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74 lines
2.4 KiB
Python
74 lines
2.4 KiB
Python
# Copyright 2021 DeepMind Technologies Limited
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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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# https://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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"""Tests for io_processors."""
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import numpy as np
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import tensorflow as tf
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from perceiver import io_processors
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def _create_test_image(shape):
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image = np.arange(np.prod(np.array(shape)))
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return np.reshape(image, shape)
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def test_space_to_depth_image():
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image_shape = (2, 3 * 5, 3 * 7, 11)
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image = _create_test_image(image_shape)
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output = io_processors.space_to_depth(image, spatial_block_size=3)
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assert output.shape == (2, 5, 7, 3 * 3 * 11)
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def test_space_to_depth_video():
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image_shape = (2, 5 * 7, 3 * 11, 3 * 13, 17)
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image = _create_test_image(image_shape)
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output = io_processors.space_to_depth(image, spatial_block_size=3,
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temporal_block_size=5)
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assert output.shape == (2, 7, 11, 13, 5 * 3 * 3 * 17)
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def test_reverse_space_to_depth_image():
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image_shape = (2, 5, 7, 3 * 3 * 11)
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image = _create_test_image(image_shape)
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output = io_processors.reverse_space_to_depth(image, spatial_block_size=3)
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assert output.shape == (2, 3 * 5, 3 * 7, 11)
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def test_reverse_space_to_depth_video():
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image_shape = (2, 7, 11, 13, 5 * 3 * 3 * 17)
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image = _create_test_image(image_shape)
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output = io_processors.reverse_space_to_depth(
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image, spatial_block_size=3, temporal_block_size=5)
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assert output.shape == (2, 5 * 7, 3 * 11, 3 * 13, 17)
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def test_extract_patches():
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image_shape = (2, 5, 7, 3)
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image = _create_test_image(image_shape)
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sizes = [1, 2, 3, 1]
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strides = [1, 1, 2, 1]
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rates = [1, 2, 1, 1]
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for padding in ["VALID", "SAME"]:
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jax_patches = io_processors.extract_patches(
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image, sizes=sizes, strides=strides, rates=rates, padding=padding)
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tf_patches = tf.image.extract_patches(
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image, sizes=sizes, strides=strides, rates=rates, padding=padding)
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assert np.array_equal(
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np.array(jax_patches),
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tf_patches.numpy())
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