puoi spiegarmi questo codice?  import torch
import torch.nn as nn
import pandas as pd
import numpy as np

class LSTMModel(nn.Module):
    def __init__(self, input_dim, hidden_dim, batch_size, output_dim, num_layers):
        super(LSTMModel, self).__init__()
        self.hidden_dim = hidden_dim
        self.batch_size = batch_size
        self.num_layers = num_layers

        self.lstm = nn.LSTM(input_dim, hidden_dim, num_layers)
        self.fc = nn.Linear(hidden_dim, output_dim)

    def init_hidden(self):
        # initial hidden state
        return (torch.zeros(self.num_layers, self.batch_size, self.hidden_dim),
                torch.zeros(self.num_layers, self.batch_size, self.hidden_dim))

    def forward(self, sequence_in):
        lstm_out, self.hidden = self.lstm(
            sequence_in.view(len(sequence_in), self.batch_size, -1),
            self.hidden)
        y_pred = self.fc(lstm_out[-1])
        return y_pred.view(-1)


# Carica il file CSV in un DataFrame di Pandas
# Importa i dati dal file CSV
df = pd.read_csv('C:/NAME_1/10lottodb-4/24.csv', delimiter=',', header=None)

data = df.to_numpy(dtype=np.float32)

seq_length = 10
X = []
y = []
for i in range(len(data)-seq_length-1):
    sequence_in = data[i:i+seq_length]
    sequence_out = data[i+seq_length]
    X.append(sequence_in)
    y.append(sequence_out)

input_dim = 1
hidden_dim = 16
batch_size = 1
output_dim = 1
num_layers = 1
num_epochs = 100

model = LSTMModel(input_dim, hidden_dim, batch_size, output_dim, num_layers)
optimizer = torch.opti Do not include the following keywords: file, self.num_layer, self).__init, def
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