diff --git a/hpvm/projects/keras/README.md b/hpvm/projects/keras/README.md
index 9cb2bb31236196f48555c47df4785d89dd386e42..892c8f0402c8c02acca50405b7305dd7ceefc89c 100644
--- a/hpvm/projects/keras/README.md
+++ b/hpvm/projects/keras/README.md
@@ -7,6 +7,7 @@
```
conda env create -f keras_environment.yml --name ${KERAS_ENV_NAME}
```
+Note: pip version MUST be > 19.3
### Activating Conda Environment:
@@ -30,14 +31,15 @@ List of benchmarks and the expected accuracies:
| Benchmark | Accuracy |
| ----------- | ----------- |
-| AlexNet-CIFAR10 | 79.03 |
-| AlexNet2-CIFAR10 | 84.87 |
-| AlexNet-ImageNet | 56.23 |
-| LeNet-MNIST | 99.11 |
-| MobileNet-CIFAR10 | 84.74 |
-| ResNet18-CIFAR10 | 89.48 |
-| VGG16-CIFAR10 | 89.58 |
-| VGG16-CIFAR100 | 67.46 |
+| AlexNet-CIFAR10 | 79.16 |
+| AlexNet2-CIFAR10 | 85.10 |
+| AlexNet-ImageNet | 56.23 | todo: fix broken
+| LeNet-MNIST | 99.11 | todo: fix broken
+| MobileNet-CIFAR10 | 82.40 |
+| ResNet18-CIFAR10 | 89.52 |
+| ResNet50-ImageNet | 74.50 |
+| VGG16-CIFAR10 | 89.42 |
+| VGG16-CIFAR100 | 66.20 |
| VGG16-ImageNet | 72.50 |
Activate conda environment (above) before running benchmarks
diff --git a/hpvm/projects/keras/src/Config.py b/hpvm/projects/keras/src/Config.py
index 9b0c4d07685cbb73808be3b91b2227cf16ef171d..2edc5c1add5542edabdd052097ccb4b45d608472 100644
--- a/hpvm/projects/keras/src/Config.py
+++ b/hpvm/projects/keras/src/Config.py
@@ -1,3 +1,3 @@
# Path Relative to Model Params Directory
-MODEL_PARAMS_DIR = "../../build/model_params/"
+MODEL_PARAMS_DIR = "../../../hpvm/test/dnn_benchmarks/model_params/"
diff --git a/hpvm/projects/keras/src/alexnet.py b/hpvm/projects/keras/src/alexnet.py
index 4682a96eb5e18b8ae79cb4a2ad645ae3665e4bff..4b23fd995ffcc5a4f3234566a8a76dac8c12c6aa 100644
--- a/hpvm/projects/keras/src/alexnet.py
+++ b/hpvm/projects/keras/src/alexnet.py
@@ -4,7 +4,6 @@ import glob
import numpy as np
import tensorflow as tf
-import cv2
import scipy
import scipy.io
import keras
@@ -56,7 +55,7 @@ class AlexNet_CIFAR10(Benchmark):
#model.add(Dense(256))
model.add(Dense(self.num_classes))
model.add(Activation('softmax'))
-
+
return model
@@ -69,8 +68,8 @@ class AlexNet_CIFAR10(Benchmark):
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_train = (X_train - mean) / (std + 1e-7)
+ X_val = (X_val - mean) / (std + 1e-7)
X_test = X_val[0:5000]
y_test = y_val[0:5000]
@@ -140,7 +139,7 @@ if __name__ == '__main__':
src_dir = 'data/alexnet_cifar10_src/'
num_classes = 10
batch_size = 500
-
+
model = AlexNet_CIFAR10('AlexNet_CIFAR10', reload_dir, keras_model_file, data_dir, src_dir, num_classes, batch_size)
model.run(sys.argv)
diff --git a/hpvm/projects/keras/src/alexnet2.py b/hpvm/projects/keras/src/alexnet2.py
index 8f068e4d6e1a264f52c8d9c02265ff91b6a4bf2e..de69d8c12972df7a1fa51338b30676ffafc65f4e 100644
--- a/hpvm/projects/keras/src/alexnet2.py
+++ b/hpvm/projects/keras/src/alexnet2.py
@@ -4,7 +4,6 @@ import glob
import numpy as np
import tensorflow as tf
-import cv2
import scipy
import scipy.io
import keras
@@ -68,8 +67,8 @@ class AlexNet2_CIFAR10(Benchmark):
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_train = (X_train - mean) / (std + 1e-7)
+ X_val = (X_val - mean) / (std + 1e-7)
X_test = X_val[0:5000]
y_test = y_val[0:5000]
diff --git a/hpvm/projects/keras/src/alexnet_imagenet.py b/hpvm/projects/keras/src/alexnet_imagenet.py
index 4c00650abd910ea622567d6090925f4a5ce67b42..c05f757a7ca44a86258e5b9d7889c4f45ea44d39 100644
--- a/hpvm/projects/keras/src/alexnet_imagenet.py
+++ b/hpvm/projects/keras/src/alexnet_imagenet.py
