29 lines
908 B
Python
29 lines
908 B
Python
import pytest
|
|
import torch
|
|
|
|
from lerobot.common.datasets.factory import make_offline_buffer
|
|
|
|
from .utils import DEVICE, init_config
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"env_name,dataset_id",
|
|
[
|
|
("simxarm", "lift"),
|
|
("pusht", "pusht"),
|
|
("aloha", "sim_insertion_human"),
|
|
("aloha", "sim_insertion_scripted"),
|
|
("aloha", "sim_transfer_cube_human"),
|
|
("aloha", "sim_transfer_cube_scripted"),
|
|
],
|
|
)
|
|
def test_factory(env_name, dataset_id):
|
|
cfg = init_config(overrides=[f"env={env_name}", f"env.task={dataset_id}", f"device={DEVICE}"])
|
|
offline_buffer = make_offline_buffer(cfg)
|
|
for key in offline_buffer.image_keys:
|
|
img = offline_buffer[0].get(key)
|
|
assert img.dtype == torch.float32
|
|
# TODO(rcadene): we assume for now that image normalization takes place in the model
|
|
assert img.max() <= 1.0
|
|
assert img.min() >= 0.0
|