
"""simple docstring"""





import math



def 						_lowerCAmelCase				(				UpperCamelCase_  ,				UpperCamelCase_				):
		if 0 not in (x, y):
				# We use the relation x^y = y*log10(x), where 10 is the base.
				return y * math.logaa(UpperCamelCase_				)
		else:
				if x == 0:  # 0 raised to any number is 0
						return 0
				elif y == 0:
						return 1  # any number raised to 0 is 1
		raise AssertionError("""This should never happen"""				)


if __name__ == "__main__":  # Main function
							# Read two numbers from input and typecast them to int using map function.
							# Here x is the base and y is the power.
							__magic_name__       =			"Enter the base and the power separated by a comma: "
							__magic_name__,							__magic_name__       =			map(int, input(prompt).split(","))
							__magic_name__,							__magic_name__       =			map(int, input(prompt).split(","))

							# We find the log of each number, using the function res(), which takes two
							# arguments.
							__magic_name__       =			res(xa, ya)
							__magic_name__       =			res(xa, ya)

							# We check for the largest number
							if resa > resa:
														print("Largest number is", xa, "^", ya)
							elif resa > resa:
														print("Largest number is", xa, "^", ya)
							else:
														print("Both are equal")











import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer


UpperCAmelCase	:	int		     =       logging.get_logger(__name__)

UpperCAmelCase	:	Optional[Any]		     =       {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

UpperCAmelCase	:	List[Any]		     =       [
    """small""",
    """small-base""",
    """medium""",
    """medium-base""",
    """intermediate""",
    """intermediate-base""",
    """large""",
    """large-base""",
    """xlarge""",
    """xlarge-base""",
]

UpperCAmelCase	:	Optional[int]		     =       {
    """vocab_file""": {
        """funnel-transformer/small""": """https://huggingface.co/funnel-transformer/small/resolve/main/vocab.txt""",
        """funnel-transformer/small-base""": """https://huggingface.co/funnel-transformer/small-base/resolve/main/vocab.txt""",
        """funnel-transformer/medium""": """https://huggingface.co/funnel-transformer/medium/resolve/main/vocab.txt""",
        """funnel-transformer/medium-base""": (
            """https://huggingface.co/funnel-transformer/medium-base/resolve/main/vocab.txt"""
        ),
        """funnel-transformer/intermediate""": (
            """https://huggingface.co/funnel-transformer/intermediate/resolve/main/vocab.txt"""
        ),
        """funnel-transformer/intermediate-base""": (
            """https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/vocab.txt"""
        ),
        """funnel-transformer/large""": """https://huggingface.co/funnel-transformer/large/resolve/main/vocab.txt""",
        """funnel-transformer/large-base""": """https://huggingface.co/funnel-transformer/large-base/resolve/main/vocab.txt""",
        """funnel-transformer/xlarge""": """https://huggingface.co/funnel-transformer/xlarge/resolve/main/vocab.txt""",
        """funnel-transformer/xlarge-base""": (
            """https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/vocab.txt"""
        ),
    },
    """tokenizer_file""": {
        """funnel-transformer/small""": """https://huggingface.co/funnel-transformer/small/resolve/main/tokenizer.json""",
        """funnel-transformer/small-base""": (
            """https://huggingface.co/funnel-transformer/small-base/resolve/main/tokenizer.json"""
        ),
        """funnel-transformer/medium""": """https://huggingface.co/funnel-transformer/medium/resolve/main/tokenizer.json""",
        """funnel-transformer/medium-base""": (
            """https://huggingface.co/funnel-transformer/medium-base/resolve/main/tokenizer.json"""
        ),
        """funnel-transformer/intermediate""": (
            """https://huggingface.co/funnel-transformer/intermediate/resolve/main/tokenizer.json"""
        ),
        """funnel-transformer/intermediate-base""": (
            """https://huggingface.co/funnel-transformer/intermediate-base/resolve/main/tokenizer.json"""
        ),
        """funnel-transformer/large""": """https://huggingface.co/funnel-transformer/large/resolve/main/tokenizer.json""",
        """funnel-transformer/large-base""": (
            """https://huggingface.co/funnel-transformer/large-base/resolve/main/tokenizer.json"""
        ),
        """funnel-transformer/xlarge""": """https://huggingface.co/funnel-transformer/xlarge/resolve/main/tokenizer.json""",
        """funnel-transformer/xlarge-base""": (
            """https://huggingface.co/funnel-transformer/xlarge-base/resolve/main/tokenizer.json"""
        ),
    },
}
UpperCAmelCase	:	Optional[int]		     =       {F"""funnel-transformer/{name}""": 512 for name in _model_names}
UpperCAmelCase	:	Optional[int]		     =       {F"""funnel-transformer/{name}""": {"""do_lower_case""": True} for name in _model_names}







