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- # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ==============================================================================
- """Tests for slim.nets.nasnet.nasnet_utils."""
- from __future__ import absolute_import
- from __future__ import division
- from __future__ import print_function
- import tensorflow as tf
- from nets.nasnet import nasnet_utils
- class NasnetUtilsTest(tf.test.TestCase):
- def testCalcReductionLayers(self):
- num_cells = 18
- num_reduction_layers = 2
- reduction_layers = nasnet_utils.calc_reduction_layers(
- num_cells, num_reduction_layers)
- self.assertEqual(len(reduction_layers), 2)
- self.assertEqual(reduction_layers[0], 6)
- self.assertEqual(reduction_layers[1], 12)
- def testGetChannelIndex(self):
- data_formats = ['NHWC', 'NCHW']
- for data_format in data_formats:
- index = nasnet_utils.get_channel_index(data_format)
- correct_index = 3 if data_format == 'NHWC' else 1
- self.assertEqual(index, correct_index)
- def testGetChannelDim(self):
- data_formats = ['NHWC', 'NCHW']
- shape = [10, 20, 30, 40]
- for data_format in data_formats:
- dim = nasnet_utils.get_channel_dim(shape, data_format)
- correct_dim = shape[3] if data_format == 'NHWC' else shape[1]
- self.assertEqual(dim, correct_dim)
- def testGlobalAvgPool(self):
- data_formats = ['NHWC', 'NCHW']
- inputs = tf.placeholder(tf.float32, (5, 10, 20, 10))
- for data_format in data_formats:
- output = nasnet_utils.global_avg_pool(
- inputs, data_format)
- self.assertEqual(output.shape, [5, 10])
- if __name__ == '__main__':
- tf.test.main()
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