wehub-resource-sync
91 lines
3.1 KiB
Python
91 lines
3.1 KiB
Python
# Copyright (c) 2025 ByteDance Ltd. and/or its affiliates.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# coding: utf-8
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"""
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Generic parquet/data file helpers that do not depend on cluster-specific settings.
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"""
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import os
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import logging
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from typing import Iterable, List, Optional
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import pyarrow.fs as pf
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import torch.distributed as dist
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logger = logging.getLogger(__name__)
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SUPPORTED_DATA_EXTENSIONS = (".parquet", ".json", ".jsonl")
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def select_supported_files(file_paths: Iterable[str]) -> List[str]:
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file_paths = list(file_paths)
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parquet_files = [path for path in file_paths if path.endswith(".parquet")]
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if parquet_files:
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return parquet_files
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return [path for path in file_paths if path.endswith((".json", ".jsonl"))]
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def list_local_supported_data_files(data_dir: str) -> List[str]:
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if os.path.isfile(data_dir):
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if not data_dir.endswith(SUPPORTED_DATA_EXTENSIONS):
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raise ValueError(f"Unsupported data file: {data_dir}")
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return [data_dir]
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if not os.path.isdir(data_dir):
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raise FileNotFoundError(f"Data path does not exist: {data_dir}")
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files = [
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os.path.join(data_dir, name)
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for name in os.listdir(data_dir)
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if name.endswith(SUPPORTED_DATA_EXTENSIONS)
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]
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return select_supported_files(files)
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def init_arrow_fs(parquet_file_path: str) -> pf.FileSystem:
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if parquet_file_path.startswith("hdfs://"):
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raise ValueError(f"Only local parquet files are supported, got remote path: {parquet_file_path}")
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return pf.LocalFileSystem()
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def init_arrow_pf_fs(parquet_file_path: str) -> pf.FileSystem:
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return init_arrow_fs(parquet_file_path)
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def get_parquet_data_paths_balanced(data_dir_list, rank=0, world_size=1, num_repeat=1):
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all_data_paths = []
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if rank == 0:
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logger.info("Rank 0 is gathering local data file paths...")
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for data_dir in data_dir_list:
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all_data_paths.extend(sorted(list_local_supported_data_files(data_dir)))
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logger.info(f"Total local data files found: {len(all_data_paths)}")
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if num_repeat > 1:
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original_len = len(all_data_paths)
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all_data_paths = all_data_paths * num_repeat
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logger.info(f"Repeating dataset {num_repeat} times, from {original_len} to {len(all_data_paths)} files.")
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if world_size > 1 and dist.is_available() and dist.is_initialized():
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object_list = [all_data_paths]
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dist.broadcast_object_list(object_list, src=0)
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return object_list[0]
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return all_data_paths
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def read_parquet_rows(parquet_file, row_group_id: int, columns: Optional[List[str]] = None):
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return parquet_file.read_row_group(row_group_id, columns=columns).to_pylist() |