
from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


_snake_case      = logging.get_logger(__name__)

_snake_case      = {
    '''YituTech/conv-bert-base''': '''https://huggingface.co/YituTech/conv-bert-base/resolve/main/config.json''',
    '''YituTech/conv-bert-medium-small''': (
        '''https://huggingface.co/YituTech/conv-bert-medium-small/resolve/main/config.json'''
    ),
    '''YituTech/conv-bert-small''': '''https://huggingface.co/YituTech/conv-bert-small/resolve/main/config.json''',
    # See all ConvBERT models at https://huggingface.co/models?filter=convbert
}
class       _lowerCAmelCase  (		__magic_name__							):

 """simple docstring"""
 SCREAMING_SNAKE_CASE_				:					Optional[Any]       						="convbert"

 def __init__(						self			:			Any					, SCREAMING_SNAKE_CASE__			:			str=3_05_22					, SCREAMING_SNAKE_CASE__			:			List[Any]=7_68					, SCREAMING_SNAKE_CASE__			:			Tuple=12					, SCREAMING_SNAKE_CASE__			:			Optional[int]=12					, SCREAMING_SNAKE_CASE__			:			List[str]=30_72					, SCREAMING_SNAKE_CASE__			:			int="gelu"					, SCREAMING_SNAKE_CASE__			:			str=0.1					, SCREAMING_SNAKE_CASE__			:			Any=0.1					, SCREAMING_SNAKE_CASE__			:			List[Any]=5_12					, SCREAMING_SNAKE_CASE__			:			str=2					, SCREAMING_SNAKE_CASE__			:			Any=0.02					, SCREAMING_SNAKE_CASE__			:			Tuple=1e-12					, SCREAMING_SNAKE_CASE__			:			Optional[Any]=1					, SCREAMING_SNAKE_CASE__			:			Union[str, Any]=0					, SCREAMING_SNAKE_CASE__			:			int=2					, SCREAMING_SNAKE_CASE__			:			List[Any]=7_68					, SCREAMING_SNAKE_CASE__			:			str=2					, SCREAMING_SNAKE_CASE__			:			str=9					, SCREAMING_SNAKE_CASE__			:			Optional[int]=1					, SCREAMING_SNAKE_CASE__			:			List[str]=None					, **SCREAMING_SNAKE_CASE__			:			Union[str, Any]					, ):






      """simple docstring"""



      super().__init__(
          pad_token_id=SCREAMING_SNAKE_CASE__					, bos_token_id=SCREAMING_SNAKE_CASE__					, eos_token_id=SCREAMING_SNAKE_CASE__					, **SCREAMING_SNAKE_CASE__					, )

      UpperCamelCase						    =					vocab_size
      UpperCamelCase						    =					hidden_size
      UpperCamelCase						    =					num_hidden_layers
      UpperCamelCase						    =					num_attention_heads
      UpperCamelCase						    =					intermediate_size
      UpperCamelCase						    =					hidden_act
      UpperCamelCase						    =					hidden_dropout_prob
      UpperCamelCase						    =					attention_probs_dropout_prob
      UpperCamelCase						    =					max_position_embeddings
      UpperCamelCase						    =					type_vocab_size
      UpperCamelCase						    =					initializer_range
      UpperCamelCase						    =					layer_norm_eps
      UpperCamelCase						    =					embedding_size
      UpperCamelCase						    =					head_ratio
      UpperCamelCase						    =					conv_kernel_size
      UpperCamelCase						    =					num_groups
      UpperCamelCase						    =					classifier_dropout




class       _lowerCAmelCase  (		__magic_name__							):

 """simple docstring"""

 @property
 def      __lowerCAmelCase  (						self			:			Tuple   ):






      """simple docstring"""



      if self.task == "multiple-choice":
           UpperCamelCase						    =					{0: 'batch', 1: 'choice', 2: 'sequence'}
      else:
           UpperCamelCase						    =					{0: 'batch', 1: 'sequence'}
      return OrderedDict(
          [
              ('input_ids', dynamic_axis),
              ('attention_mask', dynamic_axis),
              ('token_type_ids', dynamic_axis),
          ]   )




import argparse
import shutil
from pathlib import Path

from tqdm import tqdm

from transformers import AutoTokenizer

def  __lowerCamelCase					( _lowercase						,     _lowercase						,     _lowercase						,     _lowercase=1024			)       ->      Union[str, Any]:
     UpperCamelCase    ,		UpperCamelCase						    =					[], []

     UpperCamelCase						    =					list(zip(_lowercase						,     _lowercase			)			)
     UpperCamelCase    ,		UpperCamelCase						    =					sorted_examples[0]

     def is_too_big(_lowercase			):
          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  __lowerCamelCase					( _lowercase						,     _lowercase						,     _lowercase						,     _lowercase			)       ->      Union[str, Any]:
     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  __lowerCamelCase					( )       ->      Union[str, Any]:
     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()


