1# Copyright 2024 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# ============================================================================ 15import pytest 16import numpy as np 17 18import mindspore as ms 19import mindspore.context as context 20from mindspore import Tensor 21from mindspore import ops 22import tests.st.utils.test_utils as test_utils 23 24 25@test_utils.run_with_cell 26def forward_func(x, pad_dim_size): 27 return ops.padding(x, pad_dim_size) 28 29 30@pytest.mark.level0 31@pytest.mark.env_onecard 32@pytest.mark.platform_arm_ascend_training 33@pytest.mark.platform_x86_ascend_training 34@pytest.mark.parametrize("context_mode", [context.GRAPH_MODE, context.PYNATIVE_MODE]) 35def test_padding_float32(context_mode): 36 """ 37 Feature: padding 38 Description: test padding forward 39 Expectation: expect correct result. 40 """ 41 context.set_context(mode=context_mode, device_target="Ascend") 42 x = Tensor(np.array([[8], [10]]), ms.float32) 43 pad_dim_size = 4 44 output = forward_func(x, pad_dim_size) 45 expected = np.array( 46 [[8., 0., 0., 0.], 47 [10., 0., 0., 0.]], np.float32) 48 np.testing.assert_allclose(output.asnumpy(), expected, rtol=1e-3) 49