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Hi! Thanks for the excellent work!
After I used train_all_copo_dist.py to train the model and try to visualize it, I found that the dimensions of OBS and Weights did not match, even the same problem in the <new_best_checkpoints>. This problem occurred in every environment I trained, and the number of rows in OBS is always 1 less than the number of columns in Weights.
But I can visualize the <new_best_checkpoints> by the new_vis.py, which is wired.
Traceback (most recent call last):
File "/home/CoPO_tf/CoPO/copo_code/copo/vis_from_checkpoint.py", line 91, in <module>
action = policy_function(o, d)
File "/home/CoPO_tf/CoPO/copo_code/copo/eval/get_policy_function.py", line 170, in __call__
actions = self.policy(obs_to_be_eval)
File "/home/CoPO_tf/CoPO/copo_code/copo/vis_from_checkpoint.py", line 72, in policy
ret = policy_class(weights, obs, policy_name=policy_name, layer_name_suffix="_1", deterministic=deterministic)
File "/home/CoPO_tf/CoPO/copo_code/copo/eval/get_policy_function.py", line 61, in _compute_actions_for_tf_policy
assert obs.shape[1] == weights[s].shape[0], (obs.shape, weights[s].shape)
AssertionError: ((20, 96), (97, 256))
The text was updated successfully, but these errors were encountered:
Hi! Thanks for the excellent work!
After I used
train_all_copo_dist.py
to train the model and try to visualize it, I found that the dimensions of OBS and Weights did not match, even the same problem in the <new_best_checkpoints>. This problem occurred in every environment I trained, and the number of rows in OBS is always 1 less than the number of columns in Weights.But I can visualize the <new_best_checkpoints> by the new_vis.py, which is wired.
The text was updated successfully, but these errors were encountered: