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41 lines
1.4 KiB
41 lines
1.4 KiB
# Copyright 2019 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 mindspore.context as context
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import mindspore.nn as nn
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from mindspore.common.api import ms_function
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from mindspore.ops import operations as P
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context.set_context(device_target="Ascend")
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class Net(nn.Cell):
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def __init__(self):
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super(Net, self).__init__()
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self.matmul = P.MatMul(transpose_b=True)
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self.bias_add = P.BiasAdd()
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@ms_function
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def construct(self, x, w, b):
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return self.bias_add(self.matmul(x, w), b)
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# def test_net():
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# x = np.random.randn(32, 2048).astype(np.float16)
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# w = np.random.randn(1001, 2048).astype(np.float16)
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# b = np.random.randn(1001).astype(np.float16)
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# FullConnection = Net()
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# output = FullConnection(Tensor(x), Tensor(w), Tensor(b))
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# print(output.asnumpy())
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