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我正在尝试使用PyTorch构建一个非常简单的LSTM自动编码器。我总是用相同的数据训练它：

x = torch.Tensor([[0.0], [0.1], [0.2], [0.3], [0.4]])

我建立我的模型下面这个链接：

inputs = Input(shape=(timesteps, input_dim))
encoded = LSTM(latent_dim)(inputs)

decoded = RepeatVector(timesteps)(encoded)
decoded = LSTM(input_dim, return_sequences=True)(decoded)

sequence_autoencoder = Model(inputs, decoded)
encoder = Model(inputs, encoded)

我的代码正在运行，没有错误，但y_pred收敛到：

tensor([[[0.2]],
        [[0.2]],
        [[0.2]],
        [[0.2]],
        [[0.2]]], grad_fn=<StackBackward>)

这是我的代码：

import torch
import torch.nn as nn
import torch.optim as optim


class LSTM(nn.Module):

    def __init__(self, input_dim, latent_dim, batch_size, num_layers):
        super(LSTM, self).__init__()
        self.input_dim = input_dim
        self.latent_dim = latent_dim
        self.batch_size = batch_size
        self.num_layers = num_layers

        self.encoder = nn.LSTM(self.input_dim, self.latent_dim, self.num_layers) …