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- # Copyright 2021 Huawei Technologies Co., Ltd
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- # ============================================================================
- # """test_dice"""
- import math
- import numpy as np
- import pytest
- from mindspore import Tensor
- from mindspore.nn.metrics import get_metric_fn, Dice
-
-
- def test_classification_dice():
- """test_dice"""
- x = Tensor(np.array([[0.2, 0.5], [0.3, 0.1], [0.9, 0.6]]))
- y = Tensor(np.array([[0, 1], [1, 0], [0, 1]]))
- metric = get_metric_fn('dice')
- metric.clear()
- metric.update(x, y)
- dice = metric.eval()
-
- assert math.isclose(dice, 0.20467791371802546, abs_tol=0.001)
-
-
- def test_dice_update1():
- x = Tensor(np.array([[0.2, 0.5, 0.7], [0.3, 0.1, 0.2], [0.9, 0.6, 0.5]]))
- metric = Dice(1e-5)
- metric.clear()
-
- with pytest.raises(ValueError):
- metric.update(x)
-
-
- def test_dice_runtime():
- metric = Dice(1e-5)
- metric.clear()
-
- with pytest.raises(RuntimeError):
- metric.eval()
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