'''simple docstring'''

from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_clip import CLIPTokenizer


lowerCAmelCase_			:			str    	=   logging.get_logger(__name__)

lowerCAmelCase_			:			List[Any]    	=   {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

lowerCAmelCase_			:			List[Any]    	=   {
    "vocab_file": {
        "openai/clip-vit-base-patch32": "https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/vocab.json",
    },
    "merges_file": {
        "openai/clip-vit-base-patch32": "https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "openai/clip-vit-base-patch32": (
            "https://huggingface.co/openai/clip-vit-base-patch32/resolve/main/tokenizer.json"
        ),
    },
}

lowerCAmelCase_			:			Union[str, Any]    	=   {
    "openai/clip-vit-base-patch32": 77,
}





class 				lowercase    (    __lowerCamelCase			):
   lowerCamelCase_            =VOCAB_FILES_NAMES
   lowerCamelCase_            =PRETRAINED_VOCAB_FILES_MAP
   lowerCamelCase_            =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowerCamelCase_            =['input_ids', 'attention_mask']
   lowerCamelCase_            =CLIPTokenizer


   def __init__( self					:						int ,		__lowerCAmelCase					:						Any=None ,		__lowerCAmelCase					:						Optional[Any]=None ,		__lowerCAmelCase					:						Optional[int]=None ,		__lowerCAmelCase					:						Union[str, Any]="<|endoftext|>" ,		__lowerCAmelCase					:						int="<|startoftext|>" ,		__lowerCAmelCase					:						Dict="<|endoftext|>" ,		__lowerCAmelCase					:						List[Any]="<|endoftext|>" ,		**__lowerCAmelCase					:						Any ,		)   ->       List[Any]:
         super().__init__(
             __lowerCAmelCase ,		__lowerCAmelCase ,		tokenizer_file=__lowerCAmelCase ,		unk_token=__lowerCAmelCase ,		bos_token=__lowerCAmelCase ,		eos_token=__lowerCAmelCase ,		pad_token=__lowerCAmelCase ,		**__lowerCAmelCase ,		)

         if not isinstance(self.backend_tokenizer.pre_tokenizer ,		pre_tokenizers.Sequence):
               raise ValueError(
                   "The `backend_tokenizer` provided does not match the expected format. The CLIP tokenizer has been"
                   " heavily modified from transformers version 4.17.0. You need to convert the tokenizer you are using"
                   " to be compatible with this version.The easiest way to do so is"
                   " `CLIPTokenizerFast.from_pretrained(\"path_to_local_folder_or_hub_repo, from_slow=True)`. If you want"
                   " to use your existing tokenizer, you will have to revert to a version prior to 4.17.0 of"
                   " transformers.")

         self._wrap_decode_method_backend_tokenizer()


   def __UpperCAmelCase							( self					:						str)   ->       Union[str, Any]:
         lowercase_     			=   self.backend_tokenizer.decode

         def new_decode_method(*__lowerCAmelCase					:						Any ,		**__lowerCAmelCase					:						Any):
               lowercase_     			=   orig_decode_method(*__lowerCAmelCase ,		**__lowerCAmelCase)
               lowercase_     			=   text.replace(self.backend_tokenizer.model.end_of_word_suffix ,		" ").strip()
               return text

         lowercase_     			=   new_decode_method


   def __UpperCAmelCase							( self					:						int ,		__lowerCAmelCase					:						List[int] ,		__lowerCAmelCase					:						Optional[List[int]] = None)   ->       List[int]:
         lowercase_     			=   [self.bos_token_id]
         lowercase_     			=   [self.eos_token_id]

         if token_ids_a is None:
               return bos_token + token_ids_a + eos_token
         return bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token


   def __UpperCAmelCase							( self					:						Tuple ,		__lowerCAmelCase					:						List[int] ,		__lowerCAmelCase					:						Optional[List[int]] = None)   ->       List[int]:
         lowercase_     			=   [self.bos_token_id]
         lowercase_     			=   [self.eos_token_id]

         if token_ids_a is None:
               return len(bos_token + token_ids_a + eos_token) * [0]
         return len(bos_token + token_ids_a + eos_token + eos_token + token_ids_a + eos_token) * [0]


   def __UpperCAmelCase							( self					:						Optional[Any] ,		__lowerCAmelCase					:						str ,		__lowerCAmelCase					:						Optional[str] = None)   ->       Tuple[str]:
         lowercase_     			=   self._tokenizer.model.save(__lowerCAmelCase ,		name=__lowerCAmelCase)
         return tuple(__lowerCAmelCase)







