feature(xyy):add HPT model to implement PolicyStem+DuelingHead #841
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puyuan1996
reviewed
Nov 29, 2024
| @@ -24,6 +24,8 @@ | |||
| from .vae import VanillaVAE | |||
| from .decision_transformer import DecisionTransformer | |||
| from .procedure_cloning import ProcedureCloningMCTS, ProcedureCloningBFS | |||
| from .hpt import HPT | |||
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| class PolicyStem(nn.Module): | ||
| """policy stem |
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reformat the docstring as the DI-engine style
| @@ -32,8 +34,13 @@ def main(): | |||
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| set_pkg_seed(cfg.seed, use_cuda=cfg.policy.cuda) | |||
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| model = DQN(**cfg.policy.model) | |||
| # # Migrating models to the GPU | |||
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | |||
| create_config = lunarlander_hpt_create_config | ||
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| if __name__ == "__main__": | ||
| # or you can enter `ding -m serial -c lunarlander_dqn_config.py -s 0` |
| import_names=['dizoo.box2d.lunarlander.envs.lunarlander_env'], | ||
| ), | ||
| env_manager=dict(type='subprocess'), | ||
| # env_manager=dict(type='base'), |
| @MODEL_REGISTRY.register('hpt') | ||
| class HPT(nn.Module): | ||
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| def __init__(self, state_dim, action_dim): |
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add overview and related introduction
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add unittest like other template in DI-engine
| policy=dict( | ||
| # Whether to use cuda for network. | ||
| cuda=True, | ||
| load_path="./lunarlander_hpt_seed0/ckpt/ckpt_best.pth.tar", |
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| # Migrating models to the GPU | ||
| device = torch.device("cuda" if torch.cuda.is_available() else "cpu") | ||
| model = HPT(cfg.policy.model.obs_shape, cfg.policy.model.action_shape).to(device) |
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add comments about the difference of HPT from normal model
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Description
Here are some tensorboard plots from the lunarlander_hpt_example.py run.
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