






import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


@require_tokenizers
class       __SCREAMING_SNAKE_CASE   (				__lowercase						,   unittest.TestCase):
						_SCREAMING_SNAKE_CASE		:    Any						=   RobertaTokenizer
						_SCREAMING_SNAKE_CASE		:    Any						=   RobertaTokenizerFast
						_SCREAMING_SNAKE_CASE		:    Optional[int]						=   True
						_SCREAMING_SNAKE_CASE		:    Tuple						=   {'''cls_token''': '''<s>'''}






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												super().setUp()

												# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
												lowerCAmelCase__        =  [
												    'l',
												    'o',
												    'w',
												    'e',
												    'r',
												    's',
												    't',
												    'i',
												    'd',
												    'n',
												    '\u0120',
												    '\u0120l',
												    '\u0120n',
												    '\u0120lo',
												    '\u0120low',
												    'er',
												    '\u0120lowest',
												    '\u0120newer',
												    '\u0120wider',
												    '<unk>',
												]
												lowerCAmelCase__        =  dict(zip(_UpperCamelCase       ,  range(len(_UpperCamelCase				)				)				)				)
												lowerCAmelCase__        =  ['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
												lowerCAmelCase__        =  {'unk_token': '<unk>'}

												lowerCAmelCase__        =  os.path.join(self.tmpdirname       ,  VOCAB_FILES_NAMES['vocab_file']				)
												lowerCAmelCase__        =  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(_UpperCamelCase				) + '\n'				)
												with open(self.merges_file       ,  'w'       ,  encoding='utf-8'				) as fp:
																		fp.write('\n'.join(_UpperCamelCase				)				)






						def  UpperCamelCase__ (		self       ,  **_UpperCamelCase				):






												"""simple docstring"""
												kwargs.update(self.special_tokens_map				)
												return self.tokenizer_class.from_pretrained(self.tmpdirname       ,  **_UpperCamelCase				)






						def  UpperCamelCase__ (		self       ,  **_UpperCamelCase				):






												"""simple docstring"""
												kwargs.update(self.special_tokens_map				)
												return RobertaTokenizerFast.from_pretrained(self.tmpdirname       ,  **_UpperCamelCase				)






						def  UpperCamelCase__ (		self       ,  _UpperCamelCase				):






												"""simple docstring"""
												lowerCAmelCase__        =  'lower newer'
												lowerCAmelCase__        =  'lower newer'
												return input_text, output_text






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  self.tokenizer_class(self.vocab_file       ,  self.merges_file       ,  **self.special_tokens_map				)
												lowerCAmelCase__        =  'lower newer'
												lowerCAmelCase__        =  ['l', 'o', 'w', 'er', '\u0120', 'n', 'e', 'w', 'er']
												lowerCAmelCase__        =  tokenizer.tokenize(_UpperCamelCase				)  # , add_prefix_space=True)
												self.assertListEqual(_UpperCamelCase       ,  _UpperCamelCase				)

												lowerCAmelCase__        =  tokens + [tokenizer.unk_token]
												lowerCAmelCase__        =  [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
												self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCamelCase				)       ,  _UpperCamelCase				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  self.get_tokenizer()

												self.assertListEqual(tokenizer.encode('Hello world!'       ,  add_special_tokens=_UpperCamelCase				)       ,  [0, 3_14_14, 2_32, 3_28, 2]				)
												self.assertListEqual(
												    tokenizer.encode('Hello world! cécé herlolip 418'       ,  add_special_tokens=_UpperCamelCase				)       ,  [0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]       ,  )






						@slow
						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  self.tokenizer_class.from_pretrained('roberta-base'				)

												lowerCAmelCase__        =  tokenizer.encode('sequence builders'       ,  add_special_tokens=_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.encode('multi-sequence build'       ,  add_special_tokens=_UpperCamelCase				)

												lowerCAmelCase__        =  tokenizer.encode(
												    'sequence builders'       ,  add_special_tokens=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.encode(
												    'sequence builders'       ,  'multi-sequence build'       ,  add_special_tokens=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase				)

												lowerCAmelCase__        =  tokenizer.build_inputs_with_special_tokens(_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.build_inputs_with_special_tokens(_UpperCamelCase       ,  _UpperCamelCase				)

												assert encoded_sentence == encoded_text_from_decode
												assert encoded_pair == encoded_pair_from_decode






