diff --git a/hpvm/test/dnn_benchmarks/keras/alexnet.py b/hpvm/test/dnn_benchmarks/keras/alexnet.py
index 0eefe1b3d3dfa28cd009d74806a9bff41f6d597b..7adfd5be5f2a91058e68ec39e6c73fe9d7b60492 100644
--- a/hpvm/test/dnn_benchmarks/keras/alexnet.py
+++ b/hpvm/test/dnn_benchmarks/keras/alexnet.py
@@ -143,10 +143,10 @@ if __name__ == '__main__':
     # *** Below are Parameters specific to each benchmark *****
     reload_dir = MODEL_PARAMS_DIR + '/alexnet_cifar10/'
     ## Either the HPVM weights are loaded (above) or the Keras Model from the path below 
-    keras_model_file = MODEL_PARAMS_DIR + '/alexnet_cifar10/weights.h5'
-    data_dir = ''   # if reloading weights, data_dir can be set to empty string (value is ignored)
+    keras_model_file = MODEL_PARAMS_DIR + '/alexnet_cifar10/model.h5'
+    data_dir = 'data/alexnet_cifar10_hpvm/'   # if reloading weights, data_dir can be set to empty string (value is ignored)
  
-    src_dir = 'data/alexnet_cifar10_src/'  # Directory where HPVM sources are downloaded
+    src_dir = 'src/alexnet_cifar10_src_hpvm/'  # Directory where HPVM sources are downloaded
     num_classes = 10  # Specify num out output classes - CIFAR10 has `10` classes
     batch_size = 500  # Batch Size set to 500 - Adjust this value based on your GPU memory 
 
diff --git a/hpvm/test/dnn_benchmarks/keras/alexnet2.py b/hpvm/test/dnn_benchmarks/keras/alexnet2.py
index d2c7d566bb2793a848bdb88c19e2905e6030d588..447d9d32ad6273c37b433a6bcc107613f164e68b 100644
--- a/hpvm/test/dnn_benchmarks/keras/alexnet2.py
+++ b/hpvm/test/dnn_benchmarks/keras/alexnet2.py
@@ -136,9 +136,9 @@ if __name__ == '__main__':
 
     ### Parameters specific to each benchmark
     reload_dir = MODEL_PARAMS_DIR + '/alexnet2_cifar10/'
-    keras_model_file = MODEL_PARAMS_DIR + '/alexnet2_cifar10/weights.h5'
-    data_dir = '' 
-    src_dir = 'data/alexnet2_cifar10_src/'
+    keras_model_file = MODEL_PARAMS_DIR + '/alexnet2_cifar10/model.h5'
+    data_dir = 'data/alexnet2_cifar10/' 
+    src_dir = 'src/alexnet2_cifar10_src/'
     num_classes = 10
     batch_size = 500
 
diff --git a/hpvm/test/dnn_benchmarks/keras/alexnet_imagenet.py b/hpvm/test/dnn_benchmarks/keras/alexnet_imagenet.py
index 1cfe7a79c2a1350689d09d07fdc50f3ce998d8af..9be1ff648c2ad27f99d4e1bccde8c4bb199dc174 100644
--- a/hpvm/test/dnn_benchmarks/keras/alexnet_imagenet.py
+++ b/hpvm/test/dnn_benchmarks/keras/alexnet_imagenet.py
@@ -93,9 +93,9 @@ if __name__ == '__main__':
 
     ### Parameters specific to each benchmark
     reload_dir = MODEL_PARAMS_DIR + '/alexnet_imagenet/'
-    keras_model_file = MODEL_PARAMS_DIR + '/alexnet_imagenet/weights.h5'
-    data_dir = '' 
-    src_dir = 'data/alexnet_imagenet_src/'
+    keras_model_file = MODEL_PARAMS_DIR + '/alexnet_imagenet/model.h5'
+    data_dir = 'data/alexnet_imagenet/' 
+    src_dir = 'src/alexnet_imagenet_src/'
     num_classes = 1000
     batch_size = 50
 
diff --git a/hpvm/test/dnn_benchmarks/keras/lenet.py b/hpvm/test/dnn_benchmarks/keras/lenet.py
index 70dd73a66ad49cee83a0f061d1240522332c469c..9de3c28b15aa097d1412880c21537c016a7392ef 100644
--- a/hpvm/test/dnn_benchmarks/keras/lenet.py
+++ b/hpvm/test/dnn_benchmarks/keras/lenet.py
@@ -102,9 +102,9 @@ if __name__ == '__main__':
 
