Related to Fixing errors with _obtain_steps function #27 #28
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added 3 commits
March 6, 2024 17:13
The shape argument in np.zeros calls for 'actions' and 'action_probs' arrays has been corrected from one-dimensional to tuple format. This change ensures that the arrays are correctly initialized with the intended dimensions (n_trajectories * step_per_trajectory, action_dim), which is the expected structure for processing action data.
The error occurred when the for loop was used with `rollout_lengths[i]`, where `rollout_lengths` was created with `self.random_.choice()`, resulting in a `numpy.int32` object. The problem has been fixed by iterating directly over the range of `rollout_lengths[i]` instead. Fixing errors with _obtain_steps function hakuhodo-technologies#27
Adding F821 undefined name 'next_state' based on Flask8. There is also another: synthetic.py:1289:25: F821 undefined name 'logged_dataset_'. However, as this is with MultipleLoggedDataset and it was not tested, I have left it for future work.
alexofficial
changed the title
self.behavior_policy existis only in this point and it is uncessary. Rename the variable self.behavior_policy to just behavior_policy will work.
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Type of change
Description
First change - Fix a TypeError caused by an unenumerable object
What has been changed?: The TypeError caused by an unenumerable object when using a for loop with rollout_lengths[i] has been fixed. Instead of directly accessing rollout_lengths[i], the fix involves iterating directly over the range of rollout_lengths[i].
How the logic works?: The previous implementation attempted to use rollout_lengths[i] directly in a loop, which caused a TypeError due to rollout_lengths being an unenumerable object created with self.random_.choice(), resulting in a numpy.int32 object. The fix involves iterating over the range of rollout_lengths[i], ensuring that each step of the loop corresponds to an index within the range of rollout_lengths[i], thus avoiding the TypeError.
Second change - Fixed form params in np.zeros for action arrays :
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Error with flake8: There is another error with flake, but I did not fix it because it was related to MultipleLoggedDataset, which I have not try to train yet (I left it for future work) - synthetic.py:1290:25: F821 undefined name 'logged_dataset_'
black format removes the () for the np.zero: I suspect that the wrong dimensions are due to the Black format. When I apply Black to synthetic.py, for some reason it removes the () in the lines, which I have already corrected. I assume Black was applied throughout the directory, so the changes were just picked up. Be aware of this 💯