57 lines
1.9 KiB
Python
57 lines
1.9 KiB
Python
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# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""Contains the ActivityRegularization layer."""
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from keras import regularizers
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from keras.engine.base_layer import Layer
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# isort: off
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from tensorflow.python.util.tf_export import keras_export
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@keras_export("keras.layers.ActivityRegularization")
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class ActivityRegularization(Layer):
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"""Layer that applies an update to the cost function based input activity.
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Args:
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l1: L1 regularization factor (positive float).
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l2: L2 regularization factor (positive float).
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Input shape:
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Arbitrary. Use the keyword argument `input_shape`
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(tuple of integers, does not include the samples axis)
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when using this layer as the first layer in a model.
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Output shape:
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Same shape as input.
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"""
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def __init__(self, l1=0.0, l2=0.0, **kwargs):
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super().__init__(
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activity_regularizer=regularizers.L1L2(l1=l1, l2=l2), **kwargs
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)
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self.supports_masking = True
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self.l1 = l1
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self.l2 = l2
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def compute_output_shape(self, input_shape):
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return input_shape
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def get_config(self):
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config = {"l1": self.l1, "l2": self.l2}
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base_config = super().get_config()
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return dict(list(base_config.items()) + list(config.items()))
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