Comments (1)
There is unfortunately no way to record a video out of the box with this code. The animation was made with an old (custom) version of that repository. However, you may be able to simply wrap the environment inside a RecordVideo
wrapper to record videos.
from pytorch-maml-rl.
Related Issues (20)
- AttributeError: Can't pickle local object 'make_env.<locals>._make_env' HOT 4
- if i want employe this work to a new env, what should i do HOT 7
- Cuda Support Issue HOT 2
- what is the mean of train_episodes and valid_episodes? HOT 4
- If I want to use the the meta-parameters to adapt to new task, what should I do? HOT 2
- TypeError: list indices must be integers or slices, not str HOT 1
- Fails to converge on bandit tasks HOT 1
- Can not read your env in the Jupyter HOT 1
- how can I adapt maml on my own environment? HOT 1
- How do you get the baseline curve in Fig5 in your paper? HOT 1
- train_returns and valid_returns seems to be equal
- is it posible to combine DPPG with MAML?
- How to solve the problem of Nan value during training?
- The progress bar doesn't increase at all HOT 4
- raise EOFError
- EOFError BrokenPipeError: [WinError 109]
- Traceback (most recent call last): File "D:\Anaconda3\envs\testenv\lib\multiprocessing\process.py", line 258, in _bootstrap self.run() File "F:\aa_maml\MAML-Pytorch-RL-master\maml_rl\envs\subproc_vec_env.py", line 61, in run command, data = self.remote.recv() File "D:\Anaconda3\envs\testenv\lib\multiprocessing\connection.py", line 312, in _recv_bytes nread, err = ov.GetOverlappedResult(True) File "D:\Anaconda3\envs\testenv\lib\multiprocessing\connection.py", line 250, in recv buf = self._recv_bytes() File "D:\Anaconda3\envs\testenv\lib\multiprocessing\connection.py", line 321, in _recv_bytes raise EOFError EOFError BrokenPipeError: [WinError 109] I run the code on win10 but this error occurred.
- Sync Vec porting
- After running the train.py, error "Unable to solve the normal equations in `LinearFeatureBaseline`. The matrix X^T*X (with X the design matrix) is not full-rank, regardless of the regularization (maximum regularization: 1.0)." occurs.
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from pytorch-maml-rl.