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import torch | |
from torch import nn | |
class RNN_model(nn.Module): | |
def __init__(self): | |
super().__init__() | |
self.rnn= nn.RNN(input_size=1080, hidden_size=240,num_layers=1, nonlinearity= 'relu', bias= True) | |
self.output= nn.Linear(in_features=240, out_features=24) | |
def forward(self, x): | |
y, hidden= self.rnn(x) | |
#print(y.shape) | |
#print(hidden.shape) | |
x= self.output(y) | |
return(x) |