



import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer


def A						(       __UpperCamelCase ,	__UpperCamelCase ,	__UpperCamelCase ,	__UpperCamelCase=1_024					)						->      Dict:
			A__     , A__       =    [], []

			A__       =    list(zip(__UpperCamelCase ,	__UpperCamelCase					)					)
			A__     , A__       =    sorted_examples[0]

			def is_too_big(__UpperCamelCase					):
						return tok(__UpperCamelCase ,	return_tensors='pt'					).input_ids.shape[1] > max_tokens

			for src, tgt in tqdm(sorted_examples[1:]					):
						A__       =    new_src + ' ' + src
						A__       =    new_tgt + ' ' + tgt
						if is_too_big(__UpperCamelCase					) or is_too_big(__UpperCamelCase					):  # cant fit, finalize example
									finished_src.append(__UpperCamelCase					)
									finished_tgt.append(__UpperCamelCase					)
									A__     , A__       =    src, tgt
						else:  # can fit, keep adding
									A__     , A__       =    cand_src, cand_tgt

    # cleanup
			if new_src:
						assert new_tgt
						finished_src.append(__UpperCamelCase					)
						finished_tgt.append(__UpperCamelCase					)
			return finished_src, finished_tgt


def A						(       __UpperCamelCase ,	__UpperCamelCase ,	__UpperCamelCase ,	__UpperCamelCase					)						->      List[Any]:
			A__       =    Path(__UpperCamelCase					)
			save_path.mkdir(exist_ok=__UpperCamelCase					)
			for split in ["train"]:
						A__     , A__       =    data_dir / f'''{split}.source''', data_dir / f'''{split}.target'''
						A__       =    [x.rstrip() for x in Path(__UpperCamelCase					).open().readlines()]
						A__       =    [x.rstrip() for x in Path(__UpperCamelCase					).open().readlines()]
						A__     , A__       =    pack_examples(__UpperCamelCase ,	__UpperCamelCase ,	__UpperCamelCase ,	__UpperCamelCase					)
						print(f'''packed {split} split from {len(__UpperCamelCase					)} examples -> {len(__UpperCamelCase					)}.'''					)
						Path(save_path / f'''{split}.source'''					).open('w'					).write('\n'.join(__UpperCamelCase					)					)
						Path(save_path / f'''{split}.target'''					).open('w'					).write('\n'.join(__UpperCamelCase					)					)
			for split in ["val", "test"]:
						A__     , A__       =    data_dir / f'''{split}.source''', data_dir / f'''{split}.target'''
						shutil.copyfile(__UpperCamelCase ,	save_path / f'''{split}.source'''					)
						shutil.copyfile(__UpperCamelCase ,	save_path / f'''{split}.target'''					)


def A						(       )						->      str:
			A__       =    argparse.ArgumentParser()
			parser.add_argument('--tok_name' ,	type=__UpperCamelCase ,	help='like facebook/bart-large-cnn,t5-base, etc.'					)
			parser.add_argument('--max_seq_len' ,	type=__UpperCamelCase ,	default=128					)
			parser.add_argument('--data_dir' ,	type=__UpperCamelCase					)
			parser.add_argument('--save_path' ,	type=__UpperCamelCase					)
			A__       =    parser.parse_args()
			A__       =    AutoTokenizer.from_pretrained(args.tok_name					)
			return pack_data_dir(__UpperCamelCase ,	Path(args.data_dir					) ,	args.max_seq_len ,	args.save_path					)


if __name__ == "__main__":
							packer_cli()









from typing import TYPE_CHECKING

from ..utils import _LazyModule


SCREAMING_SNAKE_CASE__       =      {
    '''config''': [
        '''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
        '''OnnxConfig''',
        '''OnnxConfigWithPast''',
        '''OnnxSeq2SeqConfigWithPast''',
        '''PatchingSpec''',
    ],
    '''convert''': ['''export''', '''validate_model_outputs'''],
    '''features''': ['''FeaturesManager'''],
    '''utils''': ['''ParameterFormat''', '''compute_serialized_parameters_size'''],
}


if TYPE_CHECKING:
							from .config import (
							    EXTERNAL_DATA_FORMAT_SIZE_LIMIT,
							    OnnxConfig,
							    OnnxConfigWithPast,
							    OnnxSeqaSeqConfigWithPast,
							    PatchingSpec,
							)
							from .convert import export, validate_model_outputs
							from .features import FeaturesManager
							from .utils import ParameterFormat, compute_serialized_parameters_size

else:
							import sys

							SCREAMING_SNAKE_CASE__       =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




