Upload upload.py with huggingface_hub
Browse files
upload.py
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import os
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from huggingface_hub import HfApi
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import time
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from concurrent.futures import ThreadPoolExecutor
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from tqdm import tqdm
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def upload_single_file(args):
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file_path, path_in_repo, repo_id, max_retries = args
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api = HfApi()
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for attempt in range(max_retries):
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try:
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api.upload_file(
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path_or_fileobj=file_path,
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path_in_repo=path_in_repo,
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repo_id=repo_id,
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repo_type="model"
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)
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return True, path_in_repo, None
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except Exception as e:
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if attempt < max_retries - 1:
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time.sleep(10 * (attempt + 1))
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else:
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return False, path_in_repo, str(e)
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def upload_with_retry(folder_path, repo_id, max_retries=10, max_workers=4):
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# 获取所有文件
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files = []
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for root, _, filenames in os.walk(folder_path):
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for filename in filenames:
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if not any(pattern in filename for pattern in [".git"]):
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full_path = os.path.join(root, filename)
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relative_path = os.path.relpath(full_path, folder_path)
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files.append((full_path, relative_path))
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print(f"Found {len(files)} files to upload")
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# 准备上传参数
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upload_args = [
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(file_path, path_in_repo, repo_id, max_retries)
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for file_path, path_in_repo in files
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]
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# 并行上传
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failed_files = []
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with ThreadPoolExecutor(max_workers=max_workers) as executor:
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futures = list(tqdm(
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executor.map(upload_single_file, upload_args),
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total=len(files),
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desc="Uploading files"
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))
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# 处理结果
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for success, file_name, error in futures:
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if not success:
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failed_files.append((file_name, error))
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# 报告结果
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print(f"\nUpload completed!")
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print(f"Successfully uploaded: {len(files) - len(failed_files)} files")
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if failed_files:
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print("\nFailed uploads:")
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for file_name, error in failed_files:
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print(f"- {file_name}: {error}")
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# 使用
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upload_with_retry(
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".",
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"Neph0s/CoSER-Llama-3.1-70B",
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max_retries=10,
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max_workers=10 # 同时上传4个文件
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)
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