Add pusht test artifact

This commit is contained in:
Simon Alibert 2024-03-08 15:54:30 +01:00
parent 7dbdbb051c
commit 89eaab140b
19 changed files with 42 additions and 0 deletions

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.gitattributes vendored Normal file
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*.memmap filter=lfs diff=lfs merge=lfs -text

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@ -17,6 +17,7 @@ jobs:
runs-on: ubuntu-latest runs-on: ubuntu-latest
env: env:
POETRY_VERSION: 1.8.1 POETRY_VERSION: 1.8.1
DATA_DIR: tests/data
steps: steps:
#---------------------------------------------- #----------------------------------------------
# check-out repo and set-up python # check-out repo and set-up python

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.gitignore vendored
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@ -54,6 +54,7 @@ pip-log.txt
pip-delete-this-directory.txt pip-delete-this-directory.txt
# Unit test / coverage reports # Unit test / coverage reports
!tests/data
htmlcov/ htmlcov/
.tox/ .tox/
.nox/ .nox/

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@ -125,6 +125,9 @@ class PushtExperienceReplay(AbstractExperienceReplay):
episode_ids = torch.from_numpy(dataset_dict.get_episode_idxs()) episode_ids = torch.from_numpy(dataset_dict.get_episode_idxs())
num_episodes = dataset_dict.meta["episode_ends"].shape[0] num_episodes = dataset_dict.meta["episode_ends"].shape[0]
total_frames = dataset_dict["action"].shape[0] total_frames = dataset_dict["action"].shape[0]
# to create test artifact
# num_episodes = 1
# total_frames = 50
assert len( assert len(
{dataset_dict[key].shape[0] for key in dataset_dict.keys()} # noqa: SIM118 {dataset_dict[key].shape[0] for key in dataset_dict.keys()} # noqa: SIM118
), "Some data type dont have the same number of total frames." ), "Some data type dont have the same number of total frames."
@ -142,6 +145,8 @@ class PushtExperienceReplay(AbstractExperienceReplay):
idxtd = 0 idxtd = 0
for episode_id in tqdm.tqdm(range(num_episodes)): for episode_id in tqdm.tqdm(range(num_episodes)):
idx1 = dataset_dict.meta["episode_ends"][episode_id] idx1 = dataset_dict.meta["episode_ends"][episode_id]
# to create test artifact
# idx1 = 51
num_frames = idx1 - idx0 num_frames = idx1 - idx0

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tests/data/meta.json Normal file
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{"action": {"device": "cpu", "shape": [50, 2], "dtype": "torch.float32"}, "episode": {"device": "cpu", "shape": [50], "dtype": "torch.int64"}, "frame_id": {"device": "cpu", "shape": [50], "dtype": "torch.int64"}, "shape": [50], "device": "cpu", "_type": "<class 'tensordict._td.TensorDict'>"}

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