diff options
Diffstat (limited to 'tensorflow/python/keras/applications/mobilenet.py')
| -rw-r--r-- | tensorflow/python/keras/applications/mobilenet.py | 22 |
1 files changed, 4 insertions, 18 deletions
diff --git a/tensorflow/python/keras/applications/mobilenet.py b/tensorflow/python/keras/applications/mobilenet.py index e56c695a28..7285e03963 100644 --- a/tensorflow/python/keras/applications/mobilenet.py +++ b/tensorflow/python/keras/applications/mobilenet.py @@ -72,13 +72,9 @@ from __future__ import print_function import os from tensorflow.python.keras import backend as K -from tensorflow.python.keras import constraints -from tensorflow.python.keras import initializers -from tensorflow.python.keras import regularizers from tensorflow.python.keras.applications import imagenet_utils from tensorflow.python.keras.applications.imagenet_utils import _obtain_input_shape from tensorflow.python.keras.applications.imagenet_utils import decode_predictions -from tensorflow.python.keras.engine.base_layer import InputSpec from tensorflow.python.keras.layers import Activation from tensorflow.python.keras.layers import BatchNormalization from tensorflow.python.keras.layers import Conv2D @@ -87,10 +83,10 @@ from tensorflow.python.keras.layers import Dropout from tensorflow.python.keras.layers import GlobalAveragePooling2D from tensorflow.python.keras.layers import GlobalMaxPooling2D from tensorflow.python.keras.layers import Input +from tensorflow.python.keras.layers import ReLU from tensorflow.python.keras.layers import Reshape from tensorflow.python.keras.layers import ZeroPadding2D from tensorflow.python.keras.models import Model -from tensorflow.python.keras.utils import conv_utils from tensorflow.python.keras.utils import layer_utils from tensorflow.python.keras.utils.data_utils import get_file from tensorflow.python.platform import tf_logging as logging @@ -100,10 +96,6 @@ from tensorflow.python.util.tf_export import tf_export BASE_WEIGHT_PATH = 'https://github.com/fchollet/deep-learning-models/releases/download/v0.6/' -def relu6(x): - return K.relu(x, max_value=6) - - @tf_export('keras.applications.mobilenet.preprocess_input') def preprocess_input(x): """Preprocesses a numpy array encoding a batch of images. @@ -130,12 +122,6 @@ def MobileNet(input_shape=None, classes=1000): """Instantiates the MobileNet architecture. - To load a MobileNet model via `load_model`, import the custom - objects `relu6` and pass them to the `custom_objects` parameter. - E.g. - model = load_model('mobilenet.h5', custom_objects={ - 'relu6': mobilenet.relu6}) - Arguments: input_shape: optional shape tuple, only to be specified if `include_top` is False (otherwise the input shape @@ -412,7 +398,7 @@ def _conv_block(inputs, filters, alpha, kernel=(3, 3), strides=(1, 1)): strides=strides, name='conv1')(x) x = BatchNormalization(axis=channel_axis, name='conv1_bn')(x) - return Activation(relu6, name='conv1_relu')(x) + return ReLU(6, name='conv1_relu')(x) def _depthwise_conv_block(inputs, @@ -479,7 +465,7 @@ def _depthwise_conv_block(inputs, use_bias=False, name='conv_dw_%d' % block_id)(x) x = BatchNormalization(axis=channel_axis, name='conv_dw_%d_bn' % block_id)(x) - x = Activation(relu6, name='conv_dw_%d_relu' % block_id)(x) + x = ReLU(6, name='conv_dw_%d_relu' % block_id)(x) x = Conv2D( pointwise_conv_filters, (1, 1), @@ -489,4 +475,4 @@ def _depthwise_conv_block(inputs, name='conv_pw_%d' % block_id)( x) x = BatchNormalization(axis=channel_axis, name='conv_pw_%d_bn' % block_id)(x) - return Activation(relu6, name='conv_pw_%d_relu' % block_id)(x) + return ReLU(6, name='conv_pw_%d_relu' % block_id)(x) |