

"""simple docstring"""




import warnings
from collections.abc import Callable
from typing import Any

import numpy
from matplotlib import pyplot

__A	:       List[Any]        =						0.25 + 0.0J
__A	:       Tuple        =						-0.4 + 0.6J
__A	:       List[Any]        =						-0.1 + 0.651J
__A	:       Union[str, Any]        =						-2.0
__A	:       Dict        =						56
__A	:       List[Any]        =						2.0
__A	:       Optional[Any]        =						6_66
def   __SCREAMING_SNAKE_CASE		(		lowercase__     ,				lowercase__ ):
					"""simple docstring"""
					return numpy.exp(lowercase__ ) + c_parameter
def   __SCREAMING_SNAKE_CASE		(		lowercase__     ,				lowercase__ ):
					"""simple docstring"""
					return z_values * z_values + c_parameter
def   __SCREAMING_SNAKE_CASE		(		lowercase__     ,				lowercase__ ):
					"""simple docstring"""
					A     =   numpy.linspace(-window_size     ,				lowercase__     ,				lowercase__ )
					A     =   x.reshape((nb_pixels, 1) )
					A     =   numpy.linspace(-window_size     ,				lowercase__     ,				lowercase__ )
					A     =   y.reshape((1, nb_pixels) )
					return x + 1.0J * y
def   __SCREAMING_SNAKE_CASE		(		lowercase__     ,				lowercase__     ,				lowercase__     ,				lowercase__     ,				lowercase__ = None     ,				):
					"""simple docstring"""
					A     =   z_a.astype("complex64" )
					for _ in range(lowercase__ ):
										A     =   eval_function(lowercase__     ,				lowercase__ )
										if infinity is not None:
															numpy.nan_to_num(lowercase__     ,				copy=lowercase__     ,				nan=lowercase__ )
															A     =   infinity
					return z_n
def   __SCREAMING_SNAKE_CASE		(		lowercase__     ,				lowercase__     ,				lowercase__     ,				lowercase__     ,				):
					"""simple docstring"""
					A     =   (abs(lowercase__ )).transpose()
					A     =   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   __SCREAMING_SNAKE_CASE		(		):
					"""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__":
	__A	:       Optional[Any]        =						prepare_grid(window_size, nb_pixels)

	ignore_overflow_warnings()  # See file header for explanations

	__A	:       Optional[Any]        =						24
	__A	:       Optional[int]        =						2 * abs(c_cauliflower) + 1
	__A	:       int        =						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)

	__A	:       Optional[Any]        =						64
	__A	:       List[str]        =						2 * abs(c_polynomial_a) + 1
	__A	:       Union[str, Any]        =						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)

	__A	:       Any        =						1_61
	__A	:       Union[str, Any]        =						2 * abs(c_polynomial_a) + 1
	__A	:       int        =						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)

	__A	:       str        =						12
	__A	:       List[str]        =						1_00_00.0
	__A	:       Dict        =						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)











import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
 from .tokenization_xlm_roberta import XLMRobertaTokenizer
else:
 a_ 		=  None


a_ 		=  logging.get_logger(__name__)

a_ 		=  {"vocab_file": "sentencepiece.bpe.model", "tokenizer_file": "tokenizer.json"}

a_ 		=  {
    "vocab_file": {
        "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/sentencepiece.bpe.model",
        "xlm-roberta-large-finetuned-conll02-dutch": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll02-spanish": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-english": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/sentencepiece.bpe.model"
        ),
        "xlm-roberta-large-finetuned-conll03-german": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/sentencepiece.bpe.model"
        ),
    },
    "tokenizer_file": {
        "xlm-roberta-base": "https://huggingface.co/xlm-roberta-base/resolve/main/tokenizer.json",
        "xlm-roberta-large": "https://huggingface.co/xlm-roberta-large/resolve/main/tokenizer.json",
        "xlm-roberta-large-finetuned-conll02-dutch": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/tokenizer.json"
        ),
        "xlm-roberta-large-finetuned-conll02-spanish": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/tokenizer.json"
        ),
        "xlm-roberta-large-finetuned-conll03-english": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/tokenizer.json"
        ),
        "xlm-roberta-large-finetuned-conll03-german": (
            "https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/tokenizer.json"
        ),
    },
}

