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- # Copyright 2020 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_loss """
- import numpy as np
- import pytest
-
- import mindspore.nn as nn
- from mindspore import Tensor
- from ...ut_filter import non_graph_engine
-
-
- def test_L1Loss():
- loss = nn.L1Loss()
- input_data = Tensor(np.array([1, 2, 3]))
- target_data = Tensor(np.array([1, 2, 2]))
- with pytest.raises(NotImplementedError):
- loss.construct(input_data, target_data)
-
-
- @non_graph_engine
- def test_SoftmaxCrossEntropyWithLogits():
- """ test_SoftmaxCrossEntropyWithLogits """
- loss = nn.SoftmaxCrossEntropyWithLogits()
-
- logits = Tensor(np.random.randint(0, 9, [100, 10]).astype(np.float32))
- labels = Tensor(np.random.randint(0, 9, [100, 10]).astype(np.float32))
- loss.construct(logits, labels)
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