




import argparse
from collections import defaultdict

def    UpperCAmelCase_				( __UpperCAmelCase		:      List[Any]     ,     __UpperCAmelCase		:      List[str]     ,     __UpperCAmelCase		:      List[str]     ,     __UpperCAmelCase		:      Any     ,     __UpperCAmelCase		:      Any				)   ->					Dict:
      SCREAMING_SNAKE_CASE_      		=     f"{file}_{class_name}_{test_name}"
      done_test[_id] += 1

      with open(__UpperCAmelCase     ,     'r'				) as f:
            SCREAMING_SNAKE_CASE_      		=     f.readlines()

      SCREAMING_SNAKE_CASE_      		=     f"class {class_name}("
      SCREAMING_SNAKE_CASE_      		=     f"{4 * ' '}def {test_name}("
      SCREAMING_SNAKE_CASE_      		=     f"{8 * ' '}{correct_line.split()[0]}"
      SCREAMING_SNAKE_CASE_      		=     f"{16 * ' '}{correct_line.split()[0]}"
      SCREAMING_SNAKE_CASE_      		=     False
      SCREAMING_SNAKE_CASE_      		=     False
      SCREAMING_SNAKE_CASE_      		=     False
      SCREAMING_SNAKE_CASE_      		=     False
      SCREAMING_SNAKE_CASE_      		=     0
      SCREAMING_SNAKE_CASE_      		=     0

      SCREAMING_SNAKE_CASE_      		=     []
      for line in lines:
            if line.startswith(__UpperCAmelCase				):
                  SCREAMING_SNAKE_CASE_      		=     True
            elif in_class and line.startswith(__UpperCAmelCase				):
                  SCREAMING_SNAKE_CASE_      		=     True
            elif in_class and in_func and (line.startswith(__UpperCAmelCase				) or line.startswith(__UpperCAmelCase				)):
                  SCREAMING_SNAKE_CASE_      		=     len(line.split(correct_line.split()[0]				)[0]				)
                  count += 1

                  if count == done_test[_id]:
                        SCREAMING_SNAKE_CASE_      		=     True

            if in_class and in_func and in_line:
                  if ")" not in line:
                        continue
                  else:
                        SCREAMING_SNAKE_CASE_      		=     True

            if in_class and in_func and in_line and insert_line:
                  new_lines.append(f"{spaces * ' '}{correct_line}"				)
                  SCREAMING_SNAKE_CASE_      		=     SCREAMING_SNAKE_CASE_      		=     SCREAMING_SNAKE_CASE_      		=     SCREAMING_SNAKE_CASE_      		=     False
            else:
                  new_lines.append(__UpperCAmelCase				)

      with open(__UpperCAmelCase     ,     'w'				) as f:
            for line in new_lines:
                  f.write(__UpperCAmelCase				)

def    UpperCAmelCase_				( __UpperCAmelCase		:      Any     ,     __UpperCAmelCase		:      str=None				)   ->					Tuple:
      if fail is not None:
            with open(__UpperCAmelCase     ,     'r'				) as f:
                  SCREAMING_SNAKE_CASE_      		=     {l.strip() for l in f.readlines()}
      else:
            SCREAMING_SNAKE_CASE_      		=     None

      with open(__UpperCAmelCase     ,     'r'				) as f:
            SCREAMING_SNAKE_CASE_      		=     f.readlines()

      SCREAMING_SNAKE_CASE_      		=     defaultdict(__UpperCAmelCase				)
      for line in correct_lines:
            SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_		,					SCREAMING_SNAKE_CASE_      		=     line.split(';'				)
            if test_failures is None or "::".join([file, class_name, test_name]				) in test_failures:
                  overwrite_file(__UpperCAmelCase     ,     __UpperCAmelCase     ,     __UpperCAmelCase     ,     __UpperCAmelCase     ,     __UpperCAmelCase				)


if __name__ == "__main__":
   lowerCamelCase__					:  Optional[Any]      							=				argparse.ArgumentParser()
   parser.add_argument('--correct_filename', help='filename of tests with expected result')
   parser.add_argument('--fail_filename', help='filename of test failures', type=str, default=None)
   lowerCamelCase__					:  int      							=				parser.parse_args()

   main(args.correct_filename, args.fail_filename)





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


if is_sentencepiece_available():
   from ..ta.tokenization_ta import TaTokenizer
else:
   from ...utils.dummy_sentencepiece_objects import TaTokenizer

lowerCamelCase__					:  List[Any]      							=				TaTokenizer

if is_tokenizers_available():
   from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
   from ...utils.dummy_tokenizers_objects import TaTokenizerFast

lowerCamelCase__					:  Union[str, Any]      							=				TaTokenizerFast

lowerCamelCase__					:  Dict      							=				{'configuration_mt5': ['MT5Config', 'MT5OnnxConfig']}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				[
       'MT5EncoderModel',
       'MT5ForConditionalGeneration',
       'MT5ForQuestionAnswering',
       'MT5Model',
       'MT5PreTrainedModel',
       'MT5Stack',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				['TFMT5EncoderModel', 'TFMT5ForConditionalGeneration', 'TFMT5Model']

try:
   if not is_flax_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase__					:  Tuple      							=				['FlaxMT5EncoderModel', 'FlaxMT5ForConditionalGeneration', 'FlaxMT5Model']


if TYPE_CHECKING:
   from .configuration_mta import MTaConfig, MTaOnnxConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mta import (
          MTaEncoderModel,
          MTaForConditionalGeneration,
          MTaForQuestionAnswering,
          MTaModel,
          MTaPreTrainedModel,
          MTaStack,
      )

   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

   try:
      if not is_flax_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
   import sys

   lowerCamelCase__					:  int      							=				_LazyModule(
       __name__,
       globals()['__file__'],
       _import_structure,
       extra_objects={'MT5Tokenizer': MTaTokenizer, 'MT5TokenizerFast': MTaTokenizerFast},
       module_spec=__spec__,
   )