code: 
  
  
  import os
  import unittest
  
  from transformers.models.bertweet.tokenization_bertweet import VOCAB_FILES_NAMES, BertweetTokenizer
  
  from ...test_tokenization_common import TokenizerTesterMixin
  
  
  
  class   __lowerCamelCase (_a							,			unittest.TestCase	):
         _lowercase       							=    BertweetTokenizer
         _lowercase       							=    False
  
  
  
  
  
  
  
         def 		snake_case_  ( self:   Dict				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              super().setUp()
  
              # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
              __UpperCamelCase   = ['I', 'm', 'V@@', 'R@@', 'r', 'e@@']
              __UpperCamelCase   = dict(zip(A_,range(len(A_				)				)				)				)
              __UpperCamelCase   = ['#version: 0.2', 'a m</w>']
              __UpperCamelCase   = {'unk_token': '<unk>'}
  
              __UpperCamelCase   = os.path.join(self.tmpdirname,VOCAB_FILES_NAMES['vocab_file']				)
              __UpperCamelCase   = os.path.join(self.tmpdirname,VOCAB_FILES_NAMES['merges_file']				)
              with open(self.vocab_file,'w',encoding='utf-8'				) as fp:
                   for token in vocab_tokens:
                        fp.write(F'''{token} {vocab_tokens[token]}\n'''				)
              with open(self.merges_file,'w',encoding='utf-8'				) as fp:
                   fp.write('\n'.join(A_				)				)
  
  
  
  
  
  
  
         def 		snake_case_  ( self:   Optional[Any],**A_:   List[Any]				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              kwargs.update(self.special_tokens_map				)
              return BertweetTokenizer.from_pretrained(self.tmpdirname,**A_				)
  
  
  
  
  
  
  
         def 		snake_case_  ( self:   int,A_:   Optional[Any]				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              __UpperCamelCase   = 'I am VinAI Research'
              __UpperCamelCase   = 'I <unk> m V<unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>'
              return input_text, output_text
  
  
  
  
  
  
  
         def 		snake_case_  ( self:   Optional[int]				):
  
  
  
  
  
  
              '''simple docstring'''
  
  
  
  
              __UpperCamelCase   = BertweetTokenizer(self.vocab_file,self.merges_file,**self.special_tokens_map				)
              __UpperCamelCase   = 'I am VinAI Research'
              __UpperCamelCase   = 'I a@@ m V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h'.split()
              __UpperCamelCase   = tokenizer.tokenize(A_				)
              self.assertListEqual(A_,A_				)
  
              __UpperCamelCase   = tokens + [tokenizer.unk_token]
  
              __UpperCamelCase   = [4, 3, 5, 6, 3, 3, 3, 4, 7, 9, 3, 9, 3, 3, 3, 3, 3]
              self.assertListEqual(tokenizer.convert_tokens_to_ids(A_				),A_				)
  
style_context: 
  
  
  import warnings
  from collections.abc import Callable
  from typing import Any
  
  import numpy
  from matplotlib import pyplot
  
  __snake_case             =	0.25 + 0.0j
  __snake_case             =	-0.4 + 0.6j
  __snake_case             =	-0.1 + 0.6_51j
  __snake_case             =	-2.0
  __snake_case             =	5_6
  __snake_case             =	2.0
  __snake_case             =	6_6_6
  
  
  
  
  
  
  def 		_A		(		_lowercase				,     _lowercase   )				->   numpy.ndarray:
  
  
       """simple docstring"""
  
  
       return numpy.exp(_lowercase   ) + c_parameter
  
  
  
  
  
  
  def 		_A		(		_lowercase				,     _lowercase   )				->   numpy.ndarray:
  
  
       """simple docstring"""
  
  
       return z_values * z_values + c_parameter
  
  
  
  
  
  
  def 		_A		(		_lowercase				,     _lowercase   )				->   numpy.ndarray:
  
  
       """simple docstring"""
  
  
       __UpperCamelCase   = numpy.linspace(-window_size				,     _lowercase				,     _lowercase   )
       __UpperCamelCase   = x.reshape((nb_pixels, 1)   )
       __UpperCamelCase   = numpy.linspace(-window_size				,     _lowercase				,     _lowercase   )
       __UpperCamelCase   = y.reshape((1, nb_pixels)   )
       return x + 1.0J * y
  
  
  
  
  
  
  def 		_A		(		_lowercase				,     _lowercase				,     _lowercase				,     _lowercase				,     _lowercase = None				,     )				->   numpy.ndarray:
  
  
       """simple docstring"""
  
  
       __UpperCamelCase   = z_a.astype('complex64'   )
       for _ in range(_lowercase   ):
            __UpperCamelCase   = eval_function(_lowercase				,     _lowercase   )
            if infinity is not None:
                 numpy.nan_to_num(_lowercase				,     copy=_lowercase				,     nan=_lowercase   )
                 __UpperCamelCase   = infinity
       return z_n
  
  
  
  
  
  
  def 		_A		(		_lowercase				,     _lowercase				,     _lowercase				,     _lowercase				,     )				->   None:
  
  
       """simple docstring"""
  
  
       __UpperCamelCase   = (abs(_lowercase   )).transpose()
       __UpperCamelCase   = abs_z_final[::-1, :]
       pyplot.matshow(abs_z_final < escape_radius   )
       pyplot.title(f'''Julia set of ${function_label}$, $c={function_params}$'''   )
       pyplot.show()
  
  
  
  
  
  
  def 		_A		(		)				->   None:
  
  
       """simple docstring"""
  
  
       warnings.filterwarnings(
           'ignore'				,     category=_lowercase				,     message='overflow encountered in multiply'   )
       warnings.filterwarnings(
           'ignore'				,     category=_lowercase				,     message='invalid value encountered in multiply'				,     )
       warnings.filterwarnings(
           'ignore'				,     category=_lowercase				,     message='overflow encountered in absolute'   )
       warnings.filterwarnings(
           'ignore'				,     category=_lowercase				,     message='overflow encountered in exp'   )
  
  
  if __name__ == "__main__":
      __snake_case             =	prepare_grid(window_size, nb_pixels)
  
      ignore_overflow_warnings()  # See file header for explanations
  
      __snake_case             =	2_4
      __snake_case             =	2 * abs(c_cauliflower) + 1
      __snake_case             =	iterate_function(
          eval_quadratic_polynomial,
          c_cauliflower,
          nb_iterations,
          z_a,
          infinity=1.1 * escape_radius,
      )
      show_results('''z^2+c''', c_cauliflower, escape_radius, z_final)
  
      __snake_case             =	6_4
      __snake_case             =	2 * abs(c_polynomial_a) + 1
      __snake_case             =	iterate_function(
          eval_quadratic_polynomial,
          c_polynomial_a,
          nb_iterations,
          z_a,
          infinity=1.1 * escape_radius,
      )
      show_results('''z^2+c''', c_polynomial_a, escape_radius, z_final)
  
      __snake_case             =	1_6_1
      __snake_case             =	2 * abs(c_polynomial_a) + 1
      __snake_case             =	iterate_function(
          eval_quadratic_polynomial,
          c_polynomial_a,
          nb_iterations,
          z_a,
          infinity=1.1 * escape_radius,
      )
      show_results('''z^2+c''', c_polynomial_a, escape_radius, z_final)
  
      __snake_case             =	1_2
      __snake_case             =	10_000.0
      __snake_case             =	iterate_function(
          eval_exponential,
          c_exponential,
          nb_iterations,
          z_a + 2,
          infinity=1.0e10,
      )
      show_results('''e^z+c''', c_exponential, escape_radius, z_final)
  
  
  