






'''simple docstring'''



import argparse
import collections
import os
import re

from transformers.utils import direct_transformers_import


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
SCREAMING_SNAKE_CASE							=						'src/transformers'
SCREAMING_SNAKE_CASE							=						'docs/source/en'
SCREAMING_SNAKE_CASE							=						'.'


def 				lowercase_					(     __A			:							List[Any]       ,   __A			:							Dict       ,   __A			:							int      )							->   List[str]:



 """simple docstring"""




 with open(__A       ,   '''r'''       ,   encoding='''utf-8'''       ,   newline='''\n'''      ) as f:
  lowercase       : Optional[Any]						=f.readlines()
 # Find the start prompt.
 lowercase       : Optional[int]						=0
 while not lines[start_index].startswith(__A      ):
  start_index += 1
 start_index += 1

 lowercase       : str						=start_index
 while not lines[end_index].startswith(__A      ):
  end_index += 1
 end_index -= 1

 while len(lines[start_index]      ) <= 1:
  start_index += 1
 while len(lines[end_index]      ) <= 1:
  end_index -= 1
 end_index += 1
 return "".join(lines[start_index:end_index]      ), start_index, end_index, lines


# Add here suffixes that are used to identify models, separated by |
SCREAMING_SNAKE_CASE							=						'Model|Encoder|Decoder|ForConditionalGeneration'
# Regexes that match TF/Flax/PT model names.
SCREAMING_SNAKE_CASE							=						re.compile(r'TF(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)')
SCREAMING_SNAKE_CASE							=						re.compile(r'Flax(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)')
# Will match any TF or Flax model too so need to be in an else branch afterthe two previous regexes.
SCREAMING_SNAKE_CASE							=						re.compile(r'(.*)(?:Model|Encoder|Decoder|ForConditionalGeneration)')


# This is to make sure the transformers module imported is the one in the repo.
SCREAMING_SNAKE_CASE							=						direct_transformers_import(TRANSFORMERS_PATH)


def 				lowercase_					(     __A			:							Union[str, Any]      )							->   Union[str, Any]:



 """simple docstring"""




 lowercase       : Optional[int]						=re.finditer('''.+?(?:(?<=[a-z])(?=[A-Z])|(?<=[A-Z])(?=[A-Z][a-z])|$)'''       ,   __A      )
 return [m.group(0      ) for m in matches]


def 				lowercase_					(     __A			:							Tuple       ,   __A			:							List[Any]      )							->   int:



 """simple docstring"""




 lowercase       : int						=2 if text == '''✅''' or text == '''❌''' else len(__A      )
 lowercase       : int						=(width - text_length) // 2
 lowercase       : Dict						=width - text_length - left_indent
 return " " * left_indent + text + " " * right_indent


def 				lowercase_					(     )							->   int:



 """simple docstring"""




 lowercase       : List[str]						=transformers_module.models.auto.configuration_auto.CONFIG_MAPPING_NAMES
 lowercase       : Union[str, Any]						={
     name: config_maping_names[code]
     for code, name in transformers_module.MODEL_NAMES_MAPPING.items()
     if code in config_maping_names
 }
 lowercase       : Dict						={name: config.replace('''Config'''       ,   ''''''      ) for name, config in model_name_to_config.items()}

 # Dictionaries flagging if each model prefix has a slow/fast tokenizer, backend in PT/TF/Flax.
 lowercase       : Optional[int]						=collections.defaultdict(__A      )
 lowercase       : List[Any]						=collections.defaultdict(__A      )
 lowercase       : List[Any]						=collections.defaultdict(__A      )
 lowercase       : str						=collections.defaultdict(__A      )
 lowercase       : int						=collections.defaultdict(__A      )

