288 Pervmom High Quality -

def forward(self, x): x = torch.relu(self.fc1(x)) x = torch.relu(self.fc2(x)) x = self.fc3(x) return x

# Dummy data initialization data = np.random.rand(100, 288) # 100 samples, 288 features labels = np.random.randint(0, 10, 100) # Dummy labels 288 pervmom high quality