





'''simple docstring'''



import json
import os
from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__magic_name__   :						Any    =			logging.get_logger(__name__)


__magic_name__   :						List[str]    =			{
    """vocab_file""": """vocab.json""",
    """tokenizer_config_file""": """tokenizer_config.json""",
    """merges_file""": """merges.txt""",
}

__magic_name__   :						Dict    =			{
    """vocab_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/vocab.json"""
        ),
    },
    """tokenizer_config_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/tokenizer_config.json"""
        ),
    },
    """merges_file""": {
        """facebook/s2t-wav2vec2-large-en-de""": (
            """https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/merges.txt"""
        ),
    },
}

__magic_name__   :						Optional[int]    =			"""</w>"""
__magic_name__   :						Optional[int]    =			"""@@ """




def 				snake_case_      (		SCREAMING_SNAKE_CASE__       ):







  '''simple docstring'''



  _snake_case     		=				set()
  _snake_case     		=				word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)       )
    _snake_case     		=				char
  return pairs


# Speech2Text2 has no max input length
__magic_name__   :						Tuple    =			{"""facebook/s2t-wav2vec2-large-en-de""": 1_024}




class       __SCREAMING_SNAKE_CASE	(						__UpperCamelCase			):



     '''simple docstring'''






     UpperCAmelCase__       :						Dict      =   VOCAB_FILES_NAMES
     UpperCAmelCase__       :						Union[str, Any]      =   PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase__       :						str      =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase__       :						str      =   ['''input_ids''', '''attention_mask''']

     def __init__(					self						,   lowerCamelCase						,   lowerCamelCase="<s>"						,   lowerCamelCase="<pad>"						,   lowerCamelCase="</s>"						,   lowerCamelCase="<unk>"						,   lowerCamelCase=False						,   lowerCamelCase=None						,   **lowerCamelCase						,   ):
       super().__init__(
           unk_token=lowerCamelCase						,   bos_token=lowerCamelCase						,   eos_token=lowerCamelCase						,   pad_token=lowerCamelCase						,   do_lower_case=lowerCamelCase						,   **lowerCamelCase						,   )

       _snake_case     		=				do_lower_case

       with open(lowerCamelCase						,   encoding="utf-8"	) as vocab_handle:
         _snake_case     		=				json.load(lowerCamelCase	)
       _snake_case     		=				{v: k for k, v in self.encoder.items()}

       if merges_file is None:
         logger.info(F'''No merges files provided. {self.__class__.__name__} can only be used for decoding.'''	)

         _snake_case     		=				None
         _snake_case     		=				None
       else:
         with open(lowerCamelCase						,   encoding="utf-8"	) as merges_handle:
           _snake_case     		=				merges_handle.read().split("\n"	)[:-1]

         _snake_case     		=				[tuple(merge.split()[:2]	) for merge in merges]
         _snake_case     		=				dict(zip(lowerCamelCase						,   range(len(lowerCamelCase	)	)	)	)
         _snake_case     		=				{}

     @property
     def 	UpperCamelCase(					self	):
       return len(self.decoder	)

     def 	UpperCamelCase(					self	):
       return dict(self.encoder						,   **self.added_tokens_encoder	)

     def 	UpperCamelCase(					self						,   lowerCamelCase	):
       _snake_case     		=				tuple(token[:-1]	) + (token[-1] + BPE_TOKEN_MERGES,)
       if token in self.cache:
         return self.cache[token]
       _snake_case     		=				get_pairs(lowerCamelCase	)

       if not pairs:
         return token

       while True:
         _snake_case     		=				min(lowerCamelCase						,   key=lambda lowerCamelCase	: self.bpe_ranks.get(lowerCamelCase						,   float("inf"	)	)	)
         if bigram not in self.bpe_ranks:
           break
         _snake_case		,		_snake_case     		=				bigram
         _snake_case     		=				[]
         _snake_case     		=				0
         while i < len(lowerCamelCase	):
           try:
             _snake_case     		=				word.index(lowerCamelCase						,   lowerCamelCase	)
           except ValueError:
             new_word.extend(word[i:]	)
             break
           else:
             new_word.extend(word[i:j]	)
             _snake_case     		=				j

           if word[i] == first and i < len(lowerCamelCase	) - 1 and word[i + 1] == second:
             new_word.append(first + second	)
             i += 2
           else:
             new_word.append(word[i]	)
             i += 1
         _snake_case     		=				tuple(lowerCamelCase	)
         _snake_case     		=				new_word
         if len(lowerCamelCase	) == 1:
           break
         else:
           _snake_case     		=				get_pairs(lowerCamelCase	)
       _snake_case     		=				" ".join(lowerCamelCase	)
       if word == "\n  " + BPE_TOKEN_MERGES:
         _snake_case     		=				"\n" + BPE_TOKEN_MERGES

       if word.endswith(lowerCamelCase	):
         _snake_case     		=				word.replace(lowerCamelCase						,   ""	)

