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116 lines
3.4 KiB
116 lines
3.4 KiB
# Copyright 2020 Huawei Technologies Co., Ltd
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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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# ============================================================================
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"""
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Test nn.probability.distribution.
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"""
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import pytest
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import mindspore.nn as nn
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import mindspore.nn.probability.distribution as msd
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from mindspore import dtype as mstype
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from mindspore import Tensor
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from mindspore import context
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func_name_list = ['prob', 'log_prob', 'cdf', 'log_cdf',
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'survival_function', 'log_survival',
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'sd', 'var', 'mode', 'mean',
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'entropy', 'kl_loss', 'cross_entropy',
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'sample']
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class MyExponential(msd.Distribution):
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"""
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Test distribution class: no function is implemented.
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"""
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def __init__(self, rate=None, seed=None, dtype=mstype.float32, name="MyExponential"):
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param = dict(locals())
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param['param_dict'] = {'rate': rate}
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super(MyExponential, self).__init__(seed, dtype, name, param)
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class Net(nn.Cell):
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"""
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Test Net: function called through construct.
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"""
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def __init__(self, func_name):
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super(Net, self).__init__()
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self.dist = MyExponential()
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self.name = func_name
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def construct(self, *args, **kwargs):
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return self.dist(self.name, *args, **kwargs)
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def test_raise_not_implemented_error_construct():
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"""
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test raise not implemented error in pynative mode.
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"""
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value = Tensor([0.2], dtype=mstype.float32)
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for func_name in func_name_list:
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with pytest.raises(NotImplementedError):
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net = Net(func_name)
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net(value)
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def test_raise_not_implemented_error_construct_graph_mode():
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"""
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test raise not implemented error in graph mode.
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"""
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context.set_context(mode=context.GRAPH_MODE)
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value = Tensor([0.2], dtype=mstype.float32)
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for func_name in func_name_list:
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with pytest.raises(NotImplementedError):
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net = Net(func_name)
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net(value)
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class Net1(nn.Cell):
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"""
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Test Net: function called directly.
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"""
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def __init__(self, func_name):
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super(Net1, self).__init__()
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self.dist = MyExponential()
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self.func = getattr(self.dist, func_name)
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def construct(self, *args, **kwargs):
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return self.func(*args, **kwargs)
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def test_raise_not_implemented_error():
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"""
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test raise not implemented error in pynative mode.
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"""
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value = Tensor([0.2], dtype=mstype.float32)
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for func_name in func_name_list:
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with pytest.raises(NotImplementedError):
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net = Net1(func_name)
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net(value)
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def test_raise_not_implemented_error_graph_mode():
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"""
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test raise not implemented error in graph mode.
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"""
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context.set_context(mode=context.GRAPH_MODE)
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value = Tensor([0.2], dtype=mstype.float32)
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for func_name in func_name_list:
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with pytest.raises(NotImplementedError):
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net = Net1(func_name)
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net(value)
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