divide by zero error

Hello, thank you for the work. I am facing the issue of dividing by zero error in the line below when calling the sample function to sample memory. Any idea why?

is_weight /= is_weight.max()

[Jspujol]

Hello, I also find that the uninitialized samples will be sampled and got the unwanted data “0”. I tried to find out the root caused but failed. Did you guys figure out the reason? @stormont @emunaran Many thanks!

Hi there! I faced the same issue and what I did is to sample another value of that same interval, until it is not an integer (given that the capacity is initialized to np.zeros ). In the prioritized memory I added the following:

for i in range(n):
            a = segment * i
            b = segment * (i + 1)
            while True:
                s = random.uniform(a, b)
                (idx, p, data) = self.tree.get(s)
                if not isinstance(data, int):
                    break
            priorities.append(p)
            batch.append(data)
            idxs.append(idx)

This did the trick for me. Hope it does the same to you.

[being-aerys]

If anyone is still wondering why it pulls 0 from the replay memory, it is because the location in the replay memory that was sampled was not filled out yet and thus contained the initial values with which we initialized the replay buffer. i.e., 0’s. If you set a condition that the training does not start until the buffer is completely filled, then you never encounter this issue.