     ### Parameters specific to each benchmark
     reload_dir = MODEL_PARAMS_DIR + '/lenet_mnist/'
-    keras_model_file = MODEL_PARAMS_DIR + '/lenet_mnist/weights.h5'
-    data_dir = '' 
-    src_dir = 'data/lenet_mnist_src/'
+    keras_model_file = MODEL_PARAMS_DIR + '/lenet_mnist/model.h5'
+    data_dir = 'data/lenet_mnist/' 
+    src_dir = 'src/lenet_mnist_src/'
     num_classes = 10
     batch_size = 500
     
diff --git a/hpvm/test/dnn_benchmarks/keras/mobilenet_cifar10.py b/hpvm/test/dnn_benchmarks/keras/mobilenet_cifar10.py
index 34335b0f1a7e3e414f7915a5eb9305086b7344d8..4987f3235f2458fc8ad78b7157941b648bc0e1c0 100644
--- a/hpvm/test/dnn_benchmarks/keras/mobilenet_cifar10.py
+++ b/hpvm/test/dnn_benchmarks/keras/mobilenet_cifar10.py
@@ -182,9 +182,9 @@ if __name__ == '__main__':
 
     ### Parameters specific to each benchmark
     reload_dir = MODEL_PARAMS_DIR + '/mobilenet_cifar10/'
-    keras_model_file = MODEL_PARAMS_DIR + '/mobilenet_cifar10/weights.h5'
-    data_dir = '' 
-    src_dir = 'data/mobilenet_cifar10_src/'
+    keras_model_file = MODEL_PARAMS_DIR + '/mobilenet_cifar10/model.h5'
+    data_dir = 'data/mobilenet_cifar10/' 
+    src_dir = 'src/mobilenet_cifar10_src/'
     num_classes = 10
     batch_size = 500
 
diff --git a/hpvm/test/dnn_benchmarks/keras/resnet18_cifar10.py b/hpvm/test/dnn_benchmarks/keras/resnet18_cifar10.py
index 02753f9eac83a252e5b128f29981b39c14f35d2c..1a77cf1b2ce91c16a775e4a99df13dec2282e247 100644
--- a/hpvm/test/dnn_benchmarks/keras/resnet18_cifar10.py
+++ b/hpvm/test/dnn_benchmarks/keras/resnet18_cifar10.py
@@ -554,9 +554,9 @@ if __name__ == '__main__':
 
     ### Parameters specific to each benchmark
     reload_dir = MODEL_PARAMS_DIR + '/resnet18_cifar10/'
-    keras_model_file = MODEL_PARAMS_DIR + '/resnet18_cifar10/weights.h5'
-    data_dir = '' 
-    src_dir = 'data/resnet18_cifar10_src/'
+    keras_model_file = MODEL_PARAMS_DIR + '/resnet18_cifar10/model.h5'
+    data_dir = 'data/resnet18_cifar10/' 
+    src_dir = 'src/resnet18_cifar10_src/'
     num_classes = 10
     batch_size = 500
 
diff --git a/hpvm/test/dnn_benchmarks/keras/resnet50_imagenet.py b/hpvm/test/dnn_benchmarks/keras/resnet50_imagenet.py
index de42ae48d834b6f55e7827138f60baeefe8fb897..6674faffab6e4c57b12607e01fda983b846dfa74 100644
--- a/hpvm/test/dnn_benchmarks/keras/resnet50_imagenet.py
+++ b/hpvm/test/dnn_benchmarks/keras/resnet50_imagenet.py
@@ -141,9 +141,9 @@ if __name__ == '__main__':
 
