Всё про мир IT и программирование

import numpy as np
import torch
import torch.nn as nn
import torch.optim as optim

class NeuralNetwork(nn.Module):
    def __init__(self, input_dim, hidden_dim, output_dim):
        super(NeuralNetwork, self).__init__()
        self.fc1 = nn.Linear(input_dim, hidden_dim)
        self.fc2 = nn.Linear(hidden_dim, output_dim)

    def forward(self, x):
        x = torch.relu(self.fc1(x))
        return self.fc2(x)

optimizer = optim.SGD(model.parameters(), lr=0.01)
for epoch in range(10):
    optimizer.zero_grad()
    outputs = model(inputs)
    loss = criterion(outputs, labels)
    loss.backward()
    optimizer.step()

with torch.no_grad():
    for inputs, labels in test_loader:
        outputs = model(inputs)
        loss = criterion(outputs, labels)

SELECT * FROM customers;

CREATE TABLE books (id INT, title VARCHAR(100), author VARCHAR(100));