双向循环神经网络

双向循环神经网络的错误应用

In [1]:
import torch
from torch import nn
from d2l import torch as d2l

batch_size, num_steps, device = 32, 35, d2l.try_gpu()
train_iter, vocab = d2l.load_data_time_machine(batch_size, num_steps)
vocab_size, num_hiddens, num_layers = len(vocab), 256, 2
num_inputs = vocab_size
lstm_layer = nn.LSTM(num_inputs, num_hiddens, num_layers, bidirectional=True)
model = d2l.RNNModel(lstm_layer, len(vocab))
model = model.to(device)
num_epochs, lr = 500, 1
d2l.train_ch8(model, train_iter, vocab, lr, num_epochs, device)
perplexity 1.1, 119970.8 tokens/sec on cuda:0
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2021-07-13T17:18:09.811949 image/svg+xml Matplotlib v3.3.4, https://matplotlib.org/