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#!/usr/bin/env python
# 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.
"""
Once you have trained a policy with our training script (lerobot/scripts/train.py), use this script to push it
to the hub.
Example:
```bash
python lerobot/scripts/push_pretrained.py \
--pretrained_path=outputs/train/act_aloha_sim_transfer_cube_human/checkpoints/last/pretrained_model \
--repo_id=lerobot/act_aloha_sim_transfer_cube_human
```
"""
from dataclasses import dataclass
from pathlib import Path
import draccus
from huggingface_hub import HfApi
@dataclass
class PushPreTrainedConfig:
pretrained_path: Path
repo_id: str
branch: str | None = None
private: bool = False
exist_ok: bool = False
@draccus.wrap()
def main(cfg: PushPreTrainedConfig):
hub_api = HfApi()
hub_api.create_repo(
repo_id=cfg.repo_id,
private=cfg.private,
repo_type="model",
exist_ok=cfg.exist_ok,
)
if cfg.branch:
hub_api.create_branch(
repo_id=cfg.repo_id,
branch=cfg.branch,
repo_type="model",
exist_ok=cfg.exist_ok,
)
hub_api.upload_folder(
repo_id=cfg.repo_id,
folder_path=cfg.pretrained_path,
repo_type="model",
revision=cfg.branch,
)
if __name__ == "__main__":
main()
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