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    Searched defs:BatchNormalization (Results 1 - 4 of 4) sorted by null

  /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.py 55 set `axis=1` in `BatchNormalization`.
132 # By default, the base class uses V2 behavior. The BatchNormalization V1
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  /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
  /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`
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