reinforcement-learning
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Bidirectional RNN
Is there a way to train a bidirectional RNN (like LSTM or GRU) on trax nowadays?
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The following applies to DDPG and TD3, and possibly other models. The following libraries were installed in a virtual environment:
numpy==1.16.4
stable-baselines==2.10.0
gym==0.14.0
tensorflow==1.14.0
Episode rewards do not seem to be updated in model.learn() before callback.on_step(). Depending on which callback.locals variable is used, this means that:
- episode rewards may n
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Jun 30, 2020 - Jupyter Notebook
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Problem: Currently
JsonLoggerCallback.handle_resultwill load in the entirety of the existing results, append the new result, and then rewrite the entire file. This may not scale when running long-running jobs or jobs with large results.https://github.com/ray-project/ray/blob/4e8f90aca20aa7bb87a4e84039889444824382ca/python/ray/train/callbacks/logging.py#L138-L142
Potential Fix: