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I'm Marcus, and welcome to my repo!

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ERROR

Dear Chiamp,

Thank you for sharing your effort with the community. I was trying your muZero code and I fixed some not updated issues relative to the use of the discontinued Monitor. Once I fixed those, I experienced this error

=========== TESTING ===========
Total reward: 9.0
C:\Users\Federico\AppData\Roaming\Python\Python310\site-packages\gym\wrappers\record_video.py:41: UserWarning: ←[33mWARN: Overwriting existing videos at D:\Dropbox\PROJECTS\MLTrading\muzero-cartpole\video folder (try specifying a different `video_folder` for the `RecordVideo` wrapper if this is not desired)←[0m
  logger.warn(
Total reward: 10.0
Total reward: 8.0
Total reward: 8.0
Total reward: 10.0
Total reward: 10.0
Total reward: 10.0
Total reward: 10.0
Total reward: 10.0
Total reward: 9.0

Iteration: 1    Total reward: 35.0      Time elapsed: 0.33502347469329835 minutes
Traceback (most recent call last):
  File "D:\Dropbox\PROJECTS\MLTrading\muzero-cartpole\main.py", line 301, in <module>
    self_play(network_model,config)
  File "D:\Dropbox\PROJECTS\MLTrading\muzero-cartpole\main.py", line 48, in self_play
    train(network_model,replay_buffer,optimizer,config)
  File "D:\Dropbox\PROJECTS\MLTrading\muzero-cartpole\main.py", line 184, in train
    loss += (1/num_unroll_steps) * ( mean_squared_error(true_reward,pred_reward) + mean_squared_error(true_value,pred_value) + binary_crossentropy(true_policy,pred_policy) ) # take the average loss among all unroll steps
  File "C:\Users\Federico\anaconda3\envs\mltrading_base\lib\site-packages\tensorflow\python\util\traceback_utils.py", line 153, in error_handler
    raise e.with_traceback(filtered_tb) from None
  File "C:\Users\Federico\anaconda3\envs\mltrading_base\lib\site-packages\keras\losses.py", line 2176, in binary_crossentropy
    backend.binary_crossentropy(y_true, y_pred, from_logits=from_logits),
  File "C:\Users\Federico\anaconda3\envs\mltrading_base\lib\site-packages\keras\backend.py", line 5680, in binary_crossentropy
    return tf.nn.sigmoid_cross_entropy_with_logits(
ValueError: `logits` and `labels` must have the same shape, received ((1, 2) vs (2,)).

Did it happen to you too?

By the way is it possible to skip the rendering through any config parameter?

Thank you.

continous action space

Hey Chiamp,
how can i use this code to balance the continuous Single inverted pendulum environment with continuous action space? can you guide me little bit thanks.

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