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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 axial_layers."""
import tensorflow as tf
from deeplab2.model.layers import axial_layers
class AxialLayersTest(tf.test.TestCase):
def test_default_axial_attention_layer_output_shape(self):
layer = axial_layers.AxialAttention()
output = layer(tf.zeros([10, 5, 32]))
self.assertListEqual(output.get_shape().as_list(), [10, 5, 1024])
def test_axial_attention_2d_layer_output_shape(self):
layer = axial_layers.AxialAttention2D()
output = layer(tf.zeros([2, 5, 5, 32]))
self.assertListEqual(output.get_shape().as_list(), [2, 5, 5, 1024])
def test_change_filters_output_shape(self):
layer = axial_layers.AxialAttention2D(filters=32)
output = layer(tf.zeros([2, 5, 5, 32]))
self.assertListEqual(output.get_shape().as_list(), [2, 5, 5, 64])
def test_value_expansion_output_shape(self):
layer = axial_layers.AxialAttention2D(value_expansion=1)
output = layer(tf.zeros([2, 5, 5, 32]))
self.assertListEqual(output.get_shape().as_list(), [2, 5, 5, 512])
def test_global_attention_output_shape(self):
layer = axial_layers.GlobalAttention2D()
output = layer(tf.zeros([2, 5, 5, 32]))
self.assertListEqual(output.get_shape().as_list(), [2, 5, 5, 1024])
def test_stride_two_output_shape(self):
layer = axial_layers.AxialAttention2D(strides=2)
output = layer(tf.zeros([2, 5, 5, 32]))
self.assertListEqual(output.get_shape().as_list(), [2, 3, 3, 1024])
if __name__ == '__main__':
tf.test.main()
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