import torch.nn as nn
from fastNLP.modules.utils import initial_parameter
[docs]class Linear(nn.Module):
"""
Linear module
Args:
input_size : input size
hidden_size : hidden size
num_layers : number of hidden layers
dropout : dropout rate
bidirectional : If True, becomes a bidirectional RNN
"""
def __init__(self, input_size, output_size, bias=True, initial_method=None):
super(Linear, self).__init__()
self.linear = nn.Linear(input_size, output_size, bias)
initial_parameter(self, initial_method)
[docs] def forward(self, x):
x = self.linear(x)
return x