Searched refs:ReLU (Results 1 – 14 of 14) sorted by relevance
| /external/tensorflow/tensorflow/python/keras/layers/ |
| D | advanced_activations_test.py | 65 testing_utils.layer_test(keras.layers.ReLU,
72 'LeakyRelu' in keras.layers.ReLU(negative_slope=0.2)(x).name)
74 self.assertTrue('Relu' in keras.layers.ReLU()(x).name)
76 self.assertTrue('Relu6' in keras.layers.ReLU(max_value=6)(x).name)
81 testing_utils.layer_test(keras.layers.ReLU,
89 keras.layers.ReLU,
95 layer = keras.layers.Dense(1, activation=keras.layers.ReLU())
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| D | advanced_activations.py | 273 class ReLU(Layer): class
298 super(ReLU, self).__init__(**kwargs)
327 base_config = super(ReLU, self).get_config()
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| D | __init__.py | 32 from tensorflow.python.keras.layers.advanced_activations import ReLU
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| /external/tensorflow/tensorflow/tools/api/golden/v2/ |
| D | tensorflow.keras.layers.-re-l-u.pbtxt | 1 path: "tensorflow.keras.layers.ReLU"
3 is_instance: "<class \'tensorflow.python.keras.layers.advanced_activations.ReLU\'>"
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| D | tensorflow.keras.layers.pbtxt | 308 name: "ReLU"
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| /external/tensorflow/tensorflow/tools/api/golden/v1/ |
| D | tensorflow.keras.layers.-re-l-u.pbtxt | 1 path: "tensorflow.keras.layers.ReLU"
3 is_instance: "<class \'tensorflow.python.keras.layers.advanced_activations.ReLU\'>"
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| D | tensorflow.keras.layers.pbtxt | 312 name: "ReLU"
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| /external/libtextclassifier/lang_id/common/flatbuffers/ |
| D | embedding-network.fbs | 90 // this is not the first layer, we apply a nonlinear function (ReLU); for the
91 // first layer, we skip ReLU. Next, we multiply by |weights| and add |bias|,
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| /external/tensorflow/tensorflow/python/keras/engine/ |
| D | base_layer_test.py | 598 10, activation=keras.layers.ReLU(name='MyAct'), name='MyName2')
607 10, activation=keras.layers.ReLU(name='MyAct'), name='MyName3')
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| /external/tensorflow/tensorflow/contrib/specs/ |
| D | README.md | 168 This will stack four fully connected ReLU layers, sharing the same
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| /external/tensorflow/tensorflow/contrib/autograph/examples/notebooks/ |
| D | rnn_keras_estimator.ipynb | 227 " followed by a fully connected layer with ReLU activation.\n",
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| D | dev_summit_2018_demo.ipynb | 1148 " followed by a fully connected layer with ReLU activation.\n",
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| /external/tensorflow/ |
| D | RELEASE.md | 1185 Activation: rectified linear unit (ReLU)
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| /external/tensorflow/tensorflow/examples/tutorials/deepdream/ |
| D | deepdream.ipynb | 404 … "# Picking some internal layer. Note that we use outputs before applying the ReLU nonlinearity\n",
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