fix file paths

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 
 

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
 

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
 

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
     

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
 

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
 

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
 

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
 

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
 

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