Hi, I’m using
dqn for my custom multi-agent
env. I can test my
tune, both work without any error. After just a few training iterations, I would like to see the agent’s performance with
compute_action. But I get the following error:
AttributeError: 'numpy.ndarray' object has no attribute 'float'
I ran my code in debugger mode, and I found that the problem comes from
torch_policy.py line 276.
return self._compute_action_helper(input_dict, state_batches, seq_lens, explore, timestep)
torch vision as the policy. in this line 276,
input_dict contains the
PyTorch expects to receive it as a Tensor. But, for some reason
RLlib/Ray stores the
obs tensor in a
nparray. As a result, this error rises.
I wonder anyone knows what is happening in the background?