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I cloned the repository, ran cartpole_per.py, and got:
prioritized_memory.py:41: RuntimeWarning: divide by zero encountered in power
is_weight = np.power(self.tree.n_entries * sampling_probabilities, -self.beta)
prioritized_memory.py:42: RuntimeWarning: invalid value encountered in true_divide
is_weight /= is_weight.max()
Traceback (most recent call last):
File "cartpole_per.py", line 201, in
agent.train_model()
File "cartpole_per.py", line 117, in train_model
states = np.vstack(mini_batch[0])
File "AppData\Local\Programs\Python\Python37\lib\site-packages\numpy\core\shape_base.py", line 283, in vstack
return _nx.concatenate([atleast_2d(_m) for _m in tup], 0)
ValueError: all the input array dimensions except for the concatenation axis must match exactly
I reran a few times, and the error always eventually occurs, though at varying lengths of time before it happens.
The text was updated successfully, but these errors were encountered:
I cloned the repository, ran cartpole_per.py, and got:
prioritized_memory.py:41: RuntimeWarning: divide by zero encountered in power
is_weight = np.power(self.tree.n_entries * sampling_probabilities, -self.beta)
prioritized_memory.py:42: RuntimeWarning: invalid value encountered in true_divide
is_weight /= is_weight.max()
Traceback (most recent call last):
File "cartpole_per.py", line 201, in
agent.train_model()
File "cartpole_per.py", line 117, in train_model
states = np.vstack(mini_batch[0])
File "AppData\Local\Programs\Python\Python37\lib\site-packages\numpy\core\shape_base.py", line 283, in vstack
return _nx.concatenate([atleast_2d(_m) for _m in tup], 0)
ValueError: all the input array dimensions except for the concatenation axis must match exactly
I reran a few times, and the error always eventually occurs, though at varying lengths of time before it happens.
The text was updated successfully, but these errors were encountered: