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deeplab2 / model /layers /resized_fuse_test.py

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	# coding=utf-8
	# Copyright 2021 The Deeplab2 Authors.
	#
	# 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 resized_fuse."""

	import tensorflow as tf

	from deeplab2.model.layers import resized_fuse


	class ResizedFuseTest(tf.test.TestCase):

	def test_resize_and_fuse_features(self):
	batch, height, width, channels = 2, 11, 11, 6
	smaller_height, smaller_width, smaller_channels = 6, 6, 3
	larger_height1, larger_width1 = 21, 21 # Stride 2 conv.
	larger_height2, larger_width2 = 22, 22 # Stride 2 conv.
	larger_height3, larger_width3 = 23, 23 # Conv and resize.

	feature_list = []
	feature_list.append(tf.zeros([batch, smaller_height, smaller_width,
	smaller_channels]))
	feature_list.append(tf.zeros([batch, smaller_height, smaller_width,
	channels]))
	feature_list.append(tf.zeros([batch, height, width, smaller_channels]))
	feature_list.append(tf.zeros([batch, height, width, channels]))
	feature_list.append(tf.zeros([batch, larger_height1, larger_width1,
	channels]))
	feature_list.append(tf.zeros([batch, larger_height1, larger_width1,
	smaller_channels]))
	feature_list.append(tf.zeros([batch, larger_height2, larger_width2,
	smaller_channels]))
	feature_list.append(tf.zeros([batch, larger_height3, larger_width3,
	smaller_channels]))
	layer = resized_fuse.ResizedFuse(name='fuse',
	height=height,
	width=width,
	num_channels=channels)
	output = layer(feature_list)
	self.assertEqual(output.get_shape().as_list(), [batch, height, width,
	channels])

	if __name__ == '__main__':
	tf.test.main()