Hi,
Iam new to this forum and to pytorch.
Could someone help me with that error
RuntimeError: invalid argument 4: Index tensor must have same dimensions as input tensor at
def learn(self, batch, gamma):
“”"Update value parameters using given batch of experience tuples.
    Params
    ======
        experiences (Tuple[torch.Variable]): tuple of (s, a, r, s', done) tuples 
        gamma (float): discount factor
    """
    
    #states, actions, rewards, next_states, dones = experiences
    states = np.array([each[0][0] for each in batch], ndmin=3)
    actions = np.array([each[0][1] for each in batch])
    rewards = np.array([each[0][2] for each in batch]) 
    next_states = np.array([each[0][3] for each in batch], ndmin=3)

    dones = np.array([each[0][4] for each in batch])
    #dones  = np.array([map(lambda x: 1 if x else 0, dones)],dtype=np.float16)
    dones = dones.astype(np.int16)
    states = torch.from_numpy(states).float().cuda()
    next_states = torch.from_numpy(next_states).float().cuda()
    rewards = torch.from_numpy(rewards).float().cuda()
    actions = torch.from_numpy(actions).long().cuda()
    dones = torch.from_numpy(dones).float().cuda()
    #next_states = torch.from_numpy(next_states).float().unsqueeze(0).cuda()
    #print(states.shape)
    states = states.view(32,8)
    #print(states.shape)
    next_states = next_states.view(32,8)
    ## TODO: compute and minimize the loss
    "*** YOUR CODE HERE ***"
    Q_targets_next = self.qnetwork_target(next_states).detach().max(1)[0].unsqueeze(1)
    print(rewards.shape)
    print(Q_targets_next)
    Q_targets =  rewards + (gamma * Q_targets_next * (1-dones))
    
    Q_expected = self.qnetwork_local(states).gather(1, actions)
    
    loss = F.mse_loss(Q_expected, Q_targets)
    self.optimizer.zero_grad()
    loss.backward()
    self.optimizer.step()

    # ------------------- update target network ------------------- #
    self.soft_update(self.qnetwork_local, self.qnetwork_target, self.tau) 

I don’t know if this gather is correct here found the code online and it worked
now I try to modify to my problem
Thank you very much for your help
If you need more information let me know
Best Regards
Chris