from ctypes import c_float, sizeof
from enum import Enum
from typing import TYPE_CHECKING, Optional, Union


if TYPE_CHECKING:
    from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore
class 							a_					(		UpperCAmelCase__		):






 '''simple docstring'''






 UpperCAmelCase_      					=   c_float




 @property
 def 						__snake_case		(     self   :    int):







        '''simple docstring'''



        return sizeof(self.value)






def  __lowerCamelCase						(		lowerCAmelCase__      ,    lowerCAmelCase__      ,    lowerCAmelCase__ = 0      ):




       if dimension <= 0:
              lowerCAmelCase__	      =   fixed_dimension

       dimension -= num_token_to_add
       return dimension






def  __lowerCamelCase						(		lowerCAmelCase__      ,    lowerCAmelCase__      ):
       return num_parameters * dtype.size






def  __lowerCamelCase						(		lowerCAmelCase__      ):
       from .. import AutoFeatureExtractor, AutoProcessor, AutoTokenizer  # tests_ignore

       try:
              return AutoProcessor.from_pretrained(UpperCAmelCase_      )
       except (ValueError, OSError, KeyError):
              lowerCAmelCase__      ,   lowerCAmelCase__	      =   None, None
              try:
                     lowerCAmelCase__	      =   AutoTokenizer.from_pretrained(UpperCAmelCase_      )
              except (OSError, KeyError):
                     pass
              try:
                     lowerCAmelCase__	      =   AutoFeatureExtractor.from_pretrained(UpperCAmelCase_      )
              except (OSError, KeyError):
                     pass

              if tokenizer is not None and feature_extractor is not None:
                     raise ValueError(
                         F"""Couldn\'t auto-detect preprocessor for {model_name}. Found both a tokenizer and a feature extractor."""      )
              elif tokenizer is None and feature_extractor is None:
                     return None
              elif tokenizer is not None:
                     return tokenizer
              else:
                     return feature_extractor






from __future__ import annotations

from typing import Any


class        UpperCAmelCase__				:



     '''simple docstring'''
     def __init__(				self ,    _lowerCAmelCase ,    _lowerCAmelCase	):  # noqa: A002
            a			   =item
            a			   =next



class        UpperCAmelCase__				:



     '''simple docstring'''
     def __init__(				self	):
            a			   =None
            a			   =0
     def        lowerCAmelCase__  (				self ,    _lowerCAmelCase	):
            a			   =Node(_lowerCAmelCase ,    self.head	)
            self.size += 1
     def        lowerCAmelCase__  (				self	):
            # Switched 'self.is_empty()' to 'self.head is None'
            # because mypy was considering the possibility that 'self.head'
            # can be None in below else part and giving error
            if self.head is None:
                   return None
            else:
                   a			   =self.head.item
                   a			   =self.head.next
                   self.size -= 1
                   return item
     def        lowerCAmelCase__  (				self	):
            return self.head is None
     def __str__(				self	):
            if self.is_empty():
                   return ""
            else:
                   a			   =self.head
                   a			   =""""""
                   a			   =[]
                   while iterate:
                          item_list.append(str(iterate.item	)	)
                          a			   =iterate.next

                   a			   =""" --> """.join(_lowerCAmelCase	)

                   return item_str






     def __len__(				self	):
            return self.size
