| /external/tensorflow/tensorflow/python/keras/wrappers/ |
| scikit_learn_test.py | 39 model.add(keras.layers.Activation('relu'))
41 model.add(keras.layers.Activation('relu'))
43 model.add(keras.layers.Activation('softmax'))
75 model.add(keras.layers.Activation('relu'))
77 model.add(keras.layers.Activation('relu'))
79 model.add(keras.layers.Activation('linear'))
|
| /external/tensorflow/tensorflow/core/kernels/ |
| conv_ops_fused_impl.h | 18 // - Conv2D + BiasAdd + <Activation>
19 // - Conv2D + FusedBatchNorm + <Activation>
21 // Activation: Relu, Relu6, Elu, etc...
75 // identity activation function, it in theory should allow to fuse convolution
77 // and always does Relu activation.
156 // contraction + activation function defined by Activation.
157 template <typename T, typename Activation = Identity>
175 output = Activation::template apply<decltype(expr)>(expr);
184 // contraction + activation function defined by Activation
[all...] |
| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| blocks.py | 58 batch_norm_first: whether to apply activation and batch norm before conv
132 batch_norm_first: whether to apply activation and batch norm before conv
281 batch_norm_first: whether to apply activation and batch norm before conv
363 batch_norm_first: whether to apply activation and batch norm before conv
433 self.activation = tf.keras.layers.Activation("relu")
447 net = self.activation(net)
491 self.activation = tf.keras.layers.Activation("relu")
500 net = self.activation(net
[all...] |
| /external/tensorflow/tensorflow/python/keras/layers/ |
| core_test.py | 248 keras.layers.Activation,
249 kwargs={'activation': 'relu'},
254 keras.layers.Activation,
255 kwargs={'activation': keras.backend.relu},
|
| core.py | 336 @keras_export('keras.layers.Activation')
337 class Activation(Layer):
338 """Applies an activation function to an output.
341 activation: Activation function, such as `tf.nn.relu`, or string name of
342 built-in activation function, such as "relu".
353 def __init__(self, activation, **kwargs):
354 super(Activation, self).__init__(**kwargs)
356 self.activation = activations.get(activation)
[all...] |
| wrappers_test.py | 124 model.add(keras.layers.Activation('relu'))
139 model.add(keras.layers.Activation('relu'))
155 model.add(keras.layers.Activation('relu'))
|
| __init__.py | 72 from tensorflow.python.keras.layers.core import Activation
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| summary_ops_test.py | 43 from tensorflow.python.keras.layers.core import Activation
[all...] |
| /external/tensorflow/tensorflow/contrib/keras/api/keras/layers/ |
| __init__.py | 70 from tensorflow.python.keras.layers.core import Activation
|
| /external/v8/src/wasm/ |
| wasm-interpreter.cc | [all...] |
| /external/tensorflow/tensorflow/python/keras/engine/ |
| base_layer_test.py | 225 keras.layers.Dense(3, activation='relu', kernel_initializer='ones'),
226 keras.layers.Dense(1, activation='sigmoid', kernel_initializer='ones')
598 10, activation=keras.layers.ReLU(name='MyAct'), name='MyName2')
607 10, activation=keras.layers.ReLU(name='MyAct'), name='MyName3')
615 (keras.layers.Activation, (2, 2),
616 collections.OrderedDict(activation=['relu'])),
630 activation=[None, 'relu'],
|
| training_test.py | 483 10, activation='relu', activity_regularizer=reg,
486 1, activation='sigmoid', kernel_initializer='ones',
524 10, activation='relu', activity_regularizer='l2')(
526 outputs = keras.layers.Dense(1, activation='sigmoid')(x)
767 model.add(keras.layers.Dense(10, activation='relu'))
768 model.add(keras.layers.Dense(1, activation='sigmoid'))
820 outputs = keras.layers.Dense(1, activation='sigmoid')(inputs)
840 outputs = keras.layers.Dense(1, activation='sigmoid')(inputs)
[all...] |
| /external/tensorflow/tensorflow/python/keras/saving/ |
| saved_model_test.py | 425 outputs = keras.layers.Activation(relu6)(inputs)
|
| /external/libjpeg-turbo/doc/html/search/ |
| search.js | 403 // -------- Activation Functions
|
| /external/tinyxml2/docs/search/ |
| search.js | 370 // -------- Activation Functions
|
| /external/tensorflow/tensorflow/python/ops/ |
| nn_impl.py | 366 """Computes the Swish activation function: `x * sigmoid(x)`.
368 Source: "Searching for Activation Functions" (Ramachandran et al. 2017)
376 The activation value.
[all...] |
