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README.md
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@@ -44,7 +44,7 @@ RL Zoo branch: `feat/gym-donkeycar`
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```
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export AE_PATH=/path/to/ae-32_mountain.pkl
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# Download model and save it into the logs/ folder
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python -m
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python enjoy.py --algo tqc --env donkey-mountain-track-v0 -f logs/
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```
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@@ -52,7 +52,7 @@ python enjoy.py --algo tqc --env donkey-mountain-track-v0 -f logs/
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```
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python train.py --algo tqc --env donkey-mountain-track-v0 -f logs/
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# Upload the model and generate video (when possible)
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python -m
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```
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## Hyperparameters
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OrderedDict([('batch_size', 256),
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('buffer_size', 200000),
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('callback',
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[{'
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'
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('ent_coef', 'auto'),
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('env_wrapper',
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[{'gym.wrappers.time_limit.TimeLimit': {'max_episode_steps': 10000}},
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'ae.wrapper.AutoencoderWrapper',
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{'
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('gamma', 0.99),
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('gradient_steps', 256),
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('learning_rate', 0.00073),
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```
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export AE_PATH=/path/to/ae-32_mountain.pkl
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# Download model and save it into the logs/ folder
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python -m rl_zoo3.load_from_hub --algo tqc --env donkey-mountain-track-v0 -orga araffin -f logs/
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python enjoy.py --algo tqc --env donkey-mountain-track-v0 -f logs/
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```
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```
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python train.py --algo tqc --env donkey-mountain-track-v0 -f logs/
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# Upload the model and generate video (when possible)
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python -m rl_zoo3.push_to_hub --algo tqc --env donkey-mountain-track-v0 -f logs/ -orga araffin
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```
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## Hyperparameters
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OrderedDict([('batch_size', 256),
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('buffer_size', 200000),
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('callback',
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[{'rl_zoo3.callbacks.ParallelTrainCallback': {'gradient_steps': 200}},
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'rl_zoo3.callbacks.LapTimeCallback']),
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('ent_coef', 'auto'),
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('env_wrapper',
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[{'gym.wrappers.time_limit.TimeLimit': {'max_episode_steps': 10000}},
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'ae.wrapper.AutoencoderWrapper',
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{'rl_zoo3.wrappers.HistoryWrapper': {'horizon': 2}}]),
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('gamma', 0.99),
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('gradient_steps', 256),
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('learning_rate', 0.00073),
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