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import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
class neural_network (nn.Module):
def __init__(self, input_dim, hidden_dim, output_dim):
super(neural_network, self).__init__()
self.hidden = nn.Linear (input_dim, hidden_dim)
self.act = nn.ReLU()
self.output = nn.Linear (hidden_dim, output_dim)
def forward (self, x):
x = self.hidden (x)
x = self.act (x)
x = self.output (x)
return x
input_dim = 4
hidden_dim = 32
output_dim = 4
model = neural_network(input_dim, hidden_dim, output_dim)
print(model)
criterion = nn.CrossEntropyLoss()
optimizer = optim.Adam(model.parameters(), lr= 0.01) |