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1# Copyright 2020 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"""
16Test nn.probability.distribution.Geometric.
17"""
18import pytest
19
20import mindspore.nn as nn
21import mindspore.nn.probability.distribution as msd
22from mindspore import dtype
23from mindspore import Tensor
24
25
26def test_arguments():
27    """
28    Args passing during initialization.
29    """
30    g = msd.Geometric()
31    assert isinstance(g, msd.Distribution)
32    g = msd.Geometric([0.1, 0.3, 0.5, 0.9], dtype=dtype.int32)
33    assert isinstance(g, msd.Distribution)
34
35
36def test_type():
37    with pytest.raises(TypeError):
38        msd.Geometric([0.1], dtype=dtype.bool_)
39
40
41def test_name():
42    with pytest.raises(TypeError):
43        msd.Geometric([0.1], name=1.0)
44
45
46def test_seed():
47    with pytest.raises(TypeError):
48        msd.Geometric([0.1], seed='seed')
49
50
51def test_prob():
52    """
53    Invalid probability.
54    """
55    with pytest.raises(ValueError):
56        msd.Geometric([-0.1], dtype=dtype.int32)
57    with pytest.raises(ValueError):
58        msd.Geometric([1.1], dtype=dtype.int32)
59    with pytest.raises(ValueError):
60        msd.Geometric([0.0], dtype=dtype.int32)
61    with pytest.raises(ValueError):
62        msd.Geometric([1.0], dtype=dtype.int32)
63
64
65class GeometricProb(nn.Cell):
66    """
67    Geometric distribution: initialize with probs.
68    """
69
70    def __init__(self):
71        super(GeometricProb, self).__init__()
72        self.g = msd.Geometric(0.5, dtype=dtype.int32)
73
74    def construct(self, value):
75        prob = self.g.prob(value)
76        log_prob = self.g.log_prob(value)
77        cdf = self.g.cdf(value)
78        log_cdf = self.g.log_cdf(value)
79        sf = self.g.survival_function(value)
80        log_sf = self.g.log_survival(value)
81        return prob + log_prob + cdf + log_cdf + sf + log_sf
82
83
84def test_geometric_prob():
85    """
86    Test probability functions: passing value through construct.
87    """
88    net = GeometricProb()
89    value = Tensor([3, 4, 5, 6, 7], dtype=dtype.float32)
90    ans = net(value)
91    assert isinstance(ans, Tensor)
92
93
94class GeometricProb1(nn.Cell):
95    """
96    Geometric distribution: initialize without probs.
97    """
98
99    def __init__(self):
100        super(GeometricProb1, self).__init__()
101        self.g = msd.Geometric(dtype=dtype.int32)
102
103    def construct(self, value, probs):
104        prob = self.g.prob(value, probs)
105        log_prob = self.g.log_prob(value, probs)
106        cdf = self.g.cdf(value, probs)
107        log_cdf = self.g.log_cdf(value, probs)
108        sf = self.g.survival_function(value, probs)
109        log_sf = self.g.log_survival(value, probs)
110        return prob + log_prob + cdf + log_cdf + sf + log_sf
111
112
113def test_geometric_prob1():
114    """
115    Test probability functions: passing value/probs through construct.
116    """
117    net = GeometricProb1()
118    value = Tensor([3, 4, 5, 6, 7], dtype=dtype.float32)
119    probs = Tensor([0.5], dtype=dtype.float32)
120    ans = net(value, probs)
121    assert isinstance(ans, Tensor)
122
123
124class GeometricKl(nn.Cell):
125    """
126    Test class: kl_loss between Geometric distributions.
127    """
128
129    def __init__(self):
130        super(GeometricKl, self).__init__()
131        self.g1 = msd.Geometric(0.7, dtype=dtype.int32)
132        self.g2 = msd.Geometric(dtype=dtype.int32)
133
134    def construct(self, probs_b, probs_a):
135        kl1 = self.g1.kl_loss('Geometric', probs_b)
136        kl2 = self.g2.kl_loss('Geometric', probs_b, probs_a)
137        return kl1 + kl2
138
139
140def test_kl():
141    """
142    Test kl_loss function.
143    """
144    ber_net = GeometricKl()
145    probs_b = Tensor([0.3], dtype=dtype.float32)
146    probs_a = Tensor([0.7], dtype=dtype.float32)
147    ans = ber_net(probs_b, probs_a)
148    assert isinstance(ans, Tensor)
149
150
151class GeometricCrossEntropy(nn.Cell):
152    """
153    Test class: cross_entropy of Geometric distribution.
154    """
155
156    def __init__(self):
157        super(GeometricCrossEntropy, self).__init__()
158        self.g1 = msd.Geometric(0.3, dtype=dtype.int32)
159        self.g2 = msd.Geometric(dtype=dtype.int32)
160
161    def construct(self, probs_b, probs_a):
162        h1 = self.g1.cross_entropy('Geometric', probs_b)
163        h2 = self.g2.cross_entropy('Geometric', probs_b, probs_a)
164        return h1 + h2
165
166
167def test_cross_entropy():
168    """
169    Test cross_entropy between Geometric distributions.
170    """
171    net = GeometricCrossEntropy()
172    probs_b = Tensor([0.3], dtype=dtype.float32)
173    probs_a = Tensor([0.7], dtype=dtype.float32)
174    ans = net(probs_b, probs_a)
175    assert isinstance(ans, Tensor)
176
177
178class GeometricBasics(nn.Cell):
179    """
180    Test class: basic mean/sd/mode/entropy function.
181    """
182
183    def __init__(self):
184        super(GeometricBasics, self).__init__()
185        self.g = msd.Geometric([0.3, 0.5], dtype=dtype.int32)
186
187    def construct(self):
188        mean = self.g.mean()
189        sd = self.g.sd()
190        var = self.g.var()
191        mode = self.g.mode()
192        entropy = self.g.entropy()
193        return mean + sd + var + mode + entropy
194
195
196def test_bascis():
197    """
198    Test mean/sd/mode/entropy functionality of Geometric distribution.
199    """
200    net = GeometricBasics()
201    ans = net()
202    assert isinstance(ans, Tensor)
203
204
205class GeoConstruct(nn.Cell):
206    """
207    Bernoulli distribution: going through construct.
208    """
209
210    def __init__(self):
211        super(GeoConstruct, self).__init__()
212        self.g = msd.Geometric(0.5, dtype=dtype.int32)
213        self.g1 = msd.Geometric(dtype=dtype.int32)
214
215    def construct(self, value, probs):
216        prob = self.g('prob', value)
217        prob1 = self.g('prob', value, probs)
218        prob2 = self.g1('prob', value, probs)
219        return prob + prob1 + prob2
220
221
222def test_geo_construct():
223    """
224    Test probability function going through construct.
225    """
226    net = GeoConstruct()
227    value = Tensor([0, 0, 0, 0, 0], dtype=dtype.float32)
228    probs = Tensor([0.5], dtype=dtype.float32)
229    ans = net(value, probs)
230    assert isinstance(ans, Tensor)
231