105 lines
3.2 KiB
Python
105 lines
3.2 KiB
Python
#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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# ==============================================================================
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#
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# Copyright (c) 2019, NVIDIA CORPORATION. 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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# ==============================================================================
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import tensorflow as tf
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from model.layers.utils import _log_hparams
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__all__ = ['average_pooling2d', 'max_pooling2d']
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def average_pooling2d(inputs, pool_size=(2, 2), strides=None, padding='valid', data_format=None, name="avg_pooling2d"):
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if data_format not in ['NHWC', 'NCHW']:
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raise ValueError("Unknown data format: `%s` (accepted: ['NHWC', 'NCHW'])" % data_format)
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if padding.lower() not in ['same', 'valid']:
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raise ValueError("Unknown padding: `%s` (accepted: ['same', 'valid'])" % padding)
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'''
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net = tf.keras.layers.AveragePooling2D(
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pool_size=pool_size,
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strides=strides,
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padding=padding,
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data_format='channels_first' if data_format == 'NCHW' else 'channels_last',
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name=name,
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)(inputs)
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'''
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net = tf.layers.average_pooling2d(
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inputs,
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pool_size=pool_size,
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strides=strides,
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padding=padding,
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data_format='channels_first' if data_format == 'NCHW' else 'channels_last',
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name=name
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)
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_log_hparams(
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classname='AveragePooling2D',
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layername=net.name,
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pool_size=pool_size,
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strides=strides,
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padding=padding,
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data_format=data_format,
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out_shape=str(net.get_shape())
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)
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return net
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def max_pooling2d(inputs, pool_size=(2, 2), strides=None, padding='valid', data_format=None, name="max_pooling2d"):
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if data_format not in ['NHWC', 'NCHW']:
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raise ValueError("Unknown data format: `%s` (accepted: ['NHWC', 'NCHW'])" % data_format)
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if padding.lower() not in ['same', 'valid']:
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raise ValueError("Unknown padding: `%s` (accepted: ['same', 'valid'])" % padding)
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'''
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net = tf.keras.layers.MaxPool2D(
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pool_size=pool_size,
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strides=strides,
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padding=padding,
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data_format='channels_first' if data_format == 'NCHW' else 'channels_last',
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name=name,
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)(inputs)
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'''
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net = tf.layers.max_pooling2d(
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inputs,
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pool_size=pool_size,
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strides=strides,
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padding=padding,
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data_format='channels_first' if data_format == 'NCHW' else 'channels_last',
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name=name
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)
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_log_hparams(
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classname='MaxPooling2D',
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layername=net.name,
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pool_size=pool_size,
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strides=strides,
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padding=padding,
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data_format=data_format,
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out_shape=str(net.get_shape()),
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out_dtype=net.dtype
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)
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return net
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