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supplement another method
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tutorial-contents/403_RNN_regressor.py

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@@ -57,6 +57,11 @@ def forward(self, x, h_state):
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# outs = self.out(r_out)
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# outs = outs.view(-1, TIME_STEP, 1)
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# return outs, h_state
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# or even simpler, since nn.Linear can accept inputs of any dimension
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# and returns outputs with same dimension except for the last
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# outs = self.out(r_out)
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# return outs
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rnn = RNN()
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print(rnn)

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