• Home
  • Line#
  • Scopes#
  • Navigate#
  • Raw
  • Download
1# Copyright 2021 Huawei Technologies Co., Ltd
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7# http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ============================================================================
15"""test cases for cauchy distribution"""
16
17import pytest
18import numpy as np
19import mindspore.context as context
20import mindspore.nn as nn
21import mindspore.nn.probability.distribution as msd
22from mindspore import Tensor
23from mindspore import dtype as ms
24
25context.set_context(mode=context.PYNATIVE_MODE, device_target="Ascend")
26
27
28class CauchyMean(nn.Cell):
29    def __init__(self, loc, scale, seed=10, dtype=ms.float32, name='Cauchy'):
30        super().__init__()
31        self.b = msd.Cauchy(loc, scale, seed, dtype, name)
32
33    def construct(self):
34        out4 = self.b.entropy()
35        return out4
36
37
38
39@pytest.mark.level1
40@pytest.mark.platform_arm_ascend_training
41@pytest.mark.env_onecard
42def test_probability_cauchy_mean_loc_scale_rand_2_ndarray():
43    loc = np.random.randn(1024, 512, 7, 7).astype(np.float32)
44    scale = np.random.uniform(0.0001, 100, size=(1024, 512, 7, 7)).astype(np.float32)
45    net = CauchyMean(loc, scale)
46    net()
47
48
49class CauchyProb(nn.Cell):
50    def __init__(self, loc, scale, seed=10, dtype=ms.float32, name='Cauchy'):
51        super().__init__()
52        self.b = msd.Cauchy(loc, scale, seed, dtype, name)
53
54    def construct(self, value):
55        out1 = self.b.prob(value)
56        out2 = self.b.log_prob(value)
57        out3 = self.b.cdf(value)
58        out4 = self.b.log_cdf(value)
59        out5 = self.b.survival_function(value)
60        out6 = self.b.log_survival(value)
61        return out1, out2, out3, out4, out5, out6
62
63
64@pytest.mark.level1
65@pytest.mark.platform_arm_ascend_training
66@pytest.mark.env_onecard
67def test_probability_cauchy_prob_cdf_loc_scale_rand_4_ndarray():
68    loc = np.random.randn(1024, 512, 7, 7).astype(np.float32)
69    scale = np.random.uniform(0.0001, 100, size=(1024, 512, 7, 7)).astype(np.float32)
70    value = np.random.randn(1024, 512, 7, 7).astype(np.float32)
71    net = CauchyProb(loc, scale)
72    net(Tensor(value))
73