| /external/tensorflow/tensorflow/python/keras/layers/ |
| normalization_v2.py | 25 @keras_export('keras.layers.BatchNormalization', v1=[]) # pylint: disable=missing-docstring
26 class BatchNormalization(BatchNormalizationBase):
|
| normalization_test.py | 41 keras.layers.BatchNormalization,
50 keras.layers.BatchNormalization,
59 keras.layers.BatchNormalization,
66 layer = keras.layers.BatchNormalization(scale=False, center=False)
71 layer = keras.layers.BatchNormalization()
78 layer = keras.layers.BatchNormalization(
83 layer = keras.layers.BatchNormalization(
94 norm = keras.layers.BatchNormalization(
114 norm = keras.layers.BatchNormalization(
134 normalization.BatchNormalization, dtype='float32'
[all...] |
| serialization_test.py | 53 [batchnorm_v1.BatchNormalization, batchnorm_v2.BatchNormalization])
58 self.assertEqual(config['class_name'], 'BatchNormalization')
62 self.assertIsInstance(new_layer, batchnorm_v2.BatchNormalization)
66 self.assertIsInstance(new_layer, batchnorm_v1.BatchNormalization)
|
| __init__.py | 113 from tensorflow.python.keras.layers.normalization import BatchNormalization
114 from tensorflow.python.keras.layers.normalization_v2 import BatchNormalization as BatchNormalizationV2
|
| wrappers_test.py | 164 keras.layers.BatchNormalization(center=True, scale=True),
184 layer = keras.layers.TimeDistributed(keras.layers.BatchNormalization())
|
| /external/tensorflow/tensorflow/python/layers/ |
| normalization.py | 30 @tf_export(v1=['layers.BatchNormalization'])
31 class BatchNormalization(keras_layers.BatchNormalization, base.Layer):
130 super(BatchNormalization, self).__init__(
155 return super(BatchNormalization, self).call(inputs, training=training)
159 date=None, instructions='Use keras.layers.BatchNormalization instead.')
215 `data_format="channels_first"`, set `axis=1` in `BatchNormalization`.
288 layer = BatchNormalization(
317 BatchNorm = BatchNormalization
|
| normalization_test.py | 52 bn_layer = normalization_layers.BatchNormalization(fused=fused)
262 bn = normalization_layers.BatchNormalization(axis=1)
288 bn = normalization_layers.BatchNormalization(axis=1, fused=True)
317 bn = normalization_layers.BatchNormalization(
360 bn = normalization_layers.BatchNormalization(
402 bn = normalization_layers.BatchNormalization(
443 bn = normalization_layers.BatchNormalization(
484 bn = normalization_layers.BatchNormalization(
525 bn = normalization_layers.BatchNormalization(
567 bn = normalization_layers.BatchNormalization(
[all...] |
| layers.py | 77 from tensorflow.python.layers.normalization import BatchNormalization
|
| /external/tensorflow/tensorflow/contrib/distributions/python/kernel_tests/bijectors/ |
| batch_normalization_test.py | 25 from tensorflow.contrib.distributions.python.ops.bijectors.batch_normalization import BatchNormalization
76 layer = normalization.BatchNormalization(
78 batch_norm = BatchNormalization(
150 batch_norm = BatchNormalization(training=True)
180 layer = normalization.BatchNormalization(epsilon=0.)
181 batch_norm = BatchNormalization(batchnorm_layer=layer, training=False)
200 layer = normalization.BatchNormalization(epsilon=0.)
201 batch_norm = BatchNormalization(batchnorm_layer=layer, training=False)
219 layer = normalization.BatchNormalization(epsilon=0.)
221 BatchNormalization(batchnorm_layer=layer, training=False)
[all...] |
| /external/tensorflow/tensorflow/contrib/eager/python/examples/resnet50/ |
| resnet50.py | 56 self.bn2a = layers.BatchNormalization(
65 self.bn2b = layers.BatchNormalization(
70 self.bn2c = layers.BatchNormalization(
123 self.bn2a = layers.BatchNormalization(
132 self.bn2b = layers.BatchNormalization(
137 self.bn2c = layers.BatchNormalization(
145 self.bn_shortcut = layers.BatchNormalization(
231 self.bn_conv1 = layers.BatchNormalization(axis=bn_axis, name='bn_conv1')
|
| /external/tensorflow/tensorflow/contrib/distributions/python/ops/bijectors/ |
| batch_normalization.py | 34 "BatchNormalization",
85 class BatchNormalization(bijector.Bijector):
96 The `inverse()` method of the `BatchNormalization` bijector, which is used in
156 batchnorm_layer: `tf.layers.BatchNormalization` layer object. If `None`,
158 `tf.layers.BatchNormalization(gamma_constraint=nn_ops.relu(x) + 1e-6)`.
