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75 lines
2.1 KiB
75 lines
2.1 KiB
# Copyright 2019 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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"""test cases for exp"""
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import pytest
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import mindspore.nn as nn
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import mindspore.nn.probability.bijector as msb
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from mindspore import Tensor
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from mindspore import dtype
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def test_init():
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b = msb.Exp()
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assert isinstance(b, msb.Bijector)
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def test_type():
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with pytest.raises(TypeError):
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msb.Exp(name=0.1)
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class Net(nn.Cell):
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"""
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Test class: forward and inverse pass of bijector.
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"""
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def __init__(self):
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super(Net, self).__init__()
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self.b1 = msb.Exp()
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self.b2 = msb.Exp()
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def construct(self, x_):
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forward = self.b1.forward(x_)
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inverse = self.b1.inverse(forward)
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return x_ - inverse
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def test1():
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"""
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Test forward and inverse pass of exp bijector.
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"""
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net = Net()
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x = Tensor([2.0, 3.0, 4.0, 5.0], dtype=dtype.float32)
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ans = net(x)
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assert isinstance(ans, Tensor)
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class Jacobian(nn.Cell):
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"""
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Test class: forward and inverse pass of bijector.
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"""
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def __init__(self):
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super(Jacobian, self).__init__()
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self.b1 = msb.Exp()
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self.b2 = msb.Exp()
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def construct(self, x_):
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ans1 = self.b1.forward_log_jacobian(x_)
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ans2 = self.b1.inverse_log_jacobian(x_)
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return ans1 + ans2
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def test2():
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"""
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Test jacobians of exp bijector.
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"""
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net = Jacobian()
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x = Tensor([2.0, 3.0, 4.0, 5.0], dtype=dtype.float32)
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ans = net(x)
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assert isinstance(ans, Tensor)
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