 16, 3, 3, 3);
@@ -237,9 +236,9 @@ int main() {
     void *var_95 = tensorHalfAdd(var_94, dense_1_b);
     void *var_96 = tensorSoftmax(var_95);
 
-    uint8_t *labels = readLabelsBatch(labels_path.c_str(), start, end);
+    uint32_t *labels = readLabelsBatch3(labels_path.c_str(), start, end);
 
-    float accuracy = computeAccuracy2(labels, batch_size, var_96);
+    float accuracy = computeAccuracy3(labels, var_96);
     final_accuracy += accuracy;
 
     freeBatchMemory();

hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet18_cifar10.cc

 
 
-#include "../../tensor_runtime/include/tensor_runtime.h"
-#include "../include/utils.h"
+#include "../../../tensor_runtime/include/tensor_runtime.h"
+#include "../../include/utils.h"
 
 int main() {
 
-  llvm_hpvm_initTensorRt(1);
+  llvm_hpvm_initTensorRt(0);
 
-  std::string dir_prefix =
-      model_params_path + std::string("/resnet18_cifar10/");
-  std::string input_path = dir_prefix + std::string("input.bin");
-  // void* input = readTrainedWeights(input_path.c_str(), 0,
-  // batch_size,3,32,32);
-  std::string labels_path = dir_prefix + std::string("labels.bin");
-  // uint8_t* labels = readLabels(labels_path.c_str(), batch_size);
+  std::string dir_prefix =  model_params_path + std::string("/resnet18_cifar10/");
+
+  std::string input_path = dir_prefix + std::string("test_input.bin");
+  
+  std::string labels_path = dir_prefix + std::string("test_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, 16, 3, 3, 3);
@@ -237,9 +236,9 @@ int main() {
     void *var_95 = tensorAdd(var_94, dense_1_b);
     void *var_96 = tensorSoftmax(var_95);
 
-    uint8_t *labels = readLabelsBatch(labels_path.c_str(), start, end);
+    uint32_t *labels = readLabelsBatch3(labels_path.c_str(), start, end);
 
-    float accuracy = computeAccuracy2(labels, batch_size, var_96);
+    float accuracy = computeAccuracy3(labels, var_96);
     final_accuracy += accuracy;
 
     freeBatchMemory();