pytorch入门（六）—— 循环神经网络

循环神经网络（RNN）

import torch as tr
import torch.nn as nn
import torchvision.datasets as dsets
import torchvision.transforms as tf
import torch.utils.data as Data
from torch.autograd import Variable

sequence_length = 28
input_size = 28
hidden_size = 128
num_layers = 2
num_classes = 10
batch_size = 100
num_epochs = 2
learning_rate = 0.01

train_dataset = dsets.MNIST(
        root='./data/',
        train=True,
        transform=tf.ToTensor(),
        download=True
    )

train_loader = Data.DataLoader(dataset=train_dataset,
        batch_size=batch_size,
        shuffle=True)

test_dataset = dsets.MNIST(
        root='./data/',
        train=False,
        transform=tf.ToTensor()
    )

test_loader = Data.DataLoader(dataset=test_dataset,
        batch_size