

def  lowerCAmelCase(			SCREAMING_SNAKE_CASE_ = 9_9_8_0_0_1 )->	Union[str, Any]:



    """simple docstring"""






    UpperCamelCase_      =	0
    for i in range(9_9_9 ,	9_9 ,	-1 ):  # 3 digit numbers range from 999 down to 100
        for j in range(9_9_9 ,	9_9 ,	-1 ):
            UpperCamelCase_      =	str(i * j )
            if product_string == product_string[::-1] and i * j < n:
                UpperCamelCase_      =	max(lowercase_ ,	i * j )
    return answer


if __name__ == "__main__":
 print(F'''{solution() = }''')








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,
)


SCREAMING_SNAKE_CASE		:Optional[Any]				  =    {"""configuration_t5""": ["""T5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """T5Config""", """T5OnnxConfig"""]}

try:
 if not is_sentencepiece_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE		:Dict				  =    ["""T5Tokenizer"""]

try:
 if not is_tokenizers_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE		:str				  =    ["""T5TokenizerFast"""]

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE		:List[Any]				  =    [
     """T5_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """T5EncoderModel""",
     """T5ForConditionalGeneration""",
     """T5Model""",
     """T5PreTrainedModel""",
     """load_tf_weights_in_t5""",
     """T5ForQuestionAnswering""",
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE		:int				  =    [
     """TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """TFT5EncoderModel""",
     """TFT5ForConditionalGeneration""",
     """TFT5Model""",
     """TFT5PreTrainedModel""",
 ]

try:
 if not is_flax_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE		:List[str]				  =    [
     """FlaxT5EncoderModel""",
     """FlaxT5ForConditionalGeneration""",
     """FlaxT5Model""",
     """FlaxT5PreTrainedModel""",
 ]


if TYPE_CHECKING:
 from .configuration_ta import T5_PRETRAINED_CONFIG_ARCHIVE_MAP, TaConfig, TaOnnxConfig

 try:
  if not is_sentencepiece_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_ta import TaTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_ta_fast import TaTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_ta import (
      T5_PRETRAINED_MODEL_ARCHIVE_LIST,
      TaEncoderModel,
      TaForConditionalGeneration,
      TaForQuestionAnswering,
      TaModel,
      TaPreTrainedModel,
      load_tf_weights_in_ta,
  )

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_ta import (
      TF_T5_PRETRAINED_MODEL_ARCHIVE_LIST,
      TFTaEncoderModel,
      TFTaForConditionalGeneration,
      TFTaModel,
      TFTaPreTrainedModel,
  )

 try:
  if not is_flax_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_flax_ta import (
      FlaxTaEncoderModel,
      FlaxTaForConditionalGeneration,
      FlaxTaModel,
      FlaxTaPreTrainedModel,
  )


else:
 import sys

 SCREAMING_SNAKE_CASE		:List[Any]				  =    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
