forked from mindspore-Ecosystem/mindspore
57 lines
2.0 KiB
Python
57 lines
2.0 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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""" test graph clear statement. """
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import pytest
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import numpy as np
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import mindspore as ms
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import mindspore.nn as nn
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from mindspore import Tensor, context
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context.set_context(mode=context.GRAPH_MODE)
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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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def test_tensorarray_clear():
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"""
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Feature: Support clear is isolated node.
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Description: Support clear is isolated node.
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Expectation: No exception.
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"""
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class Net(nn.Cell):
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def __init__(self, dtype, element_shape):
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super(Net, self).__init__()
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self.ta = nn.TensorArray(dtype=dtype, element_shape=element_shape)
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self.index_1 = 1
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self.index_2 = 30
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def construct(self, input_1, input_2):
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size_1 = self.ta.size()
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self.ta.write(self.index_1, input_1)
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self.ta.write(self.index_2, input_2)
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size_2 = self.ta.size()
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self.ta.clear()
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size_3 = self.ta.size()
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return size_1, size_2, size_3
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input_np_1 = np.random.randn(2, 3, 4, 5, 6).astype(np.int32)
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input_np_2 = np.random.randn(2, 3, 4, 5, 6).astype(np.int32)
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net = Net(dtype=ms.int32, element_shape=(2, 3, 4, 5, 6))
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out_ms = net(Tensor(input_np_1), Tensor(input_np_2))
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assert out_ms[0] == 0
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assert out_ms[1] == 31
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assert out_ms[2] == 0
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