1# Copyright 2020 Huawei Technologies Co., Ltd 2# 3# Licensed under the Apache License, Version 2.0 (the "License"); 4# you may not use this file except in compliance with the License. 5# You may obtain a copy of the License at 6# 7# http://www.apache.org/licenses/LICENSE-2.0 8# 9# Unless required by applicable law or agreed to in writing, software 10# distributed under the License is distributed on an "AS IS" BASIS, 11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12# See the License for the specific language governing permissions and 13# limitations under the License. 14# ============================================================================ 15""" test_loss """ 16import numpy as np 17import pytest 18 19import mindspore.nn as nn 20from mindspore import Tensor 21from ...ut_filter import non_graph_engine 22 23 24def test_L1Loss(): 25 loss = nn.L1Loss() 26 input_data = Tensor(np.array([1, 2, 3])) 27 target_data = Tensor(np.array([1, 2, 2])) 28 with pytest.raises(NotImplementedError): 29 loss.construct(input_data, target_data) 30 31 32@non_graph_engine 33def test_SoftmaxCrossEntropyWithLogits(): 34 """ test_SoftmaxCrossEntropyWithLogits """ 35 loss = nn.SoftmaxCrossEntropyWithLogits() 36 37 logits = Tensor(np.random.randint(0, 9, [100, 10]).astype(np.float32)) 38 labels = Tensor(np.random.randint(0, 9, [100, 10]).astype(np.float32)) 39 loss.construct(logits, labels) 40