wehub-resource-sync
159 lines
4.9 KiB
Python
159 lines
4.9 KiB
Python
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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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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# http://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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import unittest
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import mock_data as mock
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import numpy as np
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import parameterize as param
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import scipy.special
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import scipy.stats
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from distribution import config
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import paddle
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from paddle.distribution import kl
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np.random.seed(2022)
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paddle.seed(2022)
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paddle.set_default_dtype('float64')
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@param.place(config.DEVICES)
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@param.parameterize_cls(
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(param.TEST_CASE_NAME, 'a1', 'b1', 'a2', 'b2'),
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[
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(
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'test_regular_input',
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6.0 * np.random.random((4, 5)) + 1e-4,
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6.0 * np.random.random((4, 5)) + 1e-4,
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6.0 * np.random.random((4, 5)) + 1e-4,
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6.0 * np.random.random((4, 5)) + 1e-4,
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),
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],
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)
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class TestKLBetaBeta(unittest.TestCase):
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def setUp(self):
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self.p = paddle.distribution.Beta(
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paddle.to_tensor(self.a1), paddle.to_tensor(self.b1)
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)
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self.q = paddle.distribution.Beta(
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paddle.to_tensor(self.a2), paddle.to_tensor(self.b2)
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)
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def test_kl_divergence(self):
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with paddle.base.dygraph.guard(self.place):
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np.testing.assert_allclose(
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paddle.distribution.kl_divergence(self.p, self.q),
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self.scipy_kl_beta_beta(self.a1, self.b1, self.a2, self.b2),
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rtol=config.RTOL.get(str(self.a1.dtype)),
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atol=config.ATOL.get(str(self.a1.dtype)),
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)
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def scipy_kl_beta_beta(self, a1, b1, a2, b2):
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return (
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scipy.special.betaln(a2, b2)
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- scipy.special.betaln(a1, b1)
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+ (a1 - a2) * scipy.special.digamma(a1)
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+ (b1 - b2) * scipy.special.digamma(b1)
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+ (a2 - a1 + b2 - b1) * scipy.special.digamma(a1 + b1)
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)
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@param.place(config.DEVICES)
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@param.param_cls(
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(param.TEST_CASE_NAME, 'conc1', 'conc2'),
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[
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(
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'test-regular-input',
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np.random.random((5, 7, 8, 10)),
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np.random.random((5, 7, 8, 10)),
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),
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],
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)
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class TestKLDirichletDirichlet(unittest.TestCase):
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def setUp(self):
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self.p = paddle.distribution.Dirichlet(paddle.to_tensor(self.conc1))
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self.q = paddle.distribution.Dirichlet(paddle.to_tensor(self.conc2))
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def test_kl_divergence(self):
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with paddle.base.dygraph.guard(self.place):
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np.testing.assert_allclose(
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paddle.distribution.kl_divergence(self.p, self.q),
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self.scipy_kl_diric_diric(self.conc1, self.conc2),
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rtol=config.RTOL.get(str(self.conc1.dtype)),
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atol=config.ATOL.get(str(self.conc1.dtype)),
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)
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def scipy_kl_diric_diric(self, conc1, conc2):
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return (
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scipy.special.gammaln(np.sum(conc1, -1))
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- scipy.special.gammaln(np.sum(conc2, -1))
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- np.sum(
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scipy.special.gammaln(conc1) - scipy.special.gammaln(conc2), -1
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)
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+ np.sum(
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(conc1 - conc2)
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* (
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scipy.special.digamma(conc1)
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- scipy.special.digamma(np.sum(conc1, -1, keepdims=True))
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),
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-1,
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)
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)
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class DummyDistribution(paddle.distribution.Distribution):
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pass
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@param.place(config.DEVICES)
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@param.param_cls(
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(param.TEST_CASE_NAME, 'p', 'q'),
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[('test-unregister', DummyDistribution(), DummyDistribution)],
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)
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class TestDispatch(unittest.TestCase):
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def test_dispatch_with_unregister(self):
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with self.assertRaises(NotImplementedError):
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paddle.distribution.kl_divergence(self.p, self.q)
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@param.place(config.DEVICES)
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@param.param_cls(
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(param.TEST_CASE_NAME, 'p', 'q'),
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[
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(
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'test-diff-dist',
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mock.Exponential(paddle.rand((100, 200, 100)) + 1.0),
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mock.Exponential(paddle.rand((100, 200, 100)) + 2.0),
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),
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(
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'test-same-dist',
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mock.Exponential(paddle.to_tensor([1.0])),
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mock.Exponential(paddle.to_tensor([1.0])),
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),
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],
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)
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class TestKLExpfamilyExpFamily(unittest.TestCase):
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def test_kl_expfamily_expfamily(self):
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np.testing.assert_allclose(
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paddle.distribution.kl_divergence(self.p, self.q),
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kl._kl_expfamily_expfamily(self.p, self.q),
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rtol=config.RTOL.get(config.DEFAULT_DTYPE),
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atol=config.ATOL.get(config.DEFAULT_DTYPE),
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)
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if __name__ == '__main__':
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unittest.main()
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