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												lowerCAmelCase__        =  self.get_tokenizer()

												lowerCAmelCase__        =  'Encode this sequence.'
												lowerCAmelCase__        =  tokenizer.byte_encoder[' '.encode('utf-8'				)[0]]

												# Testing encoder arguments
												lowerCAmelCase__        =  tokenizer.encode(_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.convert_ids_to_tokens(encoded[0]				)[0]
												self.assertNotEqual(_UpperCamelCase       ,  _UpperCamelCase				)

												lowerCAmelCase__        =  tokenizer.encode(_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.convert_ids_to_tokens(encoded[0]				)[0]
												self.assertEqual(_UpperCamelCase       ,  _UpperCamelCase				)

												tokenizer.add_special_tokens({'bos_token': '<s>'}				)
												lowerCAmelCase__        =  tokenizer.encode(_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.convert_ids_to_tokens(encoded[1]				)[0]
												self.assertNotEqual(_UpperCamelCase       ,  _UpperCamelCase				)

												# Testing spaces after special tokens
												lowerCAmelCase__        =  '<mask>'
												tokenizer.add_special_tokens(
												    {'mask_token': AddedToken(_UpperCamelCase       ,  lstrip=_UpperCamelCase       ,  rstrip=_UpperCamelCase				)}				)  # mask token has a left space
												lowerCAmelCase__        =  tokenizer.convert_tokens_to_ids(_UpperCamelCase				)

												lowerCAmelCase__        =  'Encode <mask> sequence'
												lowerCAmelCase__        =  'Encode <mask>sequence'

												lowerCAmelCase__        =  tokenizer.encode(_UpperCamelCase				)
												lowerCAmelCase__        =  encoded.index(_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]				)[0]
												self.assertEqual(_UpperCamelCase       ,  _UpperCamelCase				)

												lowerCAmelCase__        =  tokenizer.encode(_UpperCamelCase				)
												lowerCAmelCase__        =  encoded.index(_UpperCamelCase				)
												lowerCAmelCase__        =  tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]				)[0]
												self.assertNotEqual(_UpperCamelCase       ,  _UpperCamelCase				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												pass






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"				):
																								lowerCAmelCase__        =  self.rust_tokenizer_class.from_pretrained(_UpperCamelCase       ,  **_UpperCamelCase				)
																								lowerCAmelCase__        =  self.tokenizer_class.from_pretrained(_UpperCamelCase       ,  **_UpperCamelCase				)
																								lowerCAmelCase__        =  'A, <mask> AllenNLP sentence.'
																								lowerCAmelCase__        =  tokenizer_r.encode_plus(_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase       ,  return_token_type_ids=_UpperCamelCase				)
																								lowerCAmelCase__        =  tokenizer_p.encode_plus(_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase       ,  return_token_type_ids=_UpperCamelCase				)

																								# token_type_ids should put 0 everywhere
																								self.assertEqual(sum(tokens_r['token_type_ids']				)       ,  sum(tokens_p['token_type_ids']				)				)

																								# attention_mask should put 1 everywhere, so sum over length should be 1
																								self.assertEqual(
																								    sum(tokens_r['attention_mask']				) / len(tokens_r['attention_mask']				)       ,  sum(tokens_p['attention_mask']				) / len(tokens_p['attention_mask']				)       ,  )

																								lowerCAmelCase__        =  tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids']				)
																								lowerCAmelCase__        =  tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids']				)

																								# Rust correctly handles the space before the mask while python doesnt
																								self.assertSequenceEqual(tokens_p['input_ids']       ,  [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]				)
																								self.assertSequenceEqual(tokens_r['input_ids']       ,  [0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2]				)

																								self.assertSequenceEqual(
																								    _UpperCamelCase       ,  ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']				)
																								self.assertSequenceEqual(
																								    _UpperCamelCase       ,  ['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>']				)






						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												for trim_offsets, add_prefix_space in itertools.product([True, False]       ,  repeat=2				):
																		lowerCAmelCase__        =  self.rust_tokenizer_class.from_pretrained(
																		    self.tmpdirname       ,  use_fast=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase       ,  trim_offsets=_UpperCamelCase				)

																		lowerCAmelCase__        =  json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()				)
																		lowerCAmelCase__        =  json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()				)

																		self.assertEqual(pre_tokenizer_state['add_prefix_space']       ,  _UpperCamelCase				)

																		self.assertEqual(post_processor_state['add_prefix_space']       ,  _UpperCamelCase				)
																		self.assertEqual(post_processor_state['trim_offsets']       ,  _UpperCamelCase				)







						def  UpperCamelCase__ (		self				):






