torch下的網路對文字進行embedding操作的程式碼示例如下：

from torch import nn
import torch
from torch.nn import functional as F


class TextNet(nn.Module):
    def __init__(self, vocab_size, seq_len,embedding_len, num_classes=2):
        super(TextNet, self).__init__()
        self.seq_len=seq_len
        self.vocab_size = vocab_size
        self.embedding_len = embedding_len
        self.word_embeddings = nn.Embedding(vocab_size, embedding_len)

    def forward(self, x):
        x = self.word_embeddings(x)
        return x


if __name__ == '__main__':
    model = TextNet(vocab_size=5000, seq_len=600,embedding_len=2)
    x=[[1,2,2,4]]
    input = torch.autograd.Variable(torch.LongTensor(x))
    o = model(input)
    print(o)
    print(o.size())

    x = [[1, 3, 2, 4]]
    input = torch.autograd.Variable(torch.LongTensor(x))
    o = model(input)
    print(o)
    print(o.size())
 

輸出結果：

tensor([[[-0.6614,  0.1508],
         [ 0.6160, -0.2825],
         [ 0.6160, -0.2825],
         [ 1.3361, -1.4880]]])
torch.Size([1, 4, 2])
tensor([[[-0.6614,  0.1508],
         [ 1.1087,  1.0002],
         [ 0.6160, -0.2825],
         [ 1.3361, -1.4880]]])
torch.Size([1, 4, 2])