     ### Parameters specific to each benchmark
     reload_dir = MODEL_PARAMS_DIR + '/resnet50_imagenet/'
-    keras_model_file = MODEL_PARAMS_DIR + '/resnet50_imagenet/weights.h5'
-    data_dir = '' 
-    src_dir = 'data/resnet50_imagenet_src/'
+    keras_model_file = MODEL_PARAMS_DIR + '/resnet50_imagenet/model.h5'
+    data_dir = 'data/resnet50_imagenet/' 
+    src_dir = 'src/resnet50_imagenet_src/'
     num_classes = 1000
     batch_size = 50
 
diff --git a/hpvm/test/dnn_benchmarks/keras/vgg16_cifar10.py b/hpvm/test/dnn_benchmarks/keras/vgg16_cifar10.py
index 9a5071ee94a54e4832eade954f779d64ebd3416e..53207a039cafa9a89a34641ab887b21936c10ec1 100644
--- a/hpvm/test/dnn_benchmarks/keras/vgg16_cifar10.py
+++ b/hpvm/test/dnn_benchmarks/keras/vgg16_cifar10.py
@@ -184,9 +184,9 @@ if __name__ == '__main__':
 
     ### Parameters specific to each benchmark
     reload_dir = MODEL_PARAMS_DIR + '/vgg16_cifar10/'
-    keras_model_file = MODEL_PARAMS_DIR + '/vgg16_cifar10/weights.h5'
-    data_dir = '' 
-    src_dir = 'data/vgg16_cifar10_src/'
+    keras_model_file = MODEL_PARAMS_DIR + '/vgg16_cifar10/model.h5'
+    data_dir = 'data/vgg16_cifar10/' 
+    src_dir = 'src/vgg16_cifar10_src/'
     num_classes = 10
     batch_size = 500
 
diff --git a/hpvm/test/dnn_benchmarks/keras/vgg16_cifar100.py b/hpvm/test/dnn_benchmarks/keras/vgg16_cifar100.py
index 0fd51ebe03c56ecd622cfab970c51f3096a7d2f4..6fcfd3249e24ace232d5c5c6e70e5e8d2842f773 100644
--- a/hpvm/test/dnn_benchmarks/keras/vgg16_cifar100.py
+++ b/hpvm/test/dnn_benchmarks/keras/vgg16_cifar100.py
@@ -199,9 +199,9 @@ if __name__ == '__main__':
 
     ### Parameters specific to each benchmark
     reload_dir = MODEL_PARAMS_DIR + '/vgg16_cifar100/'
-    keras_model_file = MODEL_PARAMS_DIR + '/vgg16_cifar100/weights.h5'
-    data_dir = '' 
-    src_dir = 'data/vgg16_cifar100_src/'
+    keras_model_file = MODEL_PARAMS_DIR + '/vgg16_cifar100/model.h5'
+    data_dir = 'data/vgg16_cifar100/' 
+    src_dir = 'src/vgg16_cifar100_src/'
     num_classes = 100
     batch_size = 100
 
diff --git a/hpvm/test/dnn_benchmarks/keras/vgg16_imagenet.py b/hpvm/test/dnn_benchmarks/keras/vgg16_imagenet.py
index 6b9458b5378c421f5ef8f8811e4721056fd19643..a881d2340f93ed8dac2c86bdd57c1f7be5e1330f 100644
--- a/hpvm/test/dnn_benchmarks/keras/vgg16_imagenet.py
+++ b/hpvm/test/dnn_benchmarks/keras/vgg16_imagenet.py
@@ -126,9 +126,9 @@ if __name__ == '__main__':
 
     ### Parameters specific to each benchmark
     reload_dir = MODEL_PARAMS_DIR + '/vgg16_imagenet/'
-    keras_model_file = MODEL_PARAMS_DIR + '/vgg16_imagenet/weights.h5'
-    data_dir = '' 
-    src_dir = 'data/vgg16_imagenet_src/'
+    keras_model_file = MODEL_PARAMS_DIR + '/vgg16_imagenet/model.h5'
+    data_dir = 'data/vgg16_imagenet/' 
+    src_dir = 'src/vgg16_imagenet_src/'
     num_classes = 1000
     batch_size = 25