diff --git a/hpvm/projects/keras/src/alexnet.py b/hpvm/projects/keras/src/alexnet.py
index 1d8778727b90b2e81f362cd2a75d641683a4d5b4..0eefe1b3d3dfa28cd009d74806a9bff41f6d597b 100644
--- a/hpvm/projects/keras/src/alexnet.py
+++ b/hpvm/projects/keras/src/alexnet.py
@@ -21,9 +21,11 @@ from Benchmark import Benchmark
from Config import MODEL_PARAMS_DIR
-
+# Inherits from Benchmark class defined in src/Benchmark.py
class AlexNet_CIFAR10(Benchmark):
+ # buildModel overrides the buildModel declared in src/Benchmark.py
+ # Goal: Build a Keras Sequential Model (other model types not supported) and return the (uninitalized/untrained) Model
def buildModel(self):
activation_type = 'tanh'
@@ -51,26 +53,23 @@ class AlexNet_CIFAR10(Benchmark):
model.add(Dropout(0.4))
model.add(Flatten())
- #model.add(Flatten())
- #model.add(Dense(256))
model.add(Dense(self.num_classes))
model.add(Activation('softmax'))
return model
-
+
+ # This routine is called from the common `run` method in src/Benchmark.py
+ # Goal: Return Training and Testing data after preprocessing/normalization
def data_preprocess(self):
(X_train, y_train), (X_val, y_val) = cifar10.load_data()
X_train = X_train / 255.0
- #X_val = X_val / 255.0
-
+
mean = np.mean(X_train)
std = np.std(X_train)
X_train = (X_train - mean) / (std + 1e-7)
- #X_val = (X_val - mean) / (std + 1e-7)
-
X_test = np.fromfile(MODEL_PARAMS_DIR + '/alexnet_cifar10/test_input.bin', dtype=np.float32)
y_test = np.fromfile(MODEL_PARAMS_DIR + '/alexnet_cifar10/test_labels.bin', dtype=np.uint32)
@@ -86,6 +85,7 @@ class AlexNet_CIFAR10(Benchmark):
return X_train, y_train, X_test, y_test, X_tuner, y_tuner
+ # Goal: Given a Keras Sequential Model - setup the training parameters, train, and return the trained Model
def trainModel(self, model, X_train, y_train, X_test, y_test):
y_train = to_categorical(y_train, self.num_classes)
@@ -133,23 +133,27 @@ class AlexNet_CIFAR10(Benchmark):
if __name__ == '__main__':
-
+
+ # Using GPU ID 0 - Change to use different GPU
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
- # Changing to NCHW format
+ # Changing to NCHW format - HPVM currently supports NCHW - NHWC format is not supported
K.set_image_data_format('channels_first')
- ### Parameters specific to each benchmark
+ # *** 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 = '/alexnet_cifar10/'
- data_dir = ''
- src_dir = 'data/alexnet_cifar10_src/'
- num_classes = 10
- batch_size = 500
-
+ data_dir = '' # 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
+ 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
+
+ # All Classes inherit from 'Benchmark` class in src/Benchmark.py and have a common Constructor
model = AlexNet_CIFAR10('AlexNet_CIFAR10', reload_dir, keras_model_file, data_dir, src_dir, num_classes, batch_size)
-
+
+ # This invokes the common run function in src/Benchmark.py
model.run(sys.argv)
diff --git a/hpvm/projects/keras/src/alexnet2.py b/hpvm/projects/keras/src/alexnet2.py
index 554caf06e413f410e303a8dbf8a64ebb47ecf56f..d2c7d566bb2793a848bdb88c19e2905e6030d588 100644
--- a/hpvm/projects/keras/src/alexnet2.py
+++ b/hpvm/projects/keras/src/alexnet2.py
@@ -137,7 +137,7 @@ 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 = '/alexnet2_cifar10/'
+ data_dir = ''
src_dir = 'data/alexnet2_cifar10_src/'
num_classes = 10
batch_size = 500
diff --git a/hpvm/projects/keras/src/alexnet_imagenet.py b/hpvm/projects/keras/src/alexnet_imagenet.py
index e3ab937e9bb355fde74a63664c8657c76d6343f5..1cfe7a79c2a1350689d09d07fdc50f3ce998d8af 100644
--- a/hpvm/projects/keras/src/alexnet_imagenet.py
+++ b/hpvm/projects/keras/src/alexnet_imagenet.py
@@ -94,7 +94,7 @@ 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 = '/alexnet_imagenet/'
