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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.
- # ============================================================================
-
- import numpy as np
- import pytest
-
- import mindspore.context as context
- from mindspore import Tensor
- from mindspore.ops import operations as P
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_cpu
- @pytest.mark.env_onecard
- def test_roi_align():
- def roi_align_case(data_type):
- context.set_context(mode=context.PYNATIVE_MODE, device_target="CPU")
- x = Tensor(np.array([[
- [[1, 2, 3, 4, 5, 6],
- [7, 8, 9, 10, 11, 12],
- [13, 14, 15, 16, 17, 18],
- [19, 20, 21, 22, 23, 24],
- [25, 26, 27, 28, 29, 30],
- [31, 32, 33, 34, 35, 36]]
- ]], data_type))
-
- # test case 1
- rois = Tensor(np.array([[0, -2.0, -2.0, 21.0, 21.0]], data_type))
- pooled_height, pooled_width, spatial_scale, sample_num = 3, 3, 0.25, 2
- roi_align = P.ROIAlign(pooled_height, pooled_width,
- spatial_scale, sample_num, 1)
- output = roi_align(x, rois)
- #print(output)
- expect = [[[[4.5, 6.5, 8.5],
- [16.5, 18.5, 20.5],
- [28.5, 30.5, 32.5]]]]
- assert (output.asnumpy() == expect).all()
-
- # test case 2
- rois = Tensor(np.array([[0, -2.0, -2.0, 22.0, 22.0]], data_type))
- pooled_height, pooled_width, spatial_scale, sample_num = 3, 3, 0.25, 2
- roi_align = P.ROIAlign(pooled_height, pooled_width,
- spatial_scale, sample_num, 0)
- output = roi_align(x, rois)
- #print(output)
- expect = [[[[4.5, 6.5, 8.5],
- [16.5, 18.5, 20.5],
- [28.5, 30.5, 32.5]]]]
- assert (output.asnumpy() == expect).all()
-
- # test case 3
- pooled_height, pooled_width, spatial_scale, sample_num = 2, 2, 1.0, -1
- rois = Tensor(np.array([[0, -2.0, -2.0, 22.0, 22.0]], data_type))
- roi_align = P.ROIAlign(pooled_height, pooled_width,
- spatial_scale, sample_num, 0)
- output = roi_align(x, rois)
- #print(output)
- expect = [[[[6.295, 0.],
- [0., 0.]]]]
- np.testing.assert_almost_equal(output.asnumpy(), expect, decimal=2)
-
- roi_align_case(np.float32)
- roi_align_case(np.float16)
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