94 lines
2.5 KiB
Python
94 lines
2.5 KiB
Python
import dataclasses
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import enum
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import logging
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import time
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import numpy as np
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from openpi_client import websocket_client_policy as _websocket_client_policy
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import tyro
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class EnvMode(enum.Enum):
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"""Supported environments."""
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ALOHA = "aloha"
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ALOHA_SIM = "aloha_sim"
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DROID = "droid"
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CALVIN = "calvin"
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LIBERO = "libero"
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@dataclasses.dataclass
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class Args:
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host: str = "0.0.0.0"
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port: int = 8000
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env: EnvMode = EnvMode.ALOHA_SIM
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def main(args: Args) -> None:
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obs_fn = {
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EnvMode.ALOHA: _random_observation_aloha,
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EnvMode.ALOHA_SIM: _random_observation_aloha,
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EnvMode.DROID: _random_observation_droid,
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EnvMode.CALVIN: _random_observation_calvin,
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EnvMode.LIBERO: _random_observation_libero,
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}[args.env]
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policy = _websocket_client_policy.WebsocketClientPolicy(
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host=args.host,
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port=args.port,
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)
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# Send 1 observation to make sure the model is loaded.
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policy.infer(obs_fn())
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start = time.time()
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for _ in range(100):
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policy.infer(obs_fn())
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end = time.time()
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print(f"Total time taken: {end - start}")
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# Note that each inference returns many action chunks.
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print(f"Inference rate: {100 / (end - start)} Hz")
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def _random_observation_aloha() -> dict:
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return {
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"qpos": np.ones((14,)),
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"image": np.random.rand(4, 3, 480, 640).astype(np.float32),
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}
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def _random_observation_droid() -> dict:
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return {
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"observation/exterior_image_1_left": np.random.randint(256, size=(224, 224, 3), dtype=np.uint8),
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"observation/wrist_image_left": np.random.randint(256, size=(224, 224, 3), dtype=np.uint8),
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"observation/joint_position": np.random.rand(7),
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"observation/gripper_position": np.random.rand(1),
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"prompt": "do something",
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}
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def _random_observation_calvin() -> dict:
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return {
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"observation/state": np.random.rand(15),
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"observation/rgb_static": np.random.rand(4, 3, 480, 640).astype(np.float32),
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"observation/rgb_gripper": np.random.rand(4, 3, 480, 640).astype(np.float32),
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"prompt": "do something",
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}
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def _random_observation_libero() -> dict:
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return {
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"observation/state": np.random.rand(8),
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"observation/image": np.random.rand(4, 3, 480, 640).astype(np.float32),
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"observation/wrist_image": np.random.rand(4, 3, 480, 640).astype(np.float32),
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"prompt": "do something",
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}
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if __name__ == "__main__":
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logging.basicConfig(level=logging.INFO)
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tyro.cli(main)
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