model = Net()
optimizer = optim.Adam(model.parameters(), lr=0.001)
loss_func = nn.NLLLoss()
epochs = 20
loss_list = []
model.train()
for epoch in range(epochs):
total_loss = []
for batch_idx, (data, target) in enumerate(dataset):
optimizer.zero_grad()
# Forward pass
output = model(data)
# Calculating loss
loss = loss_func(output, target)
# Backward pass
loss.backward()
# Optimize the weights
optimizer.step()
    total_loss.append(loss.item())
loss_list.append(sum(total_loss)/len(total_loss))
print('Training [{:.0f}%]\tLoss: {:.4f}'.format(
    100. * (epoch + 1) / epochs, loss_list[-1]))


NameError                                 Traceback (most recent call last)
 in 
----> 1 model = Net()
2 optimizer = optim.Adam(model.parameters(), lr=0.001)
3 loss_func = nn.NLLLoss()
4
5 epochs = 20
 in init(self)
7         self.fc1 = nn.Linear(256, 64)
8         self.fc2 = nn.Linear(64, 1)
----> 9         self.hybrid = Hybrid(qiskit.Aer.get_backend(‘qasm_simulator’), 100, np.pi / 2)
10
11     def forward(self, x):
NameError: name ‘Hybrid’ is not defined