+ data_dir = ''
src_dir = 'data/alexnet_imagenet_src/'
num_classes = 1000
batch_size = 50
@@ -104,4 +104,4 @@ if __name__ == '__main__':
model.run(sys.argv)
-
\ No newline at end of file
+
diff --git a/hpvm/projects/keras/src/lenet.py b/hpvm/projects/keras/src/lenet.py
index 01c84719e6b90d317f7e0dce012577b08b33fcbf..70dd73a66ad49cee83a0f061d1240522332c469c 100644
--- a/hpvm/projects/keras/src/lenet.py
+++ b/hpvm/projects/keras/src/lenet.py
@@ -103,7 +103,7 @@ 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 = '/lenet_mnist/'
+ data_dir = ''
src_dir = 'data/lenet_mnist_src/'
num_classes = 10
batch_size = 500
diff --git a/hpvm/projects/keras/src/mobilenet_cifar10.py b/hpvm/projects/keras/src/mobilenet_cifar10.py
index 2406e13435895b6b87b4d8565e2586172f562dbf..34335b0f1a7e3e414f7915a5eb9305086b7344d8 100644
--- a/hpvm/projects/keras/src/mobilenet_cifar10.py
+++ b/hpvm/projects/keras/src/mobilenet_cifar10.py
@@ -183,7 +183,7 @@ 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 = '/mobilenet_cifar10/'
+ data_dir = ''
src_dir = 'data/mobilenet_cifar10_src/'
num_classes = 10
batch_size = 500
diff --git a/hpvm/projects/keras/src/resnet18_cifar10.py b/hpvm/projects/keras/src/resnet18_cifar10.py
index 6f94a151e8b23912963df4c22ddab3940ae024af..02753f9eac83a252e5b128f29981b39c14f35d2c 100644
--- a/hpvm/projects/keras/src/resnet18_cifar10.py
+++ b/hpvm/projects/keras/src/resnet18_cifar10.py
@@ -555,7 +555,7 @@ 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 = '/resnet18_cifar10/'
+ data_dir = ''
src_dir = 'data/resnet18_cifar10_src/'
num_classes = 10
batch_size = 500
diff --git a/hpvm/projects/keras/src/resnet50_imagenet.py b/hpvm/projects/keras/src/resnet50_imagenet.py
index 0c3006213d7880f6133e1f8030256d50d25ea35d..de42ae48d834b6f55e7827138f60baeefe8fb897 100644
--- a/hpvm/projects/keras/src/resnet50_imagenet.py
+++ b/hpvm/projects/keras/src/resnet50_imagenet.py
@@ -142,7 +142,7 @@ 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 = '/resnet50_imagenet/'
+ data_dir = ''
src_dir = 'data/resnet50_imagenet_src/'
num_classes = 1000
batch_size = 50
@@ -152,4 +152,4 @@ if __name__ == '__main__':
model.run(sys.argv)
-
\ No newline at end of file
+
diff --git a/hpvm/projects/keras/src/vgg16_cifar10.py b/hpvm/projects/keras/src/vgg16_cifar10.py
index 9677fc2650b84ecc723865c3534d6d648eb70c1a..9a5071ee94a54e4832eade954f779d64ebd3416e 100644
--- a/hpvm/projects/keras/src/vgg16_cifar10.py
+++ b/hpvm/projects/keras/src/vgg16_cifar10.py
@@ -185,7 +185,7 @@ 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 = '/vgg16_cifar10/'
+ data_dir = ''
src_dir = 'data/vgg16_cifar10_src/'
num_classes = 10
batch_size = 500
diff --git a/hpvm/projects/keras/src/vgg16_cifar100.py b/hpvm/projects/keras/src/vgg16_cifar100.py
index 5d683929345ec5dac448d943c5d959c24736c171..0fd51ebe03c56ecd622cfab970c51f3096a7d2f4 100644
--- a/hpvm/projects/keras/src/vgg16_cifar100.py
+++ b/hpvm/projects/keras/src/vgg16_cifar100.py
@@ -200,7 +200,7 @@ 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 = '/vgg16_cifar100/'
+ data_dir = ''
src_dir = 'data/vgg16_cifar100_src/'
num_classes = 100
batch_size = 100
diff --git a/hpvm/projects/keras/src/vgg16_imagenet.py b/hpvm/projects/keras/src/vgg16_imagenet.py
index 35ab92479e545ba44cf2175cb7b8abcec84c4fed..8c27714fcf8799c5881e39a477c876cb2f0056a4 100644
--- a/hpvm/projects/keras/src/vgg16_imagenet.py
+++ b/hpvm/projects/keras/src/vgg16_imagenet.py
@@ -127,7 +127,7 @@ 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 = '/vgg16_imagenet/'
+ data_dir = ''
src_dir = 'data/vgg16_imagenet_src/'
num_classes = 1000
batch_size = 50
@@ -137,4 +137,4 @@ if __name__ == '__main__':
alexnet.run(sys.argv)
-
\ No newline at end of file
+