问pytorch中的keras.layers.Masking相当于什么？

EN

import torch
import torch.nn as nn
from torch.autograd import Variable

batch_size = 3
max_length = 3
hidden_size = 2
n_layers =1

# container
batch_in = torch.zeros((batch_size, 1, max_length))

#data
vec_1 = torch.FloatTensor([[1, 2, 3]])
vec_2 = torch.FloatTensor([[1, 2, 0]])
vec_3 = torch.FloatTensor([[1, 0, 0]])

batch_in[0] = vec_1
batch_in[1] = vec_2
batch_in[2] = vec_3

batch_in = Variable(batch_in)

seq_lengths = [3,2,1] # list of integers holding information about the batch size at each sequence step

# pack it
pack = torch.nn.utils.rnn.pack_padded_sequence(batch_in, seq_lengths, batch_first=True)

>>> pack
PackedSequence(data=Variable containing:
 1  2  3
 1  2  0
 1  0  0
[torch.FloatTensor of size 3x3]
, batch_sizes=[3])


# initialize
rnn = nn.RNN(max_length, hidden_size, n_layers, batch_first=True) 
h0 = Variable(torch.randn(n_layers, batch_size, hidden_size))

#forward 
out, _ = rnn(pack, h0)

# unpack
unpacked, unpacked_len = torch.nn.utils.rnn.pad_packed_sequence(out)

>>> unpacked
Variable containing:
(0 ,.,.) = 
 -0.7883 -0.7972
  0.3367 -0.6102
  0.1502 -0.4654
[torch.FloatTensor of size 1x3x2]