												"""simple docstring"""
												# Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
												# `trim_offsets`
												for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(F"{tokenizer.__class__.__name__} ({pretrained_name})"				):
																								lowerCAmelCase__        =  'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
																								lowerCAmelCase__        =  F"{text_of_1_token} {text_of_1_token}"

																								lowerCAmelCase__        =  self.rust_tokenizer_class.from_pretrained(
																								    _UpperCamelCase       ,  use_fast=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase       ,  trim_offsets=_UpperCamelCase				)
																								lowerCAmelCase__        =  tokenizer_r(_UpperCamelCase       ,  return_offsets_mapping=_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase				)
																								self.assertEqual(encoding.offset_mapping[0]       ,  (0, len(_UpperCamelCase				))				)
																								self.assertEqual(
																								    encoding.offset_mapping[1]       ,  (len(_UpperCamelCase				) + 1, len(_UpperCamelCase				) + 1 + len(_UpperCamelCase				))       ,  )

																								lowerCAmelCase__        =  self.rust_tokenizer_class.from_pretrained(
																								    _UpperCamelCase       ,  use_fast=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase       ,  trim_offsets=_UpperCamelCase				)
																								lowerCAmelCase__        =  tokenizer_r(_UpperCamelCase       ,  return_offsets_mapping=_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase				)
																								self.assertEqual(encoding.offset_mapping[0]       ,  (0, len(_UpperCamelCase				))				)
																								self.assertEqual(
																								    encoding.offset_mapping[1]       ,  (len(_UpperCamelCase				) + 1, len(_UpperCamelCase				) + 1 + len(_UpperCamelCase				))       ,  )

																								lowerCAmelCase__        =  self.rust_tokenizer_class.from_pretrained(
																								    _UpperCamelCase       ,  use_fast=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase       ,  trim_offsets=_UpperCamelCase				)
																								lowerCAmelCase__        =  tokenizer_r(_UpperCamelCase       ,  return_offsets_mapping=_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase				)
																								self.assertEqual(encoding.offset_mapping[0]       ,  (0, len(_UpperCamelCase				))				)
																								self.assertEqual(
																								    encoding.offset_mapping[1]       ,  (len(_UpperCamelCase				), len(_UpperCamelCase				) + 1 + len(_UpperCamelCase				))       ,  )

																								lowerCAmelCase__        =  self.rust_tokenizer_class.from_pretrained(
																								    _UpperCamelCase       ,  use_fast=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase       ,  trim_offsets=_UpperCamelCase				)
																								lowerCAmelCase__        =  tokenizer_r(_UpperCamelCase       ,  return_offsets_mapping=_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase				)
																								self.assertEqual(encoding.offset_mapping[0]       ,  (0, len(_UpperCamelCase				))				)
																								self.assertEqual(
																								    encoding.offset_mapping[1]       ,  (len(_UpperCamelCase				), len(_UpperCamelCase				) + 1 + len(_UpperCamelCase				))       ,  )

																								lowerCAmelCase__        =  F" {text}"

																								# tokenizer_r = self.rust_tokenizer_class.from_pretrained(
																								#     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
																								# )
																								# encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
																								# self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
																								# self.assertEqual(
																								#     encoding.offset_mapping[1],
																								#     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
																								# )

																								lowerCAmelCase__        =  self.rust_tokenizer_class.from_pretrained(
																								    _UpperCamelCase       ,  use_fast=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase       ,  trim_offsets=_UpperCamelCase				)
																								lowerCAmelCase__        =  tokenizer_r(_UpperCamelCase       ,  return_offsets_mapping=_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase				)
																								self.assertEqual(encoding.offset_mapping[0]       ,  (1, 1 + len(_UpperCamelCase				))				)
																								self.assertEqual(
																								    encoding.offset_mapping[1]       ,  (1 + len(_UpperCamelCase				) + 1, 1 + len(_UpperCamelCase				) + 1 + len(_UpperCamelCase				))       ,  )

																								lowerCAmelCase__        =  self.rust_tokenizer_class.from_pretrained(
																								    _UpperCamelCase       ,  use_fast=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase       ,  trim_offsets=_UpperCamelCase				)
																								lowerCAmelCase__        =  tokenizer_r(_UpperCamelCase       ,  return_offsets_mapping=_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase				)
																								self.assertEqual(encoding.offset_mapping[0]       ,  (0, 1 + len(_UpperCamelCase				))				)
																								self.assertEqual(
																								    encoding.offset_mapping[1]       ,  (1 + len(_UpperCamelCase				), 1 + len(_UpperCamelCase				) + 1 + len(_UpperCamelCase				))       ,  )

