Exemplos de load_data_jay_lyrics em Python

Exemplo n.º 1

#循环神经网络
#https://www.kesci.com/org/boyuai/project/share/c0d6527233dd1686

#从零开始实现循环神经网络
import torch
import torch.nn as nn
import time
import math
import sys
sys.path.append("/home/kesci/input")
import d2l_jay9460 as d2l
(corpus_indices, char_to_idx, idx_to_char,
 vocab_size) = d2l.load_data_jay_lyrics()
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

#one-hot向量


def one_hot(x, n_class, dtype=torch.float32):
    result = torch.zeros(x.shape[0], n_class, dtype=dtype,
                         device=x.device)  # shape: (n, n_class)
    result.scatter_(1, x.long().view(-1, 1), 1)  # result[i, x[i, 0]] = 1
    return result


x = torch.tensor([0, 2])
x_one_hot = one_hot(x, vocab_size)
print(x_one_hot)
print(x_one_hot.shape)
print(x_one_hot.sum(axis=1))

Exemplo n.º 2

Arquivo: lesson_13_GRU.py Projeto: zhenglinghan/boyu-platform-pytorch-lessons

• 更新⻔有助于捕捉时间序列⾥⻓期的依赖关系。

载入数据集
import os
os.listdir('/home/kesci/input')
['d2lzh1981', 'houseprices2807', 'jaychou_lyrics4703', 'd2l_jay9460']
import numpy as np
import torch
from torch import nn, optim
import torch.nn.functional as F
import sys
sys.path.append("../input/")
import d2l_jay9460 as d2l
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

(corpus_indices, char_to_idx, idx_to_char, vocab_size) = d2l.load_data_jay_lyrics()
初始化参数
num_inputs, num_hiddens, num_outputs = vocab_size, 256, vocab_size
print('will use', device)

def get_params():  
    def _one(shape):
        ts = torch.tensor(np.random.normal(0, 0.01, size=shape), device=device, dtype=torch.float32) #正态分布
        return torch.nn.Parameter(ts, requires_grad=True)
    def _three():
        return (_one((num_inputs, num_hiddens)),
                _one((num_hiddens, num_hiddens)),
                torch.nn.Parameter(torch.zeros(num_hiddens, device=device, dtype=torch.float32), requires_grad=True))
     
    W_xz, W_hz, b_z = _three()  # 更新门参数
    W_xr, W_hr, b_r = _three()  # 重置门参数