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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 mindspore.context as context
- import mindspore.nn as nn
- from mindspore import Tensor
- from mindspore.common.api import ms_function
- from mindspore.ops import operations as P
-
- context.set_context(device_target="Ascend")
-
-
- class Net(nn.Cell):
- def __init__(self):
- super(Net, self).__init__()
- self.matmul = P.MatMul()
-
- @ms_function
- def construct(self, x1_, x2_):
- return self.matmul(x1_, x2_)
-
-
- x1 = np.random.randn(1, 3).astype(np.float32)
- x2 = np.random.randn(3, 4).astype(np.float32)
-
-
- def test_net():
- matmul = Net()
- output = matmul(Tensor(x1), Tensor(x2))
- print(x1)
- print(x2)
- print(output.asnumpy())
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