																								lowerCAmelCase__        =  self.rust_tokenizer_class.from_pretrained(
																								    _UpperCamelCase       ,  use_fast=_UpperCamelCase       ,  add_prefix_space=_UpperCamelCase       ,  trim_offsets=_UpperCamelCase				)
																								lowerCAmelCase__        =  tokenizer_r(_UpperCamelCase       ,  return_offsets_mapping=_UpperCamelCase       ,  add_special_tokens=_UpperCamelCase				)
																								self.assertEqual(encoding.offset_mapping[0]       ,  (0, 1 + len(_UpperCamelCase				))				)
																								self.assertEqual(
																								    encoding.offset_mapping[1]       ,  (1 + len(_UpperCamelCase				), 1 + len(_UpperCamelCase				) + 1 + len(_UpperCamelCase				))       ,  )













import colorsys

from PIL import Image  # type: ignore







def 		_UpperCamelCase				(      UpperCamelCase_    :   float      ,    UpperCamelCase_    :   float      ,    UpperCamelCase_    :   int						)					->				float:

						"""simple docstring"""



						lowerCAmelCase__        =  x
						lowerCAmelCase__        =  y
						for step in range(UpperCamelCase_						):  # noqa: B007
												lowerCAmelCase__        =  a * a - b * b + x
												lowerCAmelCase__        =  2 * a * b + y
												lowerCAmelCase__        =  a_new

												# divergence happens for all complex number with an absolute value
												# greater than 4
												if a * a + b * b > 4:
																		break
						return step / (max_step - 1)







def 		_UpperCamelCase				(      UpperCamelCase_    :   float						)					->				tuple:

						"""simple docstring"""



						if distance == 1:
												return (0, 0, 0)
						else:
												return (255, 255, 255)







def 		_UpperCamelCase				(      UpperCamelCase_    :   float						)					->				tuple:

						"""simple docstring"""



						if distance == 1:
												return (0, 0, 0)
						else:
												return tuple(round(i * 255						) for i in colorsys.hsv_to_rgb(UpperCamelCase_      ,    1      ,    1						)						)







def 		_UpperCamelCase				(      UpperCamelCase_    :   int = 800      ,    UpperCamelCase_    :   int = 600      ,    UpperCamelCase_    :   float = -0.6      ,    UpperCamelCase_    :   float = 0      ,    UpperCamelCase_    :   float = 3.2      ,    UpperCamelCase_    :   int = 50      ,    UpperCamelCase_    :   bool = True      ,    )					->				Image.Image:

						"""simple docstring"""



						lowerCAmelCase__        =  Image.new('RGB'      ,    (image_width, image_height)						)
						lowerCAmelCase__        =  img.load()

						# loop through the image-coordinates
						for image_x in range(UpperCamelCase_						):
												for image_y in range(UpperCamelCase_						):
																		# determine the figure-coordinates based on the image-coordinates
																		lowerCAmelCase__        =  figure_width / image_width * image_height
																		lowerCAmelCase__        =  figure_center_x + (image_x / image_width - 0.5) * figure_width
																		lowerCAmelCase__        =  figure_center_y + (image_y / image_height - 0.5) * figure_height

																		lowerCAmelCase__        =  get_distance(UpperCamelCase_      ,    UpperCamelCase_      ,    UpperCamelCase_						)

																		# color the corresponding pixel based on the selected coloring-function
																		if use_distance_color_coding:
																								lowerCAmelCase__        =  get_color_coded_rgb(UpperCamelCase_						)
																		else:
																								lowerCAmelCase__        =  get_black_and_white_rgb(UpperCamelCase_						)

						return img


if __name__ == "__main__":
					import doctest

					doctest.testmod()

					# colored version, full figure
					__snake_case      :      str             =       get_image()

					# uncomment for colored version, different section, zoomed in
					# img = get_image(figure_center_x = -0.6, figure_center_y = -0.4,
					# figure_width = 0.8)

					# uncomment for black and white version, full figure
					# img = get_image(use_distance_color_coding = False)

					# uncomment to save the image
					# img.save("mandelbrot.png")

					img.show()





