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https://github.com/labmlai/annotated_deep_learning_paper_implementations.git
synced 2025-08-06 15:22:21 +08:00
ppo experiment configs
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@ -388,17 +388,7 @@ def main():
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experiment.configs(configs)
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# Initialize the trainer
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m = Trainer(
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updates=configs['updates'],
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epochs=configs['epochs'],
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n_workers=configs['n_workers'],
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worker_steps=configs['worker_steps'],
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batches=configs['batches'],
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value_loss_coef=configs['value_loss_coef'],
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entropy_bonus_coef=configs['entropy_bonus_coef'],
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clip_range=configs['clip_range'],
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learning_rate=configs['learning_rate'],
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)
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m = Trainer(**configs)
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# Run and monitor the experiment
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with experiment.start():
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2
setup.py
2
setup.py
@ -5,7 +5,7 @@ with open("readme.md", "r") as f:
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setuptools.setup(
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name='labml-nn',
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version='0.4.114',
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version='0.4.115',
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author="Varuna Jayasiri, Nipun Wijerathne",
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author_email="vpjayasiri@gmail.com, hnipun@gmail.com",
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description="🧑🏫 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit), optimizers (adam, radam, adabelief), gans(dcgan, cyclegan, stylegan2), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, etc. 🧠",
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