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- # Copyright 2019 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
-
- context.set_context(mode=context.GRAPH_MODE, device_target='GPU')
-
-
- @pytest.mark.level0
- @pytest.mark.platform_x86_gpu_training
- @pytest.mark.env_onecard
- def test_stridedslice():
- x = Tensor(np.arange(0, 2*3*4*5).reshape(2, 3, 4, 5).astype(np.float32))
- y = P.StridedSlice()(x, (1, 0, 0, 2), (2, 2, 2, 4), (1, 1, 1, 1))
- expect = np.array([[[[62, 63],
- [67, 68]],
- [[82, 83],
- [87, 88]]]])
- assert np.allclose(y.asnumpy(), expect)
-
- y = P.StridedSlice()(x, (1, 0, 0, 5), (2, 2, 2, 1), (1, 1, 1, -2))
- expect = np.array([[[[64, 62],
- [69, 67]],
- [[84, 82],
- [89, 87]]]])
- assert np.allclose(y.asnumpy(), expect)
-
- y = P.StridedSlice()(x, (1, 0, 0, -1), (2, 2, 2, 1), (1, 1, 1, -1))
- expect = np.array([[[[64, 63, 62],
- [69, 68, 67]],
- [[84, 83, 82],
- [89, 88, 87]]]])
- assert np.allclose(y.asnumpy(), expect)
-
- # ME infer fault
- # y = P.StridedSlice()(x, (1, 0, -1, -2), (2, 2, 0, -5), (1, 1, -1, -2))
- # expect = np.array([[[[78, 76],
- # [73, 71],
- # [68, 66]],
- # [[98, 96],
- # [93, 91],
- # [88, 86]]]])
- # assert np.allclose(y.asnumpy(), expect)
-
- # y = P.StridedSlice(begin_mask=0b1000, end_mask=0b0010)(x, (1, 0, 0, 2), (2, 2, 2, 4), (1, 1, 1, 1))
- # expect = np.array([[[[ 62, 63],
- # [ 67, 68]],
- # [[ 82, 83],
- # [ 87, 88]],
- # [[102, 103],
- # [107, 108]]]])
- # assert np.allclose(y.asnumpy(), expect)
-
- op = P.StridedSlice(begin_mask=0b1000, end_mask=0b0010, ellipsis_mask=0b0100)
- y = op(x, (1, 0, 0, 2), (2, 2, 2, 4), (1, 1, 1, 1))
- expect = np.array([[[[60, 61, 62, 63],
- [65, 66, 67, 68],
- [70, 71, 72, 73],
- [75, 76, 77, 78]],
- [[80, 81, 82, 83],
- [85, 86, 87, 88],
- [90, 91, 92, 93],
- [95, 96, 97, 98]],
- [[100, 101, 102, 103],
- [105, 106, 107, 108],
- [110, 111, 112, 113],
- [115, 116, 117, 118]]]])
- assert np.allclose(y.asnumpy(), expect)
-
- x = Tensor(np.arange(0, 3*4*5).reshape(3, 4, 5).astype(np.float32))
- y = P.StridedSlice()(x, (1, 0, 0), (2, -3, 3), (1, 1, 3))
- expect = np.array([[[20]]])
- assert np.allclose(y.asnumpy(), expect)
-
- x_np = np.arange(0, 4*5).reshape(4, 5).astype(np.float32)
- y = Tensor(x_np)[:, ::-1]
- expect = x_np[:, ::-1]
- assert np.allclose(y.asnumpy(), expect)
-
- x = Tensor(np.arange(0, 2 * 3 * 4 * 5 * 4 * 3 * 2).reshape(2, 3, 4, 5, 4, 3, 2).astype(np.float32))
- y = P.StridedSlice()(x, (1, 0, 0, 2, 1, 2, 0), (2, 2, 2, 4, 2, 3, 2), (1, 1, 1, 1, 1, 1, 2))
- expect = np.array([[[[[[[1498.]]],
- [[[1522.]]]],
- [[[[1618.]]],
- [[[1642.]]]]],
- [[[[[1978.]]],
- [[[2002.]]]],
- [[[[2098.]]],
- [[[2122.]]]]]]])
- assert np.allclose(y.asnumpy(), expect)
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