我要评论在做中文文本情感分析model类定义的时候报错如下：
有两种可能：
1.重写父类函数时，函数名称写错，我将
写成了
最终导致程序报错：
import torch
import torch.nn as nn
import torch.nn.functional as f
import numpy as np
class model(nn.module):
def __init__(self,config):
super(model, self).__init__()
self.embeding = nn.embedding(config.n_vocab, config.embed_size,padding_idx=config.n_vocab - 1)
self.lstm = nn.lstm(config.embed_size, config.hidden_size,
config.num_layers,
bidirectional=true,batch_first=true,
dropout=config.dropout)
self.maxpool = nn.maxpool1d(config.pad_size)
self.fc = nn.linear(config.hidden_size * 2 + config.embed_size, config.num_classes)
self.softmax = nn.softmax(dim=1)
def forword(self,x):
embed = self.embeding(x)
out,_ = self.lstm(embed)
out = torch.cat((embed,out),2)
out = f.relu(out)
out = out.permute(0,2,1)
out = self.maxpool(out).reshape(out.size()[0],-1)
out = self.fc(out)
out = self.softmax(out)
return out
if __name__ == "__main__":
from configs import config
cfg = config()
cfg.pad_size = 640
model_textcls = model(config = cfg)
input_tensor = torch.tensor([i for i in range(640)]).reshape([1,640])
out_tensor = model_textcls.forward(input_tensor)
print(out_tensor.size())
print(out_tensor)
2.def forward函数与def __init__(self,config):一定要对齐。
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