'''simple docstring'''

import timeit





class 				lowercase    :


   def __init__( self					:						Dict ,		__lowerCAmelCase					:						Any)   ->       Optional[int]:
         if isinstance(__lowerCAmelCase ,		__lowerCAmelCase):  # Initializes a matrix identical to the one provided.
               lowercase_     			=   arg
               lowercase_     			=   len(__lowerCAmelCase)
         else:  # Initializes a square matrix of the given size and set values to zero.
               lowercase_     			=   arg
               lowercase_     			=   [[0 for _ in range(self.n)] for _ in range(self.n)]


   def __mul__( self					:						int ,		__lowerCAmelCase					:						List[str])   ->       Union[str, Any]:
         lowercase_     			=   Matrix(self.n)
         for i in range(self.n):
               for j in range(self.n):
                     for k in range(self.n):
                           matrix.t[i][j] += self.t[i][k] * b.t[k][j]
         return matrix




def __a			(						__lowerCamelCase      :    List[str]			,		__lowerCamelCase      :    Dict					)						->				Optional[Any]:
      '''simple docstring'''


      lowercase_     			=   Matrix([[1, 0], [0, 1]]					)
      while b > 0:
            if b & 1:
                  matrix *= a
            a *= a
            b >>= 1
      return matrix


def __a			(						__lowerCamelCase      :    Tuple			,		__lowerCamelCase      :    Tuple			,		__lowerCamelCase      :    List[Any]					)						->				Dict:
      '''simple docstring'''


      if n == 1:
            return fa
      elif n == 2:
            return fa
      lowercase_     			=   Matrix([[1, 1], [1, 0]]					)
      lowercase_     			=   modular_exponentiation(__lowerCamelCase			,		n - 2					)
      return fa * matrix.t[0][0] + fa * matrix.t[0][1]


def __a			(						__lowerCamelCase      :    List[Any]			,		__lowerCamelCase      :    Union[str, Any]			,		__lowerCamelCase      :    List[str]					)						->				Optional[Any]:
      '''simple docstring'''


      if n == 1:
            return fa
      elif n == 2:
            return fa

      lowercase_     			=   fa
      lowercase_     			=   fa
      n -= 2

      while n > 0:
            lowercase_			,				lowercase_     			=   fn_a + fn_a, fn_a
            n -= 1

      return fn_a


def __a			(						)						->				str:
      '''simple docstring'''


      lowercase_     			=   "\nfrom random import randint\nfrom __main__ import fibonacci_with_matrix_exponentiation\n"
      lowercase_     			=   "fibonacci_with_matrix_exponentiation(randint(1,70000), 1, 1)"
      lowercase_     			=   timeit.timeit(setup=__lowerCamelCase			,		stmt=__lowerCamelCase			,		number=100					)
      print("With matrix exponentiation the average execution time is "			,		exec_time / 100					)
      return exec_time


def __a			(						)						->				Optional[Any]:
      '''simple docstring'''


      lowercase_     			=   "\nfrom random import randint\nfrom __main__ import simple_fibonacci\n"
      lowercase_     			=   "simple_fibonacci(randint(1,70000), 1, 1)"
      lowercase_     			=   timeit.timeit(setup=__lowerCamelCase			,		stmt=__lowerCamelCase			,		number=100					)
      print(
          "Without matrix exponentiation the average execution time is "			,		exec_time / 100					)
      return exec_time


def __a			(						)						->				Tuple:
      '''simple docstring'''


      matrix_exponentiation_time()
      simple_fibonacci_time()


if __name__ == "__main__":
       main()






