forked from mindspore-Ecosystem/mindspore
49 lines
1.3 KiB
Python
49 lines
1.3 KiB
Python
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# 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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"""test loss"""
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import numpy as np
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import pytest
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from mindspore.nn.metrics import Loss
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from mindspore import Tensor
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def test_loss_inputs_error():
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loss = Loss()
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with pytest.raises(ValueError):
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loss(np.array(1), np.array(2))
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def test_loss_shape_error():
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loss = Loss()
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inp = np.ones(shape=[2, 2])
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with pytest.raises(ValueError):
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loss.update(inp)
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def test_loss():
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"""test_loss"""
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num = 5
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inputs = np.random.rand(num)
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loss = Loss()
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for k in range(num):
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loss.update(Tensor(np.array([inputs[k]])))
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assert inputs.mean() == loss.eval()
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loss.clear()
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with pytest.raises(RuntimeError):
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loss.eval()
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