diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_imagenet.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_imagenet.cc
index 0f8df1a4207502b345aa02835a4d77368a35aa92..94da804e8aade0cd296a431b026be637c823201f 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_imagenet.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/alexnet_imagenet.cc
@@ -7,10 +7,10 @@ int main() {
 
   llvm_hpvm_initTensorRt(0);
 
-  std::string dir_prefix =
-      std::string("/home/nvidia/sd_card/alexnet_imagenet_tune/");
-  std::string input_path = dir_prefix + std::string("input.bin");
-  std::string labels_path = dir_prefix + std::string("labels.bin");
+  std::string dir_prefix = model_params_path + std::string("/alexnet_imagenet/");
+  
+  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, 64, 3, 11, 11);
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/mobilenet.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/mobilenet.cc
index 44336b02e0297f0ecbc37d3dccea8b97e766a357..618b418ec99418a3e02f446729d5dc2e244081d5 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/mobilenet.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/mobilenet.cc
@@ -7,9 +7,9 @@ int main() {
 
   llvm_hpvm_initTensorRt(0);
 
-  std::string dir_prefix = model_params_path + std::string("/mobilenet/");
-  std::string input_path = dir_prefix + std::string("input.bin");
-  std::string labels_path = dir_prefix + std::string("labels.bin");
+  std::string dir_prefix = model_params_path + std::string("/mobilenet_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, 32, 3, 3, 3);
@@ -709,9 +709,9 @@ int main() {
     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);
+    uint32_t *labels = readLabelsBatch3(labels_path.c_str(), start, end);
 
-    float accuracy = computeAccuracy2(labels, batch_size, var_103);
+    float accuracy = computeAccuracy3(labels, var_103);
     final_accuracy += accuracy;
     freeBatchMemory();
   }
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet50_imagenet.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet50_imagenet.cc
index afa3f0bcc1b08fc4a89c694e8e07e813b352ccbf..e19c0b21070807162c791a1a6389ccda87c23c8b 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet50_imagenet.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/resnet50_imagenet.cc
@@ -7,10 +7,10 @@ int main() {
 
   llvm_hpvm_initTensorRt(0);
 
-  std::string dir_prefix =
-      model_params_path + std::string("/shared/hsharif3/resnet50_imagenet/");
-  std::string input_path = dir_prefix + std::string("input.bin");
-  std::string labels_path = dir_prefix + std::string("labels.bin");
+  std::string dir_prefix = model_params_path + std::string("/resnet50_imagenet/");
+
+  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, 64, 3, 7, 7);
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar10.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar10.cc
index 034ddb0cf8d6b286544c669375a46746ad23d4d2..813874f0ed888ed5889b0574de454ca2720c944d 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar10.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar10.cc
@@ -8,8 +8,8 @@ int main() {
   llvm_hpvm_initTensorRt(0);
 
   std::string dir_prefix = model_params_path + std::string("/vgg16_cifar10/");
-  std::string input_path = dir_prefix + std::string("input.bin");
-  std::string labels_path = dir_prefix + std::string("labels.bin");
+  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, 64, 3, 3, 3);
@@ -164,9 +164,9 @@ int main() {
     void *var_59 = tensorAdd(var_58, dense_2_b);
     void *var_60 = tensorSoftmax(var_59);
 
-    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_60);
+    float accuracy = computeAccuracy3(labels, var_60);
     final_accuracy += accuracy;
 
     freeBatchMemory();
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar100.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar100.cc
index 94ca77329bc2f31d251590df3916d3cb10673fda..84164bf24bbff855b7a0975d7df2883e674b34c8 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar100.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_cifar100.cc
@@ -8,8 +8,8 @@ int main() {
   llvm_hpvm_initTensorRt(0);
 
   std::string dir_prefix = model_params_path + std::string("/vgg16_cifar100/");
-  std::string input_path = dir_prefix + std::string("input.bin");
-  std::string labels_path = dir_prefix + std::string("labels.bin");
+  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 =
@@ -165,9 +165,9 @@ int main() {
     void *var_59 = tensorAdd(var_58, dense_2_b);
     void *var_60 = tensorSoftmax(var_59);
 
-    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_60, 100);
+    float accuracy = computeAccuracy3(labels, var_60);
     final_accuracy += accuracy;
     freeBatchMemory();
   }
diff --git a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_imagenet.cc b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_imagenet.cc
index c5da3faf7860df24e25293acaacc1c50bcdceb72..eca833b08ff374e208f0cafabbf598cd0f7b5d90 100644
--- a/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_imagenet.cc
+++ b/hpvm/projects/hpvm-tensor-rt/dnn_sources/src/fp32/vgg16_imagenet.cc
@@ -7,10 +7,10 @@ int main() {
 
   llvm_hpvm_initTensorRt(0);
 
-  std::string dir_prefix =
-      std::string("/home/nvidia/sd_card/vgg16_imagenet_new/");
-  std::string input_path = dir_prefix + std::string("input.bin");
-  std::string labels_path = dir_prefix + std::string("labels.bin");
+  std::string dir_prefix = model_params_path + std::string("/vgg16_imagenet/");
+
+  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, 64, 3, 3, 3);