forked from mindspore-Ecosystem/mindspore
81 lines
3.0 KiB
Python
81 lines
3.0 KiB
Python
# Copyright 2022 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import numpy as np
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import pytest
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import mindspore.context as context
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import mindspore.nn as nn
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from mindspore import Tensor
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from mindspore import Parameter
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from mindspore.ops import operations as P
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context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
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def scatter_element_np(input_x, indices, updates, axis):
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result = input_x.asnumpy().copy()
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indices_np = indices.asnumpy().copy()
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updates_np = updates.asnumpy().copy()
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i_len = indices_np.shape[0]
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j_len = indices_np.shape[1]
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for i in range(i_len):
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for j in range(j_len):
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if axis == 0:
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result[indices_np[i][j]][j] = updates_np[i][j]
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if axis == 1:
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result[i][indices_np[i][j]] = updates_np[i][j]
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return result
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class TestScatterElements(nn.Cell):
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def __init__(self, input_x, indices, updates, axis):
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super(TestScatterElements, self).__init__()
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self.axis = axis
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self.input_x = Parameter(input_x, name="input_x")
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self.indices = Parameter(indices, name="indices")
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self.updates = Parameter(updates, name="updates")
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self.scatter_elements = P.ScatterElements(self.axis)
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def construct(self):
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return self.scatter_elements(self.input_x, self.indices, self.updates)
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@pytest.mark.level0
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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@pytest.mark.parametrize('dtype', [np.float32, np.float64, np.int32])
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@pytest.mark.parametrize('index_dtype', [np.int32])
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@pytest.mark.parametrize('axis', [0, 1])
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def test_scatter_elements(dtype, index_dtype, axis):
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"""
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Feature: Op ScatterElements
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Description: Scatter update value according indices to output.
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output[indices[i][j]][j] = updates[i][j] if axis = 0,
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output[i][indices[i][j]] = updates[i][j] if axis = 1.
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Expectation: Ans is same as expected.
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"""
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x = Tensor(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=dtype))
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indices = Tensor(np.array([[1, 0, 2], [0, 2, 1]], dtype=index_dtype))
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update = Tensor(np.array([[0, 0, 0], [0, 0, 0]], dtype=dtype))
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ms_output = TestScatterElements(x, indices, update, axis)()
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np_output = scatter_element_np(x, indices, update, axis)
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print("ms_output:\n", ms_output.asnumpy())
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assert np.allclose(ms_output.asnumpy(), np_output)
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