a_ 		=  {
    "xlm-roberta-base": 512,
    "xlm-roberta-large": 512,
    "xlm-roberta-large-finetuned-conll02-dutch": 512,
    "xlm-roberta-large-finetuned-conll02-spanish": 512,
    "xlm-roberta-large-finetuned-conll03-english": 512,
    "xlm-roberta-large-finetuned-conll03-german": 512,
}

class 			_lowerCamelCase    (      _SCREAMING_SNAKE_CASE ):

      """simple docstring"""

      lowerCAmelCase__      :			List[Any]     =       VOCAB_FILES_NAMES
      lowerCAmelCase__      :			List[Any]     =       PRETRAINED_VOCAB_FILES_MAP
      lowerCAmelCase__      :			Optional[Any]     =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCAmelCase__      :			Optional[int]     =       ["input_ids", "attention_mask"]
      lowerCAmelCase__      :			Union[str, Any]     =       XLMRobertaTokenizer







      def __init__(  self       :			str			,							snake_case       :			Union[str, Any]=None			,							snake_case       :			Any=None			,							snake_case       :			Union[str, Any]="<s>"			,							snake_case       :			Tuple="</s>"			,							snake_case       :			List[Any]="</s>"			,							snake_case       :			Any="<s>"			,							snake_case       :			str="<unk>"			,							snake_case       :			int="<pad>"			,							snake_case       :			Any="<mask>"			,							**snake_case       :			str			,							):
          # Mask token behave like a normal word, i.e. include the space before it
          __UpperCamelCase			=    AddedToken(snake_case			,							lstrip=snake_case			,							rstrip=snake_case					) if isinstance(snake_case			,							snake_case					) else mask_token

          super().__init__(
              snake_case			,							tokenizer_file=snake_case			,							bos_token=snake_case			,							eos_token=snake_case			,							sep_token=snake_case			,							cls_token=snake_case			,							unk_token=snake_case			,							pad_token=snake_case			,							mask_token=snake_case			,							**snake_case			,							)

          __UpperCamelCase			=    vocab_file
          __UpperCamelCase			=    False if not self.vocab_file else True







      def    snake_case						(  self       :			List[Any]			,							snake_case       :			List[int]			,							snake_case       :			Optional[List[int]] = None					):

          if token_ids_a is None:
              return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          __UpperCamelCase			=    [self.cls_token_id]
          __UpperCamelCase			=    [self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep







      def    snake_case						(  self       :			Any			,							snake_case       :			List[int]			,							snake_case       :			Optional[List[int]] = None					):
          __UpperCamelCase			=    [self.sep_token_id]
          __UpperCamelCase			=    [self.cls_token_id]

          if token_ids_a is None:
              return len(cls + token_ids_a + sep					) * [0]
          return len(cls + token_ids_a + sep + sep + token_ids_a + sep					) * [0]







      def    snake_case						(  self       :			Dict			,							snake_case       :			str			,							snake_case       :			Optional[str] = None					):
          if not self.can_save_slow_tokenizer:
              raise ValueError(
                  '''Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '''
                  '''tokenizer.'''					)

          if not os.path.isdir(snake_case					):
              logger.error(F"Vocabulary path ({save_directory}) should be a directory."					)
              return
          __UpperCamelCase			=    os.path.join(
              snake_case			,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']					)

          if os.path.abspath(self.vocab_file					) != os.path.abspath(snake_case					):
              copyfile(self.vocab_file			,							snake_case					)

          return (out_vocab_file,)






