forked from mindspore-Ecosystem/mindspore
68 lines
2.3 KiB
Python
68 lines
2.3 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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import mindspore.common.dtype as mstype
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from mindspore import Tensor
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from mindspore.ops import operations as P
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class NetDynInput(nn.Cell):
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def __init__(self, shape):
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super(NetDynInput, self).__init__()
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self.scatternd = P.ScatterNd()
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self.shape = shape
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def construct(self, indices, update):
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return self.scatternd(indices, update, self.shape)
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def check_result(output, expect):
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error = np.ones(shape=output.shape) * 1.0e-6
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diff = output - expect
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assert np.all(diff < error)
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assert np.all(-diff < error)
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def case_dyn_input():
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indices = np.array([[0, 1], [1, 1], [0, 1], [0, 1], [0, 1]]).astype(np.int32)
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update = np.array([3.2, 1.1, 5.3, -2.2, -1.0]).astype(np.float32)
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shape = (2, 2)
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expect = np.array([[0., 5.3],
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[0., 1.1]]).astype(np.float32)
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net = NetDynInput(shape)
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indices_dyn = Tensor(shape=[None, 2], dtype=mstype.int32)
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update_dyn = Tensor(shape=[None], dtype=mstype.float32)
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net.set_inputs(indices_dyn, update_dyn)
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output = net(Tensor(indices), Tensor(update)).asnumpy()
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check_result(output, expect)
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@pytest.mark.level0
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.platform_x86_gpu_training
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@pytest.mark.env_onecard
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def test_dynamic_scatternd_dyn_input():
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"""
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Feature: dynamic shape for ScatterNd
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Description: dynamic input shape for ScatterNd
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Expectation: success
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"""
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context.set_context(mode=context.GRAPH_MODE)
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case_dyn_input()
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