       _snake_case     		=				word.replace(" "						,   lowerCamelCase	)
       _snake_case     		=				word
       return word

     def 	UpperCamelCase(					self						,   lowerCamelCase	):

       if self.bpe_ranks is None:
         raise ValueError(
             "This tokenizer was instantiated without a `merges.txt` file, so"
             " that it can only be used for decoding, not for encoding."
             "Make sure to provide `merges.txt` file at instantiation to enable "
             "encoding."	)

       if self.do_lower_case:
         _snake_case     		=				text.lower()

       _snake_case     		=				text.split()

       _snake_case     		=				[]
       for token in text:
         if token:
           split_tokens.extend(list(self.bpe(lowerCamelCase	).split(" "	)	)	)

       return split_tokens

     def 	UpperCamelCase(					self						,   lowerCamelCase	):
       return self.encoder.get(lowerCamelCase						,   self.encoder.get(self.unk_token	)	)

     def 	UpperCamelCase(					self						,   lowerCamelCase	):
       _snake_case     		=				self.decoder.get(lowerCamelCase						,   self.unk_token	)
       return result

     def 	UpperCamelCase(					self						,   lowerCamelCase	):
       _snake_case     		=				" ".join(lowerCamelCase	)

       # make sure @@ tokens are concatenated
       _snake_case     		=				"".join(string.split(lowerCamelCase	)	)

       return string






     def 	UpperCamelCase(					self						,   lowerCamelCase						,   lowerCamelCase = None	):
       if not os.path.isdir(lowerCamelCase	):
         logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''	)
         return
       _snake_case     		=				os.path.join(
           lowerCamelCase						,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]	)
       _snake_case     		=				os.path.join(
           lowerCamelCase						,   (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]	)

       with open(lowerCamelCase						,   "w"						,   encoding="utf-8"	) as f:
         f.write(json.dumps(self.encoder						,   indent=2						,   sort_keys=lowerCamelCase						,   ensure_ascii=lowerCamelCase	) + "\n"	)

       _snake_case     		=				0
       if self.bpe_ranks is None:
         return (vocab_file,)

       with open(lowerCamelCase						,   "w"						,   encoding="utf-8"	) as writer:
         for bpe_tokens, token_index in sorted(self.bpe_ranks.items()						,   key=lambda lowerCamelCase	: kv[1]	):
           if index != token_index:
             logger.warning(
                 F'''Saving vocabulary to {merges_file}: BPE merge indices are not consecutive.'''
                 " Please check that the tokenizer is not corrupted!"	)
             _snake_case     		=				token_index
           writer.write(" ".join(lowerCamelCase	) + "\n"	)
           index += 1

       return (vocab_file, merges_file)









'''simple docstring'''



import math


class       __SCREAMING_SNAKE_CASE	:



     '''simple docstring'''






     def 	UpperCamelCase(					self						,   lowerCamelCase						,   lowerCamelCase	):
       _snake_case     		=				0.0
       _snake_case     		=				0.0
       for i in range(len(lowerCamelCase	)	):
         da += math.pow((sample[i] - weights[0][i])						,   2	)
         da += math.pow((sample[i] - weights[1][i])						,   2	)
         return 0 if da > da else 1
       return 0






     def 	UpperCamelCase(					self						,   lowerCamelCase						,   lowerCamelCase						,   lowerCamelCase						,   lowerCamelCase	):
       for i in range(len(lowerCamelCase	)	):
         weights[j][i] += alpha * (sample[i] - weights[j][i])
       return weights







def 				snake_case_      (		):







  '''simple docstring'''



  _snake_case     		=				[[1, 1, 0, 0], [0, 0, 0, 1], [1, 0, 0, 0], [0, 0, 1, 1]]

  # weight initialization ( n, C )
  _snake_case     		=				[[0.2, 0.6, 0.5, 0.9], [0.8, 0.4, 0.7, 0.3]]

  # training
  _snake_case     		=				SelfOrganizingMap()
  _snake_case     		=				3
  _snake_case     		=				0.5

  for _ in range(SCREAMING_SNAKE_CASE__       ):
    for j in range(len(SCREAMING_SNAKE_CASE__       )       ):
      # training sample
      _snake_case     		=				training_samples[j]

      # Compute the winning vector
      _snake_case     		=				self_organizing_map.get_winner(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__       )

      # Update the winning vector
      _snake_case     		=				self_organizing_map.update(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__       )

    # classify test sample
  _snake_case     		=				[0, 0, 0, 1]
  _snake_case     		=				self_organizing_map.get_winner(SCREAMING_SNAKE_CASE__					,	SCREAMING_SNAKE_CASE__       )

  # results
  print(f'''Clusters that the test sample belongs to : {winner}'''       )
  print(f'''Weights that have been trained : {weights}'''       )


# running the main() function
if __name__ == "__main__":
 main()


