【深度学习】RNN的简单实现

最新推荐文章于 2025-02-05 23:23:23 发布

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最新推荐文章于 2025-02-05 23:23:23 发布 · 841 阅读

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CC 4.0 BY-SA版权

文章标签：

#rnn #人工智能 #深度学习

1.RNNCell

2.RNN

3.RNN_Embedding

1.RNNCell

import torch

input_size = 4
hidden_size = 4
batch_size = 1

idx2char = ['e', 'h', 'l', 'o']
x_data = [1, 0, 2, 2, 3]  # 输入：hello
y_data = [3, 1, 2, 3, 2]  # 期待：ohlol

# 独热向量
one_hot_lookup = [[1, 0, 0, 0],
                  [0, 1, 0, 0],
                  [0, 0, 1, 0],
                  [0, 0, 0, 1]]
x_one_hot = [one_hot_lookup[x] for x in x_data]

inputs = torch.Tensor(x_one_hot).view(-1, batch_size, input_size)  # (seqLen,batchSize,inputSize)
labels = torch.LongTensor(y_data).view(-1, 1)  # (seqLen,1)


class Model(torch.nn.Module):
    def __init__(self, input_size, hidden_size, batch_size):
        super(Model, self).__init__()
        self.batch_size = batch_size
        self.input_size = input_size
        self.hidden_size = hidden_size
        self.rnncell =