Spaces:
Running
Running
File size: 3,225 Bytes
529ed6b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 |
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import logging
import traceback
from pathlib import Path
from datasets import get_dataset_config_info
from huggingface_hub import HfApi
from lerobot import available_datasets
from lerobot.common.datasets.lerobot_dataset import LeRobotDatasetMetadata
from lerobot.common.datasets.utils import INFO_PATH, write_info
from lerobot.common.datasets.v21.convert_dataset_v20_to_v21 import V20, SuppressWarnings
LOCAL_DIR = Path("data/")
hub_api = HfApi()
def fix_dataset(repo_id: str) -> str:
if not hub_api.revision_exists(repo_id, V20, repo_type="dataset"):
return f"{repo_id}: skipped (not in {V20})."
dataset_info = get_dataset_config_info(repo_id, "default")
with SuppressWarnings():
lerobot_metadata = LeRobotDatasetMetadata(repo_id, revision=V20, force_cache_sync=True)
meta_features = {key for key, ft in lerobot_metadata.features.items() if ft["dtype"] != "video"}
parquet_features = set(dataset_info.features)
diff_parquet_meta = parquet_features - meta_features
diff_meta_parquet = meta_features - parquet_features
if diff_parquet_meta:
raise ValueError(f"In parquet not in info.json: {parquet_features - meta_features}")
if not diff_meta_parquet:
return f"{repo_id}: skipped (no diff)"
if diff_meta_parquet:
logging.warning(f"In info.json not in parquet: {meta_features - parquet_features}")
assert diff_meta_parquet == {"language_instruction"}
lerobot_metadata.features.pop("language_instruction")
write_info(lerobot_metadata.info, lerobot_metadata.root)
commit_info = hub_api.upload_file(
path_or_fileobj=lerobot_metadata.root / INFO_PATH,
path_in_repo=INFO_PATH,
repo_id=repo_id,
repo_type="dataset",
revision=V20,
commit_message="Remove 'language_instruction'",
create_pr=True,
)
return f"{repo_id}: success - PR: {commit_info.pr_url}"
def batch_fix():
status = {}
LOCAL_DIR.mkdir(parents=True, exist_ok=True)
logfile = LOCAL_DIR / "fix_features_v20.txt"
for num, repo_id in enumerate(available_datasets):
print(f"\nConverting {repo_id} ({num}/{len(available_datasets)})")
print("---------------------------------------------------------")
try:
status = fix_dataset(repo_id)
except Exception:
status = f"{repo_id}: failed\n {traceback.format_exc()}"
logging.info(status)
with open(logfile, "a") as file:
file.write(status + "\n")
if __name__ == "__main__":
batch_fix()
|