 # Let's lookup through all transformers object (once).
 for attr_name in dir(__A      ):
  lowercase       : int						=None
  if attr_name.endswith('''Tokenizer'''      ):
   lowercase       : Optional[Any]						=slow_tokenizers
   lowercase       : Dict						=attr_name[:-9]
  elif attr_name.endswith('''TokenizerFast'''      ):
   lowercase       : Optional[int]						=fast_tokenizers
   lowercase       : Optional[Any]						=attr_name[:-1_3]
  elif _re_tf_models.match(__A      ) is not None:
   lowercase       : Optional[Any]						=tf_models
   lowercase       : Any						=_re_tf_models.match(__A      ).groups()[0]
  elif _re_flax_models.match(__A      ) is not None:
   lowercase       : Any						=flax_models
   lowercase       : Optional[int]						=_re_flax_models.match(__A      ).groups()[0]
  elif _re_pt_models.match(__A      ) is not None:
   lowercase       : List[str]						=pt_models
   lowercase       : Dict						=_re_pt_models.match(__A      ).groups()[0]

  if lookup_dict is not None:
   while len(__A      ) > 0:
    if attr_name in model_name_to_prefix.values():
     lowercase       : Optional[int]						=True
     break
    # Try again after removing the last word in the name
    lowercase       : List[str]						=''''''.join(camel_case_split(__A      )[:-1]      )

    # Let's build that table!
 lowercase       : List[Any]						=list(model_name_to_config.keys()      )
 model_names.sort(key=str.lower      )
 lowercase       : Tuple						=['''Model''', '''Tokenizer slow''', '''Tokenizer fast''', '''PyTorch support''', '''TensorFlow support''', '''Flax Support''']
 # We'll need widths to properly display everything in the center (+2 is to leave one extra space on each side).
 lowercase       : Optional[Any]						=[len(__A      ) + 2 for c in columns]
 lowercase       : int						=max([len(__A      ) for name in model_names]      ) + 2

 # Build the table per se
 lowercase       : Any						='''|''' + '''|'''.join([_center_text(__A       ,   __A      ) for c, w in zip(__A       ,   __A      )]      ) + '''|\n'''
 # Use ":-----:" format to center-aligned table cell texts
 table += "|" + "|".join([''':''' + '''-''' * (w - 2) + ''':''' for w in widths]      ) + "|\n"

 lowercase       : Dict						={True: '''✅''', False: '''❌'''}
 for name in model_names:
  lowercase       : Dict						=model_name_to_prefix[name]
  lowercase       : Dict						=[
      name,
      check[slow_tokenizers[prefix]],
      check[fast_tokenizers[prefix]],
      check[pt_models[prefix]],
      check[tf_models[prefix]],
      check[flax_models[prefix]],
  ]
  table += "|" + "|".join([_center_text(__A       ,   __A      ) for l, w in zip(__A       ,   __A      )]      ) + "|\n"
 return table


def 				lowercase_					(     __A			:							Any=False      )							->   Optional[Any]:



 """simple docstring"""




 lowercase	,		lowercase	,		lowercase	,		lowercase       : Optional[Any]						=_find_text_in_file(
     filename=os.path.join(__A       ,   '''index.md'''      )       ,   start_prompt='''<!--This table is updated automatically from the auto modules'''       ,   end_prompt='''<!-- End table-->'''       ,   )
 lowercase       : List[Any]						=get_model_table_from_auto_modules()

 if current_table != new_table:
  if overwrite:
   with open(os.path.join(__A       ,   '''index.md'''      )       ,   '''w'''       ,   encoding='''utf-8'''       ,   newline='''\n'''      ) as f:
    f.writelines(lines[:start_index] + [new_table] + lines[end_index:]      )
  else:
   raise ValueError(
       '''The model table in the `index.md` has not been updated. Run `make fix-copies` to fix this.'''      )


if __name__ == "__main__":
      SCREAMING_SNAKE_CASE							=						argparse.ArgumentParser()
      parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
      SCREAMING_SNAKE_CASE							=						parser.parse_args()

      check_model_table(args.fix_and_overwrite)