class 				__lowerCAmelCase       (    UpperCamelCase__):
      _lowercase				:					str						=			VOCAB_FILES_NAMES
      _lowercase				:					List[Any]						=			PRETRAINED_VOCAB_FILES_MAP
      _lowercase				:					Dict						=			PRETRAINED_INIT_CONFIGURATION
      _lowercase				:					Union[str, Any]						=			FunnelTokenizer
      _lowercase				:					Any						=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      _lowercase				:					int						=			2







      def __init__(    self		,      lowerCAmelCase__=None		,      lowerCAmelCase__=None		,      lowerCAmelCase__=True		,      lowerCAmelCase__="<unk>"		,      lowerCAmelCase__="<sep>"		,      lowerCAmelCase__="<pad>"		,      lowerCAmelCase__="<cls>"		,      lowerCAmelCase__="<mask>"		,      lowerCAmelCase__="<s>"		,      lowerCAmelCase__="</s>"		,      lowerCAmelCase__=True		,      lowerCAmelCase__=True		,      lowerCAmelCase__=None		,      lowerCAmelCase__="##"		,      **lowerCAmelCase__		,      )   ->						Optional[int]:



        '''simple docstring'''




        super().__init__(
            lowerCAmelCase__		,      tokenizer_file=lowerCAmelCase__		,      do_lower_case=lowerCAmelCase__		,      unk_token=lowerCAmelCase__		,      sep_token=lowerCAmelCase__		,      pad_token=lowerCAmelCase__		,      cls_token=lowerCAmelCase__		,      mask_token=lowerCAmelCase__		,      bos_token=lowerCAmelCase__		,      eos_token=lowerCAmelCase__		,      clean_text=lowerCAmelCase__		,      tokenize_chinese_chars=lowerCAmelCase__		,      strip_accents=lowerCAmelCase__		,      wordpieces_prefix=lowerCAmelCase__		,      **lowerCAmelCase__		,      )

        a__	:					Optional[Any]										=json.loads(self.backend_tokenizer.normalizer.__getstate__()							)
        if (
            normalizer_state.get("lowercase"		,      lowerCAmelCase__							) != do_lower_case
            or normalizer_state.get("strip_accents"		,      lowerCAmelCase__							) != strip_accents
            or normalizer_state.get("handle_chinese_chars"		,      lowerCAmelCase__							) != tokenize_chinese_chars
        ):
          a__	:					List[str]										=getattr(lowerCAmelCase__		,      normalizer_state.pop("type"							)							)
          a__	:					Union[str, Any]										=do_lower_case
          a__	:					Any										=strip_accents
          a__	:					Optional[Any]										=tokenize_chinese_chars
          a__	:					Dict										=normalizer_class(**lowerCAmelCase__							)

        a__	:					Any										=do_lower_case







      def    _lowercase  (    self		,      lowerCAmelCase__		,      lowerCAmelCase__=None							)   ->						str:



        '''simple docstring'''




        a__	:					Dict										=[self.cls_token_id] + token_ids_a + [self.sep_token_id]

        if token_ids_a:
          output += token_ids_a + [self.sep_token_id]

        return output







      def    _lowercase  (    self		,      lowerCAmelCase__		,      lowerCAmelCase__ = None							)   ->						List[int]:



        '''simple docstring'''




        a__	:					Optional[int]										=[self.sep_token_id]
        a__	:					Union[str, Any]										=[self.cls_token_id]
        if token_ids_a is None:
          return len(cls							) * [self.cls_token_type_id] + len(token_ids_a + sep							) * [0]
        return len(cls							) * [self.cls_token_type_id] + len(token_ids_a + sep							) * [0] + len(token_ids_a + sep							) * [1]







      def    _lowercase  (    self		,      lowerCAmelCase__		,      lowerCAmelCase__ = None							)   ->						Tuple[str]:



        '''simple docstring'''




        a__	:					Tuple										=self._tokenizer.model.save(lowerCAmelCase__		,      name=lowerCAmelCase__							)
        return tuple(lowerCAmelCase__							)






