




'''simple docstring'''







import os
import unittest

from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 					_a (a__,		unittest.TestCase	):





     '''simple docstring'''



     lowerCAmelCase_  :     str          =					LayoutLMTokenizer
     lowerCAmelCase_  :     Tuple          =					LayoutLMTokenizerFast
     lowerCAmelCase_  :     Optional[Any]          =					True
     lowerCAmelCase_  :     str          =					True







     def 			snake_case_      (				self							)      ->				Optional[Any]:
          super().setUp()

          snake_case			:      Optional[int]        =			[
              """[UNK]""",
              """[CLS]""",
              """[SEP]""",
              """want""",
              """##want""",
              """##ed""",
              """wa""",
              """un""",
              """runn""",
              """##ing""",
              """,""",
              """low""",
              """lowest""",
          ]
          snake_case			:      Optional[int]        =			os.path.join(self.tmpdirname							,VOCAB_FILES_NAMES["""vocab_file"""]							)
          with open(self.vocab_file							,"""w"""							,encoding="""utf-8"""							) as vocab_writer:
               vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]							)							)







     def 			snake_case_      (				self							,**__a							)      ->				List[str]:
          return LayoutLMTokenizer.from_pretrained(self.tmpdirname							,**__a							)







     def 			snake_case_      (				self							,__a							)      ->				Any:
          snake_case			:      Tuple        =			"""UNwant\u00E9d,running"""
          snake_case			:      Optional[Any]        =			"""unwanted, running"""
          return input_text, output_text







     def 			snake_case_      (				self							)      ->				Optional[int]:
          snake_case			:      Dict        =			self.tokenizer_class(self.vocab_file							)

          snake_case			:      Union[str, Any]        =			tokenizer.tokenize("""UNwant\u00E9d,running"""							)
          self.assertListEqual(__a							,["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""]							)
          self.assertListEqual(tokenizer.convert_tokens_to_ids(__a							)							,[7, 4, 5, 10, 8, 9]							)







     def 			snake_case_      (				self							)      ->				Tuple:
          pass









'''simple docstring'''







import argparse
import logging
import pickle
from collections import Counter


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

if __name__ == "__main__":
      lowercase      :   List[Any]      =       argparse.ArgumentParser(
          description="""Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)"""
      )
      parser.add_argument(
          """--data_file""", type=str, default="""data/dump.bert-base-uncased.pickle""", help="""The binarized dataset."""
      )
      parser.add_argument(
          """--token_counts_dump""", type=str, default="""data/token_counts.bert-base-uncased.pickle""", help="""The dump file."""
      )
      parser.add_argument("""--vocab_size""", default=3_0522, type=int)
      lowercase      :   str      =       parser.parse_args()

      logger.info(F"""Loading data from {args.data_file}""")
      with open(args.data_file, """rb""") as fp:
            lowercase      :   int      =       pickle.load(fp)

      logger.info("""Counting occurrences for MLM.""")
      lowercase      :   List[Any]      =       Counter()
      for tk_ids in data:
            counter.update(tk_ids)
      lowercase      :   int      =       [0] * args.vocab_size
      for k, v in counter.items():
            lowercase      :   List[Any]      =       v

      logger.info(F"""Dump to {args.token_counts_dump}""")
      with open(args.token_counts_dump, """wb""") as handle:
            pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)



