手动将LSTM从Tensorflow导入到PyTorch

import torch
import torch.nn as nn

# 定义 LSTM 模型
class LSTMModel(nn.Module):
    def __init__(self, input_size, hidden_size, num_layers, output_size):
        super(LSTMModel, self).__init__()
        self.hidden_size = hidden_size
        self.num_layers = num_layers
        self.lstm = nn.LSTM(input_size, hidden_size, num_layers, batch_first=True)
        self.fc = nn.Linear(hidden_size, output_size)

    def forward(self, x):
        h0 = torch.zeros(self.num_layers, x.size(0), self.hidden_size).to(device)
        c0 = torch.zeros(self.num_layers, x.size(0), self.hidden_size).to(device)
        out, _ = self.lstm(x, (h0, c0))
        out = self.fc(out[:, -1, :])
        return out

# 实例化 LSTM 模型
input_size = 10
hidden_size = 20
num_layers = 2
output_size = 1
model = LSTMModel(input_size, hidden_size, num_layers, output_size)

# 定义输入数据
input_data = torch.randn(32, 100, input_size)  # 假设输入数据维度为 (batch_size, sequence_length, input_size)

# 前向传递
output = model(input_data)