36 lines
1.1 KiB
Python
36 lines
1.1 KiB
Python
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#!/usr/bin/python
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# -*- coding: utf-8 -*-
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#####################################
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# File name : rnn_model.py
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# Create date : 2019-02-16 15:37
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# Modified date : 2019-02-19 13:07
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# Author : DARREN
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# Describe : not set
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# Email : lzygzh@126.com
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#####################################
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from __future__ import division
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from __future__ import print_function
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import torch
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import torch.nn as nn
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class RNN(nn.Module):
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def __init__(self, input_size, hidden_size, output_size):
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super(RNN, self).__init__()
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self.hidden_size = hidden_size
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self.input_to_hidden = nn.Linear(input_size + hidden_size, hidden_size)
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self.input_to_output = nn.Linear(input_size + hidden_size, output_size)
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self.softmax = nn.LogSoftmax(dim=1)
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def forward(self, input, hidden):
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combined = torch.cat((input, hidden), 1)
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hidden = self.input_to_hidden(combined)
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output = self.input_to_output(combined)
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output = self.softmax(output)
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return output, hidden
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def init_hidden(self):
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return torch.zeros(1, self.hidden_size)
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