168 `tf.layers.BatchNormalization`, or if it is specified with `renorm=True`
173 self.batchnorm = batchnorm_layer or normalization.BatchNormalization(
181 super(BatchNormalization, self).__init__(
186 """Check for valid BatchNormalization layer.
189 layer: Instance of `tf.layers.BatchNormalization`
[all...] |
| /external/tensorflow/tensorflow/contrib/eager/python/examples/densenet/ |
| densenet.py | 56 self.batchnorm1 = tf.keras.layers.BatchNormalization(axis=axis)
67 self.batchnorm2 = tf.keras.layers.BatchNormalization(axis=axis)
97 self.batchnorm = tf.keras.layers.BatchNormalization(axis=axis)
238 self.batchnorm1 = tf.keras.layers.BatchNormalization(axis=axis)
240 self.batchnorm2 = tf.keras.layers.BatchNormalization(axis=axis)
|
| /external/tensorflow/tensorflow/contrib/eager/python/examples/revnet/ |
| blocks.py | 289 self.batch_norm_0 = tf.keras.layers.BatchNormalization(
301 self.batch_norm_1 = tf.keras.layers.BatchNormalization(
312 self.batch_norm_2 = tf.keras.layers.BatchNormalization(
371 self.batch_norm_0 = tf.keras.layers.BatchNormalization(
383 self.batch_norm_1 = tf.keras.layers.BatchNormalization(
431 self.batch_norm = tf.keras.layers.BatchNormalization(
486 self.batch_norm = tf.keras.layers.BatchNormalization(
|
| /external/tensorflow/tensorflow/python/keras/ |
| model_subclassing_test.py | 60 self.bn = keras.layers.BatchNormalization(axis=-1)
101 self.bn = keras.layers.BatchNormalization()
123 self.bn = keras.layers.BatchNormalization()
139 x = keras.layers.BatchNormalization()(x)
153 self.bn = self.bn = keras.layers.BatchNormalization()
169 x = keras.layers.BatchNormalization()(x)
177 self.bn = keras.layers.BatchNormalization()
689 self.bn = keras.layers.BatchNormalization(beta_initializer='ones',
924 self.bn = keras.layers.BatchNormalization()
[all...] |
| integration_test.py | 82 keras.layers.BatchNormalization()],
186 keras.layers.BatchNormalization(),
|
| callbacks_v1_test.py | 84 model.add(keras.layers.BatchNormalization())
280 model.add(keras.layers.BatchNormalization())
|
| models_test.py | 68 keras.layers.BatchNormalization(),
169 x_a = keras.layers.BatchNormalization()(x_a)
|
| /external/tensorflow/tensorflow/contrib/distribute/python/ |
| keras_image_model_correctness_test.py | 40 c1 = keras.layers.BatchNormalization(name='bn1')(c1)
|
| single_loss_example.py | 105 batchnorm = normalization.BatchNormalization(
|
| keras_utils_test.py | 459 norm = keras.layers.BatchNormalization(
|
| /external/tensorflow/tensorflow/python/training/tracking/ |
| data_structures_test.py | 62 (normalization.BatchNormalization(),))
415 normalization.BatchNormalization())
417 normalization.BatchNormalization())
|
| /external/tensorflow/tensorflow/contrib/keras/api/keras/layers/ |
| __init__.py | 106 from tensorflow.python.keras.layers.normalization import BatchNormalization
|
| /external/tensorflow/tensorflow/python/keras/engine/ |
| base_layer_test.py | 474 self.dense2 = keras.layers.BatchNormalization()
618 (keras.layers.BatchNormalization, (8, 8, 3), collections.OrderedDict(
|
| sequential_test.py | 250 model.add(keras.layers.BatchNormalization(input_shape=(4,)))
|
| topology_test.py | 113 layer = keras.layers.BatchNormalization()
[all...] |
