






"""simple docstring"""


import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin






class 						snake_case  (  _lowerCamelCase       ,			unittest.TestCase	):
    __magic_name__   					=					BlenderbotSmallTokenizer
    __magic_name__   					=					False





    def     lowerCamelCase__				(							self     : int      ):


      '''simple docstring'''




      super().setUp()

      a					:      Any    =       ['__start__', 'adapt', 'act', 'ap@@', 'te', '__end__', '__unk__']
      a					:      int    =       dict(zip(lowercase_    ,		range(len(lowercase_      )      )      )      )

      a					:      List[Any]    =       ['#version: 0.2', 'a p', 't e</w>', 'ap t</w>', 'a d', 'ad apt</w>', 'a c', 'ac t</w>', '']
      a					:      Union[str, Any]    =       {'unk_token': '__unk__', 'bos_token': '__start__', 'eos_token': '__end__'}

      a					:      Optional[Any]    =       os.path.join(self.tmpdirname    ,		VOCAB_FILES_NAMES['vocab_file']      )
      a					:      Optional[Any]    =       os.path.join(self.tmpdirname    ,		VOCAB_FILES_NAMES['merges_file']      )
      with open(self.vocab_file    ,		'w'    ,		encoding='utf-8'      ) as fp:
        fp.write(json.dumps(lowercase_      ) + '\n'      )
      with open(self.merges_file    ,		'w'    ,		encoding='utf-8'      ) as fp:
        fp.write('\n'.join(lowercase_      )      )





    def     lowerCamelCase__				(							self     : Dict    ,		**A     : List[str]      ):


      '''simple docstring'''




      kwargs.update(self.special_tokens_map      )
      return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname    ,		**lowercase_      )





    def     lowerCamelCase__				(							self     : str    ,		A     : List[Any]      ):


      '''simple docstring'''




      a					:      Tuple    =       'adapt act apte'
      a					:      int    =       'adapt act apte'
      return input_text, output_text





    def     lowerCamelCase__				(							self     : Tuple      ):


      '''simple docstring'''




      a					:      List[Any]    =       BlenderbotSmallTokenizer(self.vocab_file    ,		self.merges_file    ,		**self.special_tokens_map      )
      a					:      Dict    =       'adapt act apte'
      a					:      Any    =       ['adapt', 'act', 'ap@@', 'te']
      a					:      Union[str, Any]    =       tokenizer.tokenize(lowercase_      )
      self.assertListEqual(lowercase_    ,		lowercase_      )

      a					:      Optional[int]    =       [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

      a					:      List[str]    =       [0, 1, 2, 3, 4, 5]
      self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase_      )    ,		lowercase_      )





    def     lowerCamelCase__				(							self     : Any      ):


      '''simple docstring'''




      a					:      List[str]    =       BlenderbotSmallTokenizer.from_pretrained('facebook/blenderbot-90M'      )
      assert tok('sam'      ).input_ids == [1_3_8_4]
      a					:      Tuple    =       'I am a small frog.'
      a					:      Any    =       tok([src_text]    ,		padding=lowercase_    ,		truncation=lowercase_      )['input_ids']
      a					:      List[str]    =       tok.batch_decode(lowercase_    ,		skip_special_tokens=lowercase_    ,		clean_up_tokenization_spaces=lowercase_      )[0]
      assert src_text != decoded  # I wish it did!
      assert decoded == "i am a small frog ."





    def     lowerCamelCase__				(							self     : int      ):


      '''simple docstring'''




      a					:      List[str]    =       BlenderbotSmallTokenizer.from_pretrained('facebook/blenderbot-90M'      )
      a					:      Union[str, Any]    =       'I am a small frog .'
      a					:      Dict    =       '.'
      a					:      Optional[Any]    =       tok(lowercase_      )['input_ids']
      a					:      Tuple    =       tok(lowercase_      )['input_ids']

      assert encoded[-1] == encoded_dot[0]












"""simple docstring"""


from __future__ import annotations

import math

import numpy as np
from numpy.linalg import norm




def       snake_case  (A_				:np.ndarray     ,      A_				:np.ndarray				):







  '''simple docstring'''

  return math.sqrt(sum(pow(a - b     ,      2				) for a, b in zip(A_     ,      A_				)				)				)




def       snake_case  (A_				:np.ndarray     ,      A_				:np.ndarray				):







  '''simple docstring'''

  if dataset.ndim != value_array.ndim:
    a					:      Optional[Any]    =       (
        'Wrong input data\'s dimensions... '
        f'''dataset : {dataset.ndim}, value_array : {value_array.ndim}'''
    )
    raise ValueError(A_				)

  try:
    if dataset.shape[1] != value_array.shape[1]:
      a					:      Optional[int]    =       (
          'Wrong input data\'s shape... '
          f'''dataset : {dataset.shape[1]}, value_array : {value_array.shape[1]}'''
      )
      raise ValueError(A_				)
  except IndexError:
    if dataset.ndim != value_array.ndim:
      raise TypeError('Wrong shape'				)

  if dataset.dtype != value_array.dtype:
    a					:      Optional[Any]    =       (
        'Input data have different datatype... '
        f'''dataset : {dataset.dtype}, value_array : {value_array.dtype}'''
    )
    raise TypeError(A_				)

  a					:      Tuple    =       []

  for value in value_array:
    a					:      List[Any]    =       euclidean(A_     ,      dataset[0]				)
    a					:      int    =       dataset[0].tolist()

    for dataset_value in dataset[1:]:
      a					:      Optional[int]    =       euclidean(A_     ,      A_				)

      if dist > temp_dist:
        a					:      List[str]    =       temp_dist
        a					:      int    =       dataset_value.tolist()

    answer.append([vector, dist]				)

  return answer




def       snake_case  (A_				:np.ndarray     ,      A_				:np.ndarray				):







  '''simple docstring'''

  return np.dot(A_     ,      A_				) / (norm(A_				) * norm(A_				))


if __name__ == "__main__":
   import doctest

   doctest.testmod()




