lerobot/tests/test_envs.py

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import pytest
from tensordict import TensorDict
from torchrl.envs.utils import check_env_specs, step_mdp
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from lerobot.common.envs.factory import make_env
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from lerobot.common.envs.pusht.env import PushtEnv
from lerobot.common.envs.simxarm import SimxarmEnv
from .utils import init_config
def print_spec_rollout(env):
print("observation_spec:", env.observation_spec)
print("action_spec:", env.action_spec)
print("reward_spec:", env.reward_spec)
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print("done_spec:", env.done_spec)
td = env.reset()
print("reset tensordict", td)
td = env.rand_step(td)
print("random step tensordict", td)
def simple_rollout(steps=100):
# preallocate:
data = TensorDict({}, [steps])
# reset
_data = env.reset()
for i in range(steps):
_data["action"] = env.action_spec.rand()
_data = env.step(_data)
data[i] = _data
_data = step_mdp(_data, keep_other=True)
return data
print("data from rollout:", simple_rollout(100))
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@pytest.mark.skip(reason="Simxarm is deprecated")
@pytest.mark.parametrize(
"task,from_pixels,pixels_only",
[
("lift", False, False),
("lift", True, False),
("lift", True, True),
("reach", False, False),
("reach", True, False),
("push", False, False),
("push", True, False),
("peg_in_box", False, False),
("peg_in_box", True, False),
],
)
def test_simxarm(task, from_pixels, pixels_only):
env = SimxarmEnv(
task,
from_pixels=from_pixels,
pixels_only=pixels_only,
image_size=84 if from_pixels else None,
)
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# print_spec_rollout(env)
check_env_specs(env)
@pytest.mark.parametrize(
"from_pixels,pixels_only",
[
(True, False),
],
)
def test_pusht(from_pixels, pixels_only):
env = PushtEnv(
from_pixels=from_pixels,
pixels_only=pixels_only,
image_size=96 if from_pixels else None,
)
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# print_spec_rollout(env)
check_env_specs(env)
@pytest.mark.parametrize(
"env_name",
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[
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# "simxarm",
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"pusht",
],
)
def test_factory(env_name):
cfg = init_config(overrides=[f"env={env_name}"])
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env = make_env(cfg)
check_env_specs(env)