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95 lines
3.3 KiB
95 lines
3.3 KiB
# Copyright 2021 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_confusion_matrix_metric"""
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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 ConfusionMatrixMetric
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def test_confusion_matrix_metric():
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"""test_confusion_matrix_metric"""
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metric = ConfusionMatrixMetric(skip_channel=True, metric_name="tpr", calculation_method=False)
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metric.clear()
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x = Tensor(np.array([[[0], [1]], [[1], [0]]]))
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y = Tensor(np.array([[[0], [1]], [[0], [1]]]))
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metric.update(x, y)
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x = Tensor(np.array([[[0], [1]], [[1], [0]]]))
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y = Tensor(np.array([[[0], [1]], [[1], [0]]]))
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metric.update(x, y)
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output = metric.eval()
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assert np.allclose(output, np.array([0.75]))
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def test_confusion_matrix_metric_update_len():
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x = Tensor(np.array([[0.2, 0.5, 0.7], [0.3, 0.1, 0.2], [0.9, 0.6, 0.5]]))
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metric = ConfusionMatrixMetric(skip_channel=True, metric_name="ppv", calculation_method=True)
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metric.clear()
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with pytest.raises(ValueError):
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metric.update(x)
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def test_confusion_matrix_metric_update_dim():
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x = Tensor(np.array([[0.2, 0.5, 0.7], [0.3, 0.1, 0.2], [0.9, 0.6, 0.5]]))
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y = Tensor(np.array([1, 0]))
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metric = ConfusionMatrixMetric(skip_channel=True, metric_name="tnr", calculation_method=True)
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metric.clear()
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with pytest.raises(ValueError):
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metric.update(y, x)
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def test_confusion_matrix_metric_init_skip_channel():
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with pytest.raises(TypeError):
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ConfusionMatrixMetric(skip_channel=1)
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def test_confusion_matrix_metric_init_compute_sample():
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with pytest.raises(TypeError):
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ConfusionMatrixMetric(calculation_method=1)
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def test_confusion_matrix_metric_init_metric_name_type():
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with pytest.raises(TypeError):
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metric = ConfusionMatrixMetric(skip_channel=True, metric_name=1, calculation_method=False)
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x = Tensor(np.array([[[0], [1]], [[1], [0]]]))
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y = Tensor(np.array([[[0], [1]], [[1], [0]]]))
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metric.update(x, y)
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output = metric.eval()
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assert np.allclose(output, np.array([0.75]))
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def test_confusion_matrix_metric_init_metric_name_str():
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with pytest.raises(NotImplementedError):
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metric = ConfusionMatrixMetric(skip_channel=True, metric_name="wwwww", calculation_method=False)
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x = Tensor(np.array([[[0], [1]], [[1], [0]]]))
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y = Tensor(np.array([[[0], [1]], [[1], [0]]]))
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metric.update(x, y)
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output = metric.eval()
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assert np.allclose(output, np.array([0.75]))
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def test_confusion_matrix_metric_runtime():
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metric = ConfusionMatrixMetric(skip_channel=True, metric_name="tnr", calculation_method=True)
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metric.clear()
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with pytest.raises(RuntimeError):
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metric.eval()
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