54 lines
2.1 KiB
Python
54 lines
2.1 KiB
Python
# 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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"""Private base class for global pooling 3D layers."""
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import tensorflow.compat.v2 as tf
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from keras.engine.base_layer import Layer
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from keras.engine.input_spec import InputSpec
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from keras.utils import conv_utils
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class GlobalPooling3D(Layer):
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"""Abstract class for different global pooling 3D layers."""
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def __init__(self, data_format=None, keepdims=False, **kwargs):
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super().__init__(**kwargs)
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self.data_format = conv_utils.normalize_data_format(data_format)
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self.input_spec = InputSpec(ndim=5)
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self.keepdims = keepdims
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def compute_output_shape(self, input_shape):
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input_shape = tf.TensorShape(input_shape).as_list()
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if self.data_format == "channels_last":
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if self.keepdims:
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return tf.TensorShape([input_shape[0], 1, 1, 1, input_shape[4]])
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else:
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return tf.TensorShape([input_shape[0], input_shape[4]])
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else:
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if self.keepdims:
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return tf.TensorShape([input_shape[0], input_shape[1], 1, 1, 1])
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else:
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return tf.TensorShape([input_shape[0], input_shape[1]])
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def call(self, inputs):
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raise NotImplementedError
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def get_config(self):
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config = {"data_format": self.data_format, "keepdims": self.keepdims}
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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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