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lerobot_piper/lerobot/common/envs/configs.py
Simon Alibert 3c0a209f9f Simplify configs (#550)
Co-authored-by: Remi <remi.cadene@huggingface.co>
Co-authored-by: HUANG TZU-CHUN <137322177+tc-huang@users.noreply.github.com>
2025-01-31 13:57:37 +01:00

143 lines
4.5 KiB
Python

import abc
from dataclasses import dataclass, field
import draccus
from lerobot.common.constants import ACTION, OBS_ENV, OBS_IMAGE, OBS_IMAGES, OBS_ROBOT
from lerobot.configs.types import FeatureType, PolicyFeature
@dataclass
class EnvConfig(draccus.ChoiceRegistry, abc.ABC):
task: str | None = None
fps: int = 30
features: dict[str, PolicyFeature] = field(default_factory=dict)
features_map: dict[str, str] = field(default_factory=dict)
@property
def type(self) -> str:
return self.get_choice_name(self.__class__)
@abc.abstractproperty
def gym_kwargs(self) -> dict:
raise NotImplementedError()
@EnvConfig.register_subclass("aloha")
@dataclass
class AlohaEnv(EnvConfig):
task: str = "AlohaInsertion-v0"
fps: int = 50
episode_length: int = 400
obs_type: str = "pixels_agent_pos"
render_mode: str = "rgb_array"
features: dict[str, PolicyFeature] = field(
default_factory=lambda: {
"action": PolicyFeature(type=FeatureType.ACTION, shape=(14,)),
}
)
features_map: dict[str, str] = field(
default_factory=lambda: {
"action": ACTION,
"agent_pos": OBS_ROBOT,
"top": f"{OBS_IMAGE}.top",
"pixels/top": f"{OBS_IMAGES}.top",
}
)
def __post_init__(self):
if self.obs_type == "pixels":
self.features["top"] = PolicyFeature(type=FeatureType.VISUAL, shape=(480, 640, 3))
elif self.obs_type == "pixels_agent_pos":
self.features["agent_pos"] = PolicyFeature(type=FeatureType.STATE, shape=(14,))
self.features["pixels/top"] = PolicyFeature(type=FeatureType.VISUAL, shape=(480, 640, 3))
@property
def gym_kwargs(self) -> dict:
return {
"obs_type": self.obs_type,
"render_mode": self.render_mode,
"max_episode_steps": self.episode_length,
}
@EnvConfig.register_subclass("pusht")
@dataclass
class PushtEnv(EnvConfig):
task: str = "PushT-v0"
fps: int = 10
episode_length: int = 300
obs_type: str = "pixels_agent_pos"
render_mode: str = "rgb_array"
visualization_width: int = 384
visualization_height: int = 384
features: dict[str, PolicyFeature] = field(
default_factory=lambda: {
"action": PolicyFeature(type=FeatureType.ACTION, shape=(2,)),
"agent_pos": PolicyFeature(type=FeatureType.STATE, shape=(2,)),
}
)
features_map: dict[str, str] = field(
default_factory=lambda: {
"action": ACTION,
"agent_pos": OBS_ROBOT,
"environment_state": OBS_ENV,
"pixels": OBS_IMAGE,
}
)
def __post_init__(self):
if self.obs_type == "pixels_agent_pos":
self.features["pixels"] = PolicyFeature(type=FeatureType.VISUAL, shape=(384, 384, 3))
elif self.obs_type == "environment_state_agent_pos":
self.features["environment_state"] = PolicyFeature(type=FeatureType.ENV, shape=(16,))
@property
def gym_kwargs(self) -> dict:
return {
"obs_type": self.obs_type,
"render_mode": self.render_mode,
"visualization_width": self.visualization_width,
"visualization_height": self.visualization_height,
"max_episode_steps": self.episode_length,
}
@EnvConfig.register_subclass("xarm")
@dataclass
class XarmEnv(EnvConfig):
task: str = "XarmLift-v0"
fps: int = 15
episode_length: int = 200
obs_type: str = "pixels_agent_pos"
render_mode: str = "rgb_array"
visualization_width: int = 384
visualization_height: int = 384
features: dict[str, PolicyFeature] = field(
default_factory=lambda: {
"action": PolicyFeature(type=FeatureType.ACTION, shape=(4,)),
"pixels": PolicyFeature(type=FeatureType.VISUAL, shape=(84, 84, 3)),
}
)
features_map: dict[str, str] = field(
default_factory=lambda: {
"action": ACTION,
"agent_pos": OBS_ROBOT,
"pixels": OBS_IMAGE,
}
)
def __post_init__(self):
if self.obs_type == "pixels_agent_pos":
self.features["agent_pos"] = PolicyFeature(type=FeatureType.STATE, shape=(4,))
@property
def gym_kwargs(self) -> dict:
return {
"obs_type": self.obs_type,
"render_mode": self.render_mode,
"visualization_width": self.visualization_width,
"visualization_height": self.visualization_height,
"max_episode_steps": self.episode_length,
}