wehub-resource-sync
65 lines
1.9 KiB
Python
65 lines
1.9 KiB
Python
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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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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import unittest
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import numpy as np
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import paddle
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from paddle import base
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class MLP(paddle.nn.Layer):
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def __init__(self, input_size):
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super().__init__()
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self._linear1 = paddle.nn.Linear(
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input_size,
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3,
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weight_attr=paddle.ParamAttr(
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initializer=paddle.nn.initializer.Constant(value=0.1)
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),
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bias_attr=paddle.ParamAttr(
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initializer=paddle.nn.initializer.Constant(value=0.1)
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),
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)
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self._linear2 = paddle.nn.Linear(
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3,
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4,
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weight_attr=paddle.ParamAttr(
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initializer=paddle.nn.initializer.Constant(value=0.1)
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),
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bias_attr=paddle.ParamAttr(
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initializer=paddle.nn.initializer.Constant(value=0.1)
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),
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)
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def forward(self, inputs):
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x = self._linear1(inputs)
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x = self._linear2(x)
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x = paddle.sum(x)
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return x
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class TestDygraphFramework(unittest.TestCase):
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def test_dygraph_to_string(self):
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np_inp = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
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with base.dygraph.guard():
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var_inp = paddle.to_tensor(np_inp)
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print(str(var_inp))
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if __name__ == '__main__':
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paddle.disable_static()
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unittest.main()
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