forked from mindspore-Ecosystem/mindspore
72 lines
1.9 KiB
Python
72 lines
1.9 KiB
Python
# 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 error"""
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import math
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import numpy as np
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import pytest
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from mindspore import Tensor
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from mindspore.nn.metrics import MAE, MSE
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def test_MAE():
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x = Tensor(np.array([0.1, 0.2, 0.6, 0.9]))
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y = Tensor(np.array([0.1, 0.25, 0.7, 0.9]))
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error = MAE()
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error.clear()
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error.update(x, y)
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result = error.eval()
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assert math.isclose(result, 0.15 / 4)
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def test_input_MAE():
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x = Tensor(np.array([0.1, 0.2, 0.6, 0.9]))
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y = Tensor(np.array([0.1, 0.25, 0.7, 0.9]))
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error = MAE()
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error.clear()
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with pytest.raises(ValueError):
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error.update(x, y, x)
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def test_zero_MAE():
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error = MAE()
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with pytest.raises(RuntimeError):
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error.eval()
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def test_MSE():
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x = Tensor(np.array([0.1, 0.2, 0.6, 0.9]))
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y = Tensor(np.array([0.1, 0.25, 0.5, 0.9]))
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error = MSE()
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error.clear()
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error.update(x, y)
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result = error.eval()
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assert math.isclose(result, 0.0125 / 4)
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def test_input_MSE():
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x = Tensor(np.array([0.1, 0.2, 0.6, 0.9]))
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y = Tensor(np.array([0.1, 0.25, 0.7, 0.9]))
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error = MSE()
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error.clear()
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with pytest.raises(ValueError):
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error.update(x, y, x)
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def test_zero_MSE():
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error = MSE()
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with pytest.raises(RuntimeError):
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error.eval()
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