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55 lines
1.9 KiB
55 lines
1.9 KiB
4 years ago
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# Copyright 2021 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.ops import operations as P
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from mindspore.ops.operations import _inner_ops as inner
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class MatMul_d(nn.Cell):
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def __init__(self):
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super(MatMul_d, self).__init__()
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self.test_dynamic = inner.GpuConvertToDynamicShape()
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self.matmul = P.MatMul()
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def construct(self, x, y):
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x = self.test_dynamic(x)
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y = self.test_dynamic(y)
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return self.matmul(x, y)
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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_MatMul_dynamic():
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context.set_context(mode=context.GRAPH_MODE, device_target="GPU")
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net = MatMul_d()
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x1 = np.arange(2).reshape(1, 2).astype(np.float32)
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y1 = np.arange(4).reshape(2, 2).astype(np.float32)
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output1 = net(Tensor(x1), Tensor(y1))
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expect1 = np.matmul(x1, y1)
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np.testing.assert_array_almost_equal(output1.asnumpy(), expect1)
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x2 = np.arange(102).reshape(34, 3).astype(np.float32)
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y2 = np.arange(18).reshape(3, 6).astype(np.float32)
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output2 = net(Tensor(x2), Tensor(y2))
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expect2 = np.matmul(x2, y2)
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np.testing.assert_array_almost_equal(output2.asnumpy(), expect2)
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