






def 				lowerCamelCase__      (    __lowerCamelCase			:     int | float | str		):
  try:
    __UpperCAmelCase							:	int           =  float(__lowerCamelCase		)
  except ValueError:
    raise ValueError("""Please enter a valid number"""		)
  __UpperCAmelCase							:	Union[str, Any]           =  decimal - int(__lowerCamelCase		)
  if fractional_part == 0:
    return int(__lowerCamelCase		), 1
  else:
    __UpperCAmelCase							:	Optional[int]           =  len(str(__lowerCamelCase		).split("""."""		)[1]		)
    __UpperCAmelCase							:	Dict           =  int(decimal * (10**number_of_frac_digits)		)
    __UpperCAmelCase							:	str           =  10**number_of_frac_digits
    __UpperCAmelCase      , __UpperCAmelCase							:	Dict           =  denominator, numerator
    while True:
      __UpperCAmelCase							:	List[Any]           =  dividend % divisor
      if remainder == 0:
        break
      __UpperCAmelCase      , __UpperCAmelCase							:	List[str]           =  divisor, remainder
    __UpperCAmelCase      , __UpperCAmelCase							:	Dict           =  numerator / divisor, denominator / divisor
    return int(__lowerCamelCase		), int(__lowerCamelCase		)


if __name__ == "__main__":
       print(f"""{decimal_to_fraction(2) = }""")
       print(f"""{decimal_to_fraction(89.0) = }""")
       print(f"""{decimal_to_fraction("67") = }""")
       print(f"""{decimal_to_fraction("45.0") = }""")
       print(f"""{decimal_to_fraction(1.5) = }""")
       print(f"""{decimal_to_fraction("6.25") = }""")
       print(f"""{decimal_to_fraction("78td") = }""")










from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging


a		:       Tuple			     = logging.get_logger(__name__)

a		:       Dict			     = {
    "t5-small": "https://huggingface.co/t5-small/resolve/main/config.json",
    "t5-base": "https://huggingface.co/t5-base/resolve/main/config.json",
    "t5-large": "https://huggingface.co/t5-large/resolve/main/config.json",
    "t5-3b": "https://huggingface.co/t5-3b/resolve/main/config.json",
    "t5-11b": "https://huggingface.co/t5-11b/resolve/main/config.json",
}
class     a    ( lowercase__   ):



      """simple docstring"""


      a  : int							       =	't5'
      a  : Dict							       =	['past_key_values']
      a  : Tuple							       =	{'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}
      def __init__(      self					:			str		,      __lowercase					:			Optional[int]=32128		,      __lowercase					:			Optional[int]=512		,      __lowercase					:			int=64		,      __lowercase					:			Any=2048		,      __lowercase					:			Tuple=6		,      __lowercase					:			Tuple=None		,      __lowercase					:			int=8		,      __lowercase					:			List[Any]=32		,      __lowercase					:			Dict=128		,      __lowercase					:			Optional[int]=0.1		,      __lowercase					:			int=1e-6		,      __lowercase					:			List[str]=1.0		,      __lowercase					:			List[str]="relu"		,      __lowercase					:			Dict=True		,      __lowercase					:			Optional[Any]=True		,      __lowercase					:			Tuple=0		,      __lowercase					:			List[str]=1		,      **__lowercase					:			Any		,      )							->      str:
        __UpperCAmelCase							:	Tuple           =  vocab_size
        __UpperCAmelCase							:	Optional[int]           =  d_model
        __UpperCAmelCase							:	Union[str, Any]           =  d_kv
        __UpperCAmelCase							:	Union[str, Any]           =  d_ff
        __UpperCAmelCase							:	int           =  num_layers
        __UpperCAmelCase							:	Any           =  (
            num_decoder_layers if num_decoder_layers is not None else self.num_layers
        )  # default = symmetry
        __UpperCAmelCase							:	Dict           =  num_heads
        __UpperCAmelCase							:	List[Any]           =  relative_attention_num_buckets
        __UpperCAmelCase							:	List[str]           =  relative_attention_max_distance
        __UpperCAmelCase							:	Union[str, Any]           =  dropout_rate
        __UpperCAmelCase							:	List[str]           =  layer_norm_epsilon
        __UpperCAmelCase							:	str           =  initializer_factor
        __UpperCAmelCase							:	Dict           =  feed_forward_proj
        __UpperCAmelCase							:	Optional[int]           =  use_cache

        __UpperCAmelCase							:	List[Any]           =  self.feed_forward_proj.split("""-"""					)
        __UpperCAmelCase							:	Tuple           =  act_info[-1]
        __UpperCAmelCase							:	int           =  act_info[0] == """gated"""

        if len(__lowercase					) > 1 and act_info[0] != "gated" or len(__lowercase					) > 2:
          raise ValueError(
              f"""`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."""
              """Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. """
              """'gated-gelu' or 'relu'"""					)

        # for backwards compatibility
        if feed_forward_proj == "gated-gelu":
          __UpperCAmelCase							:	Dict           =  """gelu_new"""

        super().__init__(
            pad_token_id=__lowercase		,      eos_token_id=__lowercase		,      is_encoder_decoder=__lowercase		,      **__lowercase		,      )


class     a    ( lowercase__   ):



      """simple docstring"""


      @property
      def 	UpperCAmelCase      (      self					:			str					)							->      Mapping[str, Mapping[int, str]]:
        __UpperCAmelCase							:	Union[str, Any]           =  {
            """input_ids""": {0: """batch""", 1: """encoder_sequence"""},
            """attention_mask""": {0: """batch""", 1: """encoder_sequence"""},
        }
        if self.use_past:
          __UpperCAmelCase							:	List[Any]           =  """past_encoder_sequence + sequence"""
          __UpperCAmelCase							:	Optional[int]           =  {0: """batch"""}
          __UpperCAmelCase							:	Union[str, Any]           =  {0: """batch""", 1: """past_decoder_sequence + sequence"""}
        else:
          __UpperCAmelCase							:	str           =  {0: """batch""", 1: """decoder_sequence"""}
          __UpperCAmelCase							:	str           =  {0: """batch""", 1: """decoder_sequence"""}

        if self.use_past:
          self.fill_with_past_key_values_(__lowercase		,      direction="""inputs"""					)

        return common_inputs




      @property
      def 	UpperCAmelCase      (      self					:			int					)							->      int:
        return 13


