2020-02-26 21:03:51 +08:00
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# Copyright (c) 2020 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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2020-02-11 16:56:28 +08:00
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import paddle.fluid.dygraph as dg
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import paddle.fluid.layers as layers
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2020-02-26 21:03:51 +08:00
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2020-02-11 16:56:28 +08:00
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class DynamicGRU(dg.Layer):
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def __init__(self,
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size,
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param_attr=None,
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bias_attr=None,
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is_reverse=False,
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gate_activation='sigmoid',
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candidate_activation='tanh',
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h_0=None,
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origin_mode=False,
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init_size=None):
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super(DynamicGRU, self).__init__()
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self.gru_unit = dg.GRUUnit(
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size * 3,
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param_attr=param_attr,
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bias_attr=bias_attr,
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activation=candidate_activation,
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gate_activation=gate_activation,
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origin_mode=origin_mode)
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self.size = size
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self.h_0 = h_0
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self.is_reverse = is_reverse
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def forward(self, inputs):
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"""
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Dynamic GRU block.
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Args:
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2020-03-09 15:16:02 +08:00
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input (Variable): The input value.
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Shape: (B, T, C), dtype: float32.
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2020-02-11 16:56:28 +08:00
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Returns:
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2020-03-09 15:16:02 +08:00
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output (Variable), the result compute by GRU. Shape: (B, T, C).
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2020-02-11 16:56:28 +08:00
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"""
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hidden = self.h_0
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res = []
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for i in range(inputs.shape[1]):
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if self.is_reverse:
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i = inputs.shape[1] - 1 - i
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input_ = inputs[:, i:i + 1, :]
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2020-03-05 15:22:50 +08:00
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input_ = layers.reshape(input_, [-1, input_.shape[2]])
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2020-02-11 16:56:28 +08:00
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hidden, reset, gate = self.gru_unit(input_, hidden)
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2020-03-05 15:22:50 +08:00
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hidden_ = layers.reshape(hidden, [-1, 1, hidden.shape[1]])
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2020-02-11 16:56:28 +08:00
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res.append(hidden_)
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if self.is_reverse:
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res = res[::-1]
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res = layers.concat(res, axis=1)
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return res
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