import os
import unittest

from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, ProphetNetTokenizer
from transformers.testing_utils import require_torch, slow

from ...test_tokenization_common import TokenizerTesterMixin





class    __A(					UpperCAmelCase  ,		unittest.TestCase							):
					SCREAMING_SNAKE_CASE           =     ProphetNetTokenizer
					SCREAMING_SNAKE_CASE           =     False

					def  lowercase__   (						self       :  Optional[Any] ):
												super().setUp()

												lowerCamelCase_					=       [
												    """[UNK]""",
												    """[CLS]""",
												    """[SEP]""",
												    """[PAD]""",
												    """[MASK]""",
												    """want""",
												    """##want""",
												    """##ed""",
												    """wa""",
												    """un""",
												    """runn""",
												    """##ing""",
												    """,""",
												    """low""",
												    """lowest""",
												]
												lowerCamelCase_					=       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  lowercase__   (						self       :  int ,       __UpperCamelCase       :  int ):
												lowerCamelCase_					=       """UNwant\u00E9d,running"""
												lowerCamelCase_					=       """unwanted, running"""
												return input_text, output_text

					def  lowercase__   (						self       :  Optional[int] ):
												lowerCamelCase_					=       self.tokenizer_class(self.vocab_file )

												lowerCamelCase_					=       tokenizer.tokenize("""UNwant\u00E9d,running""" )
												self.assertListEqual(__UpperCamelCase ,       ["""un""", """##want""", """##ed""", """,""", """runn""", """##ing"""] )
												self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase ) ,       [9, 6, 7, 1_2, 1_0, 1_1] )

					def  lowercase__   (						self       :  Tuple ):
												lowerCamelCase_					=       BasicTokenizer()

												self.assertListEqual(tokenizer.tokenize("""ah\u535A\u63A8zz""" ) ,       ["""ah""", """\u535A""", """\u63A8""", """zz"""] )

					def  lowercase__   (						self       :  Union[str, Any] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """ ) ,       ["""hello""", """!""", """how""", """are""", """you""", """?"""] )
												self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" ) ,       ["""hello"""] )

					def  lowercase__   (						self       :  Optional[Any] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase ,       strip_accents=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ ) ,       ["""hällo""", """!""", """how""", """are""", """you""", """?"""] )
												self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" ) ,       ["""h\u00E9llo"""] )

					def  lowercase__   (						self       :  Optional[int] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase ,       strip_accents=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ ) ,       ["""hallo""", """!""", """how""", """are""", """you""", """?"""] )
												self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" ) ,       ["""hello"""] )

					def  lowercase__   (						self       :  List[Any] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ ) ,       ["""hallo""", """!""", """how""", """are""", """you""", """?"""] )
												self.assertListEqual(tokenizer.tokenize("""H\u00E9llo""" ) ,       ["""hello"""] )

					def  lowercase__   (						self       :  List[str] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU?  """ ) ,       ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?"""] )

					def  lowercase__   (						self       :  int ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase ,       strip_accents=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ ) ,       ["""HäLLo""", """!""", """how""", """Are""", """yoU""", """?"""] )

					def  lowercase__   (						self       :  Optional[Any] ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase ,       strip_accents=__UpperCamelCase )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHäLLo!how  \n Are yoU?  """ ) ,       ["""HaLLo""", """!""", """how""", """Are""", """yoU""", """?"""] )

					def  lowercase__   (						self       :  Dict ):
												lowerCamelCase_					=       BasicTokenizer(do_lower_case=__UpperCamelCase ,       never_split=["""[UNK]"""] )

												self.assertListEqual(
												    tokenizer.tokenize(""" \tHeLLo!how  \n Are yoU? [UNK]""" ) ,       ["""HeLLo""", """!""", """how""", """Are""", """yoU""", """?""", """[UNK]"""] )