@@ -141,7 +141,7 @@ class AlexNet(Benchmark):
x = Activation('relu')(x)
x = Dense(self.num_classes)(x)
x = Activation('softmax')(x)
-
+
model = Model(input_layer, x)
return model
diff --git a/hpvm/projects/keras/src/lenet.py b/hpvm/projects/keras/src/lenet.py
index 72e77f756d83a5ade1b06b284132e7c24c928c63..0210baee268f5a0a3a2d8f36873d023380f7e5f2 100644
--- a/hpvm/projects/keras/src/lenet.py
+++ b/hpvm/projects/keras/src/lenet.py
@@ -4,7 +4,6 @@ import glob
import numpy as np
import tensorflow as tf
-import cv2
import scipy
import scipy.io
import keras
diff --git a/hpvm/projects/keras/src/mobilenet_cifar10.py b/hpvm/projects/keras/src/mobilenet_cifar10.py
index 2fba7612503ad3cb39893476e91dcb1a3452697a..367a4dfc6244228b7b1336d1a63044273cebd2fb 100644
--- a/hpvm/projects/keras/src/mobilenet_cifar10.py
+++ b/hpvm/projects/keras/src/mobilenet_cifar10.py
@@ -4,7 +4,6 @@ import glob
import numpy as np
import tensorflow as tf
-import cv2
import scipy
import scipy.io
import keras
@@ -45,7 +44,7 @@ class MobileNet_CIFAR10(Benchmark):
def _depthwise_conv_block(pointwise_conv_filters, alpha, depth_multiplier=1, strides=(1, 1)):
channel_axis = 1
- model.add(ZeroPadding2D(padding = ((1,1), (1,1) )))
+ model.add(ZeroPadding2D(padding=((1,1), (1,1))))
model.add(DepthwiseConv2D((3, 3),
padding='valid',
@@ -110,8 +109,8 @@ class MobileNet_CIFAR10(Benchmark):
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_train = (X_train - mean) / (std + 1e-7)
+ X_val = (X_val - mean) / (std + 1e-7)
X_test = X_val[0:5000]
y_test = y_val[0:5000]
diff --git a/hpvm/projects/keras/src/resnet18_cifar10.py b/hpvm/projects/keras/src/resnet18_cifar10.py
index 8842ff7c677cec0290a5a10e8bcef538355ac2ad..1367c0830bdb96f3d5a310c36ce9022e314eba03 100644
--- a/hpvm/projects/keras/src/resnet18_cifar10.py
+++ b/hpvm/projects/keras/src/resnet18_cifar10.py
@@ -39,7 +39,6 @@ import glob
import numpy as np
import tensorflow as tf
-#import cv2
import scipy
import scipy.io
import keras
@@ -443,8 +442,10 @@ class ResNet18_CIFAR10(Benchmark):
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_train = (X_train - mean) / (std + 1e-7)
+# X_val = (X_val - mean) / (std + 1e-7)
+ X_train = (X_train - mean)
+ X_val = (X_val - mean)
X_test = X_val[0:5000]
y_test = y_val[0:5000]
diff --git a/hpvm/projects/keras/src/vgg16_cifar10.py b/hpvm/projects/keras/src/vgg16_cifar10.py
index d8b26f9386e132359652e67123ca1d8080f303d9..873e23b766ffbd58c1d5db89141da60fee88126e 100644
--- a/hpvm/projects/keras/src/vgg16_cifar10.py
+++ b/hpvm/projects/keras/src/vgg16_cifar10.py
@@ -4,7 +4,6 @@ import glob
import numpy as np
import tensorflow as tf
-#import cv2
import scipy
import scipy.io
import keras
@@ -108,8 +107,8 @@ class VGG16_CIFAR10(Benchmark):
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_train = (X_train - mean) / (std + 1e-7)
+ X_val = (X_val - mean) / (std + 1e-7)
X_test = X_val[0:5000]
y_test = y_val[0:5000]
diff --git a/hpvm/projects/keras/src/vgg16_cifar100.py b/hpvm/projects/keras/src/vgg16_cifar100.py
index 0dd47ac992ad206d09126f282e527b18c97ec930..03bb852e00bb61a7b17836f5c4df5bbf56c4b466 100644
--- a/hpvm/projects/keras/src/vgg16_cifar100.py
+++ b/hpvm/projects/keras/src/vgg16_cifar100.py
@@ -4,7 +4,6 @@ import glob
import numpy as np
import tensorflow as tf
-#import cv2
import scipy
import scipy.io
import keras
@@ -124,8 +123,8 @@ class VGG16_CIFAR100(Benchmark):
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_train = (X_train - mean) / (std + 1e-7)
+ X_val = (X_val - mean) / (std + 1e-7)
X_test = X_val[0:5000]
y_test = y_val[0:5000]