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This commit is contained in:
Alexander Soare
2024-04-15 19:06:44 +01:00
parent 14f3ffb412
commit 5608e659e6
14 changed files with 1059 additions and 977 deletions
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72
lerobot/common/policies/factory.py
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@@ -1,59 +1,61 @@
import inspect
from omegaconf import OmegaConf
from omegaconf import DictConfig, OmegaConf
from lerobot.common.utils import get_safe_torch_device
def make_policy(cfg):
if cfg.policy.name == "tdmpc":
def _policy_cfg_from_hydra_cfg(policy_cfg_class, hydra_cfg):
expected_kwargs = set(inspect.signature(policy_cfg_class).parameters)
assert set(hydra_cfg.policy).issuperset(
expected_kwargs
), f"Hydra config is missing arguments: {set(hydra_cfg.policy).difference(expected_kwargs)}"
policy_cfg = policy_cfg_class(
**{
k: v
for k, v in OmegaConf.to_container(hydra_cfg.policy, resolve=True).items()
if k in expected_kwargs
}
)
return policy_cfg
def make_policy(hydra_cfg: DictConfig):
if hydra_cfg.policy.name == "tdmpc":
from lerobot.common.policies.tdmpc.policy import TDMPCPolicy
policy = TDMPCPolicy(
cfg.policy, n_obs_steps=cfg.n_obs_steps, n_action_steps=cfg.n_action_steps, device=cfg.device
hydra_cfg.policy,
n_obs_steps=hydra_cfg.n_obs_steps,
n_action_steps=hydra_cfg.n_action_steps,
device=hydra_cfg.device,
)
elif cfg.policy.name == "diffusion":
from lerobot.common.policies.diffusion.policy import DiffusionPolicy
elif hydra_cfg.policy.name == "diffusion":
from lerobot.common.policies.diffusion.configuration_diffusion import DiffusionConfig
from lerobot.common.policies.diffusion.modeling_diffusion import DiffusionPolicy
policy = DiffusionPolicy(
cfg=cfg.policy,
cfg_device=cfg.device,
cfg_noise_scheduler=cfg.noise_scheduler,
cfg_optimizer=cfg.optimizer,
cfg_ema=cfg.ema,
# n_obs_steps=cfg.n_obs_steps,
# n_action_steps=cfg.n_action_steps,
**cfg.policy,
)
elif cfg.policy.name == "act":
policy_cfg = _policy_cfg_from_hydra_cfg(DiffusionConfig, hydra_cfg)
policy = DiffusionPolicy(policy_cfg)
policy.to(get_safe_torch_device(hydra_cfg.device))
elif hydra_cfg.policy.name == "act":
from lerobot.common.policies.act.configuration_act import ActionChunkingTransformerConfig
from lerobot.common.policies.act.modeling_act import ActionChunkingTransformerPolicy
expected_kwargs = set(inspect.signature(ActionChunkingTransformerConfig).parameters)
assert set(cfg.policy).issuperset(
expected_kwargs
), f"Hydra config is missing arguments: {set(cfg.policy).difference(expected_kwargs)}"
policy_cfg = ActionChunkingTransformerConfig(
**{
k: v
for k, v in OmegaConf.to_container(cfg.policy, resolve=True).items()
if k in expected_kwargs
}
)
policy_cfg = _policy_cfg_from_hydra_cfg(ActionChunkingTransformerConfig, hydra_cfg)
policy = ActionChunkingTransformerPolicy(policy_cfg)
policy.to(get_safe_torch_device(cfg.device))
policy.to(get_safe_torch_device(hydra_cfg.device))
else:
raise ValueError(cfg.policy.name)
raise ValueError(hydra_cfg.policy.name)
if cfg.policy.pretrained_model_path:
if hydra_cfg.policy.pretrained_model_path:
# TODO(rcadene): hack for old pretrained models from fowm
if cfg.policy.name == "tdmpc" and "fowm" in cfg.policy.pretrained_model_path:
if "offline" in cfg.policy.pretrained_model_path:
if hydra_cfg.policy.name == "tdmpc" and "fowm" in hydra_cfg.policy.pretrained_model_path:
if "offline" in hydra_cfg.policy.pretrained_model_path:
policy.step[0] = 25000
elif "final" in cfg.policy.pretrained_model_path:
elif "final" in hydra_cfg.policy.pretrained_model_path:
policy.step[0] = 100000
else:
raise NotImplementedError()
policy.load(cfg.policy.pretrained_model_path)
policy.load(hydra_cfg.policy.pretrained_model_path)
return policy