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61 lines
2.1 KiB
Python
61 lines
2.1 KiB
Python
# Copyright 2020 DeepMind Technologies Limited.
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#
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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 tsm_utils."""
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from absl.testing import absltest
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from absl.testing import parameterized
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import jax.numpy as jnp
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import numpy as np
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from mmv.models import tsm_utils
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class TsmUtilsTest(parameterized.TestCase):
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@parameterized.parameters(
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((2, 32, 224, 224, 3), 'gpu', (2 * 32, 224, 224, 3), 32),
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((32, 224, 224, 3), 'tpu', (32, 224, 224, 3), None),
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)
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def test_prepare_inputs(self, input_shape, expected_mode, expected_shape,
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expected_num_frames):
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data = jnp.zeros(input_shape)
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out, mode, num_frames = tsm_utils.prepare_inputs(data)
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self.assertEqual(out.shape, expected_shape)
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self.assertEqual(mode, expected_mode)
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self.assertEqual(num_frames, expected_num_frames)
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def test_prepare_outputs(self):
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data = jnp.concatenate([jnp.zeros(4), jnp.ones(4)]).reshape(4, 2)
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out_gpu = tsm_utils.prepare_outputs(data, 'gpu', 2)
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out_tpu = tsm_utils.prepare_outputs(data, 'tpu', 2)
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expected_gpu = np.concatenate([np.zeros(2), np.ones(2)]).reshape(2, 2)
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expected_tpu = 0.5 * jnp.ones((2, 2))
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np.testing.assert_allclose(out_gpu, expected_gpu)
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np.testing.assert_allclose(out_tpu, expected_tpu)
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def test_apply_tsm(self):
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shape = (32, 224, 224, 16)
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data = jnp.zeros(shape)
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out_gpu = tsm_utils.apply_temporal_shift(data, 'gpu', 16)
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out_tpu = tsm_utils.apply_temporal_shift(data, 'tpu', 16)
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self.assertEqual(out_gpu.shape, shape)
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self.assertEqual(out_tpu.shape, shape)
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if __name__ == '__main__':
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absltest.main()
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