wehub-resource-sync
128 lines
4.5 KiB
Python
128 lines
4.5 KiB
Python
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# 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.
|
|
import numbers
|
|
import unittest
|
|
|
|
import numpy as np
|
|
import scipy.stats
|
|
from distribution.config import ATOL, DEVICES, RTOL
|
|
from parameterize import TEST_CASE_NAME, parameterize_cls, place, xrand
|
|
|
|
import paddle
|
|
|
|
np.random.seed(2022)
|
|
|
|
|
|
@place(DEVICES)
|
|
@parameterize_cls(
|
|
(TEST_CASE_NAME, 'alpha', 'beta'),
|
|
[
|
|
('test-scale', 1.0, 2.0),
|
|
('test-tensor', xrand(), xrand()),
|
|
('test-broadcast', xrand((2, 1)), xrand((2, 5))),
|
|
],
|
|
)
|
|
class TestBeta(unittest.TestCase):
|
|
def setUp(self):
|
|
# scale no need convert to tensor for scale input unittest
|
|
alpha, beta = self.alpha, self.beta
|
|
if not isinstance(self.alpha, numbers.Real):
|
|
alpha = paddle.to_tensor(self.alpha)
|
|
if not isinstance(self.beta, numbers.Real):
|
|
beta = paddle.to_tensor(self.beta)
|
|
|
|
self._paddle_beta = paddle.distribution.Beta(alpha, beta)
|
|
|
|
def test_mean(self):
|
|
with paddle.base.dygraph.guard(self.place):
|
|
np.testing.assert_allclose(
|
|
self._paddle_beta.mean,
|
|
scipy.stats.beta.mean(self.alpha, self.beta),
|
|
rtol=RTOL.get(str(self._paddle_beta.alpha.numpy().dtype)),
|
|
atol=ATOL.get(str(self._paddle_beta.alpha.numpy().dtype)),
|
|
)
|
|
|
|
def test_variance(self):
|
|
with paddle.base.dygraph.guard(self.place):
|
|
np.testing.assert_allclose(
|
|
self._paddle_beta.variance,
|
|
scipy.stats.beta.var(self.alpha, self.beta),
|
|
rtol=RTOL.get(str(self._paddle_beta.alpha.numpy().dtype)),
|
|
atol=ATOL.get(str(self._paddle_beta.alpha.numpy().dtype)),
|
|
)
|
|
|
|
def test_prob(self):
|
|
value = [np.random.rand(*self._paddle_beta.alpha.shape)]
|
|
|
|
for v in value:
|
|
with paddle.base.dygraph.guard(self.place):
|
|
np.testing.assert_allclose(
|
|
self._paddle_beta.prob(paddle.to_tensor(v)),
|
|
scipy.stats.beta.pdf(v, self.alpha, self.beta),
|
|
rtol=RTOL.get(str(self._paddle_beta.alpha.numpy().dtype)),
|
|
atol=ATOL.get(str(self._paddle_beta.alpha.numpy().dtype)),
|
|
)
|
|
|
|
def test_log_prob(self):
|
|
value = [np.random.rand(*self._paddle_beta.alpha.shape)]
|
|
|
|
for v in value:
|
|
with paddle.base.dygraph.guard(self.place):
|
|
np.testing.assert_allclose(
|
|
self._paddle_beta.log_prob(paddle.to_tensor(v)),
|
|
scipy.stats.beta.logpdf(v, self.alpha, self.beta),
|
|
rtol=RTOL.get(str(self._paddle_beta.alpha.numpy().dtype)),
|
|
atol=ATOL.get(str(self._paddle_beta.alpha.numpy().dtype)),
|
|
)
|
|
|
|
def test_entropy(self):
|
|
with paddle.base.dygraph.guard(self.place):
|
|
np.testing.assert_allclose(
|
|
self._paddle_beta.entropy(),
|
|
scipy.stats.beta.entropy(self.alpha, self.beta),
|
|
rtol=RTOL.get(str(self._paddle_beta.alpha.numpy().dtype)),
|
|
atol=ATOL.get(str(self._paddle_beta.alpha.numpy().dtype)),
|
|
)
|
|
|
|
def test_sample_shape(self):
|
|
cases = [
|
|
{
|
|
'input': [],
|
|
'expect': list(paddle.squeeze(self._paddle_beta.alpha).shape),
|
|
},
|
|
{
|
|
'input': [2, 3],
|
|
'expect': [
|
|
2,
|
|
3,
|
|
*paddle.squeeze(self._paddle_beta.alpha).shape,
|
|
],
|
|
},
|
|
]
|
|
for case in cases:
|
|
self.assertTrue(
|
|
self._paddle_beta.sample(case.get('input')).shape
|
|
== case.get('expect')
|
|
)
|
|
|
|
def test_errors(self):
|
|
with self.assertRaises(ValueError):
|
|
array = np.array([], dtype=np.float32)
|
|
x = paddle.to_tensor(np.reshape(array, [0]), dtype='int32')
|
|
paddle.distribution.Beta(alpha=x, beta=x)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|