


'''simple docstring'''
import importlib.metadata
import operator
import re
import sys
from typing import Optional

from packaging import version


UpperCAmelCase_ :     Union[str, Any]								=      {
    '<': operator.lt,
    '<=': operator.le,
    '==': operator.eq,
    '!=': operator.ne,
    '>=': operator.ge,
    '>': operator.gt,
}


def 			_lowercase       (				UpperCamelCase__       :					str,				UpperCamelCase__       :					Dict,				UpperCamelCase__       :					Any,				UpperCamelCase__       :					int,				UpperCamelCase__       :					Union[str, Any],				UpperCamelCase__       :					List[Any]			):
 if got_ver is None or want_ver is None:
  raise ValueError(
      f"""Unable to compare versions for {requirement}: need={want_ver} found={got_ver}. This is unusual. Consider"""
      f""" reinstalling {pkg}."""			)
 if not ops[op](version.parse(UpperCamelCase__			),				version.parse(UpperCamelCase__			)			):
  raise ImportError(
      f"""{requirement} is required for a normal functioning of this module, but found {pkg}=={got_ver}.{hint}"""			)


def 			_lowercase       (				UpperCamelCase__       :					str,				UpperCamelCase__       :					Optional[str] = None			):
 __A  :		Tuple       =			f"""\n{hint}""" if hint is not None else ''

 # non-versioned check
 if re.match(r'^[\w_\-\d]+$',				UpperCamelCase__			):
  __A     ,__A     ,__A  :		Optional[Any]       =			requirement, None, None
 else:
  __A  :		Any       =			re.findall(r'^([^!=<>\s]+)([\s!=<>]{1,2}.+)',				UpperCamelCase__			)
  if not match:
   raise ValueError(
       'requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23, but'
       f""" got {requirement}"""			)
  __A     ,__A  :		Optional[Any]       =			match[0]
  __A  :		Optional[int]       =			want_full.split(','			)  # there could be multiple requirements
  __A  :		Union[str, Any]       =			{}
  for w in want_range:
   __A  :		str       =			re.findall(r'^([\s!=<>]{1,2})(.+)',				UpperCamelCase__			)
   if not match:
    raise ValueError(
        'requirement needs to be in the pip package format, .e.g., package_a==1.23, or package_b>=1.23,'
        f""" but got {requirement}"""			)
   __A     ,__A  :		int       =			match[0]
   __A  :		Optional[Any]       =			want_ver
   if op not in ops:
    raise ValueError(f"""{requirement}: need one of {list(ops.keys()			)}, but got {op}"""			)

    # special case
 if pkg == "python":
  __A  :		Dict       =			'.'.join([str(UpperCamelCase__			) for x in sys.version_info[:3]]			)
  for op, want_ver in wanted.items():
   _compare_versions(UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__			)
  return

 # check if any version is installed
 try:
  __A  :		Union[str, Any]       =			importlib.metadata.version(UpperCamelCase__			)
 except importlib.metadata.PackageNotFoundError:
  raise importlib.metadata.PackageNotFoundError(
      f"""The '{requirement}' distribution was not found and is required by this application. {hint}"""			)

 # check that the right version is installed if version number or a range was provided
 if want_ver is not None:
  for op, want_ver in wanted.items():
   _compare_versions(UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__,				UpperCamelCase__			)


def 			_lowercase       (				UpperCamelCase__       :					List[Any]			):
 __A  :		int       =			'Try: pip install transformers -U or pip install -e \'.[dev]\' if you\'re working with git main'
 return require_version(UpperCamelCase__,				UpperCamelCase__			)










'''simple docstring'''
import argparse
import logging
import pickle
import random
import time

import numpy as np

from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer


logging.basicConfig(
    format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO
)
UpperCAmelCase_ :     Any								=      logging.getLogger(__name__)


def 			_lowercase       (				):
 __A  :		Tuple       =			argparse.ArgumentParser(
     description='Preprocess the data to avoid re-doing it several times by (tokenization + token_to_ids).'			)
 parser.add_argument('--file_path',				type=UpperCamelCase__,				default='data/dump.txt',				help='The path to the data.'			)
 parser.add_argument('--tokenizer_type',				type=UpperCamelCase__,				default='bert',				choices=['bert', 'roberta', 'gpt2']			)
 parser.add_argument('--tokenizer_name',				type=UpperCamelCase__,				default='bert-base-uncased',				help='The tokenizer to use.'			)
 parser.add_argument('--dump_file',				type=UpperCamelCase__,				default='data/dump',				help='The dump file prefix.'			)
 __A  :		Tuple       =			parser.parse_args()

 logger.info(f"""Loading Tokenizer ({args.tokenizer_name})"""			)
 if args.tokenizer_type == "bert":
  __A  :		Any       =			BertTokenizer.from_pretrained(args.tokenizer_name			)
  __A  :		Any       =			tokenizer.special_tokens_map['cls_token']  # `[CLS]`
  __A  :		List[Any]       =			tokenizer.special_tokens_map['sep_token']  # `[SEP]`
 elif args.tokenizer_type == "roberta":
  __A  :		Any       =			RobertaTokenizer.from_pretrained(args.tokenizer_name			)
  __A  :		List[Any]       =			tokenizer.special_tokens_map['cls_token']  # `<s>`
  __A  :		Dict       =			tokenizer.special_tokens_map['sep_token']  # `</s>`
 elif args.tokenizer_type == "gpt2":
  __A  :		List[str]       =			GPTaTokenizer.from_pretrained(args.tokenizer_name			)
  __A  :		Any       =			tokenizer.special_tokens_map['bos_token']  # `<|endoftext|>`
  __A  :		Union[str, Any]       =			tokenizer.special_tokens_map['eos_token']  # `<|endoftext|>`

 logger.info(f"""Loading text from {args.file_path}"""			)
 with open(args.file_path,				'r',				encoding='utf8'			) as fp:
  __A  :		Optional[int]       =			fp.readlines()

 logger.info('Start encoding'			)
 logger.info(f"""{len(UpperCamelCase__			)} examples to process."""			)

 __A  :		int       =			[]
 __A  :		List[str]       =			0
 __A  :		Tuple       =			10000
 __A  :		List[str]       =			time.time()
 for text in data:
  __A  :		int       =			f"""{bos} {text.strip()} {sep}"""
  __A  :		List[Any]       =			tokenizer.encode(UpperCamelCase__,				add_special_tokens=UpperCamelCase__			)
  rslt.append(UpperCamelCase__			)

  iter += 1
  if iter % interval == 0:
   __A  :		Any       =			time.time()
   logger.info(f"""{iter} examples processed. - {(end-start):.2f}s/{interval}expl"""			)
   __A  :		Any       =			time.time()
 logger.info('Finished binarization'			)
 logger.info(f"""{len(UpperCamelCase__			)} examples processed."""			)

 __A  :		List[str]       =			f"""{args.dump_file}.{args.tokenizer_name}.pickle"""
 __A  :		str       =			tokenizer.vocab_size
 if vocab_size < (1 << 16):
  __A  :		Optional[int]       =			[np.uintaa(UpperCamelCase__			) for d in rslt]
 else:
  __A  :		int       =			[np.intaa(UpperCamelCase__			) for d in rslt]
 random.shuffle(rslt_			)
 logger.info(f"""Dump to {dp_file}"""			)
 with open(UpperCamelCase__,				'wb'			) as handle:
  pickle.dump(rslt_,				UpperCamelCase__,				protocol=pickle.HIGHEST_PROTOCOL			)


if __name__ == "__main__":
 main()






