





'''simple docstring'''
import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer
def 				lowercase__   (   __lowercase						:  int				,  __lowercase						:  Optional[Any]				,  __lowercase						:  Dict				,  __lowercase						:  Optional[int]=1024     ) ->      Dict:



       """simple docstring"""






       __UpperCamelCase       ,						__UpperCamelCase       =  [], []

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

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

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

    # cleanup
       if new_src:
              assert new_tgt
              finished_src.append(__lowercase     )
              finished_tgt.append(__lowercase     )
       return finished_src, finished_tgt
def 				lowercase__   (   __lowercase						:  List[str]				,  __lowercase						:  Path				,  __lowercase						:  Dict				,  __lowercase						:  Dict     ) ->      Optional[Any]:



       """simple docstring"""






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



       """simple docstring"""






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


if __name__ == "__main__":
    packer_cli()







'''simple docstring'''
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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.

# this script dumps information about the environment

import os
import platform
import sys


a__							:							Tuple ='''3'''

print('''Python version:''', sys.version)

print('''OS platform:''', platform.platform())
print('''OS architecture:''', platform.machine())

try:
    import torch

    print('''Torch version:''', torch.__version__)
    print('''Cuda available:''', torch.cuda.is_available())
    print('''Cuda version:''', torch.version.cuda)
    print('''CuDNN version:''', torch.backends.cudnn.version())
    print('''Number of GPUs available:''', torch.cuda.device_count())
except ImportError:
    print('''Torch version:''', None)

try:
    import transformers

    print('''transformers version:''', transformers.__version__)
except ImportError:
    print('''transformers version:''', None)