					def  lowercase__   (						self       :  List[str] ):
												lowerCamelCase_					=       ["""[UNK]""", """[CLS]""", """[SEP]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing"""]

												lowerCamelCase_					=       {}
												for i, token in enumerate(__UpperCamelCase ):
																			lowerCamelCase_					=       i
												lowerCamelCase_					=       WordpieceTokenizer(vocab=__UpperCamelCase ,       unk_token="""[UNK]""" )

												self.assertListEqual(tokenizer.tokenize("""""" ) ,       [] )

												self.assertListEqual(tokenizer.tokenize("""unwanted running""" ) ,       ["""un""", """##want""", """##ed""", """runn""", """##ing"""] )

												self.assertListEqual(tokenizer.tokenize("""unwantedX running""" ) ,       ["""[UNK]""", """runn""", """##ing"""] )

					@require_torch
					def  lowercase__   (						self       :  int ):
												lowerCamelCase_					=       self.tokenizer_class.from_pretrained("""microsoft/prophetnet-large-uncased""" )

												lowerCamelCase_					=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
												lowerCamelCase_					=       [1_0_3_7, 2_1_4_6, 2_0_4_2_3, 2_0_0_5, 7_6_8_0, 7_8_4_9, 3_9_8_9, 1_0_1_2, 1_0_2]
												lowerCamelCase_					=       tokenizer(__UpperCamelCase ,       padding=__UpperCamelCase ,       return_tensors="""pt""" )
												self.assertIsInstance(__UpperCamelCase ,       __UpperCamelCase )
												lowerCamelCase_					=       list(batch.input_ids.numpy()[0] )
												self.assertListEqual(__UpperCamelCase ,       __UpperCamelCase )

												self.assertEqual((2, 9) ,       batch.input_ids.shape )
												self.assertEqual((2, 9) ,       batch.attention_mask.shape )

					def  lowercase__   (						self       :  List[str] ):
												self.assertTrue(_is_whitespace(""" """ ) )
												self.assertTrue(_is_whitespace("""\t""" ) )
												self.assertTrue(_is_whitespace("""\r""" ) )
												self.assertTrue(_is_whitespace("""\n""" ) )
												self.assertTrue(_is_whitespace("""\u00A0""" ) )

												self.assertFalse(_is_whitespace("""A""" ) )
												self.assertFalse(_is_whitespace("""-""" ) )

					def  lowercase__   (						self       :  Union[str, Any] ):
												self.assertTrue(_is_control("""\u0005""" ) )

												self.assertFalse(_is_control("""A""" ) )
												self.assertFalse(_is_control(""" """ ) )
												self.assertFalse(_is_control("""\t""" ) )
												self.assertFalse(_is_control("""\r""" ) )

					def  lowercase__   (						self       :  Tuple ):
												self.assertTrue(_is_punctuation("""-""" ) )
												self.assertTrue(_is_punctuation("""$""" ) )
												self.assertTrue(_is_punctuation("""`""" ) )
												self.assertTrue(_is_punctuation(""".""" ) )

												self.assertFalse(_is_punctuation("""A""" ) )
												self.assertFalse(_is_punctuation(""" """ ) )



					@slow
					def  lowercase__   (						self       :  str ):
												lowerCamelCase_					=       self.tokenizer_class.from_pretrained("""microsoft/prophetnet-large-uncased""" )

												lowerCamelCase_					=       tokenizer.encode("""sequence builders""" ,       add_special_tokens=__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.encode("""multi-sequence build""" ,       add_special_tokens=__UpperCamelCase )

												lowerCamelCase_					=       tokenizer.build_inputs_with_special_tokens(__UpperCamelCase )
												lowerCamelCase_					=       tokenizer.build_inputs_with_special_tokens(__UpperCamelCase ,       __UpperCamelCase )

												assert encoded_sentence == text + [1_0_2]
												assert encoded_pair == text + [1_0_2] + text_a + [1_0_2]





