
'''simple docstring'''





import colorsys
import io

import cva
import matplotlib as mpl
import matplotlib.colors as mplc
import matplotlib.figure as mplfigure
import numpy as np
import torch
from matplotlib.backends.backend_agg import FigureCanvasAgg

from utils import img_tensorize


UpperCAmelCase            = 1_000

class     a :




				def __init__(				self						:					Optional[int],     SCREAMING_SNAKE_CASE_						:					Tuple,     SCREAMING_SNAKE_CASE_						:					int=1.2,     SCREAMING_SNAKE_CASE_						:					Optional[Any]="g",     SCREAMING_SNAKE_CASE_						:					Any=0.5,     SCREAMING_SNAKE_CASE_						:					int="-",     SCREAMING_SNAKE_CASE_						:					Dict="test_out.jpg",     SCREAMING_SNAKE_CASE_						:					Any=True,     SCREAMING_SNAKE_CASE_						:					Tuple=False,     SCREAMING_SNAKE_CASE_						:					Any=None,     SCREAMING_SNAKE_CASE_						:					str=None,     SCREAMING_SNAKE_CASE_						:					str=0.7,     ):
										if isinstance(SCREAMING_SNAKE_CASE_,     torch.Tensor   ):
																snake_case							:  Dict			=     img.numpy().astype('''np.uint8'''   )
										if isinstance(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_   ):
																snake_case							:  List[Any]			=     img_tensorize(SCREAMING_SNAKE_CASE_   )
										assert isinstance(SCREAMING_SNAKE_CASE_,     np.ndarray   )

										snake_case,       snake_case							:  Optional[Any]			=     img.shape[1], img.shape[0]
										snake_case							:  int			=     mplfigure.Figure(frameon=SCREAMING_SNAKE_CASE_   )
										snake_case							:  int			=     fig.get_dpi()
										snake_case							:  Optional[int]			=     (width * scale + 1e-2) / dpi
										snake_case							:  List[Any]			=     (height * scale + 1e-2) / dpi
										fig.set_size_inches(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_   )
										snake_case							:  Any			=     fig.add_axes([0.0, 0.0, 1.0, 1.0]   )
										ax.axis('''off'''   )
										ax.set_xlim(0.0,     SCREAMING_SNAKE_CASE_   )
										ax.set_ylim(SCREAMING_SNAKE_CASE_   )

										snake_case							:  Union[str, Any]			=     saveas
										snake_case							:  str			=     rgb
										snake_case							:  Tuple			=     pynb
										snake_case							:  Optional[int]			=     img
										snake_case							:  List[str]			=     edgecolor
										snake_case							:  str			=     0.5
										snake_case							:  Optional[Any]			=     linestyle
										snake_case							:  Optional[Any]			=     int(np.sqrt(min(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_   )   ) * scale // 3   )
										snake_case							:  Any			=     width
										snake_case							:  List[str]			=     height
										snake_case							:  Optional[Any]			=     scale
										snake_case							:  int			=     fig
										snake_case							:  Optional[int]			=     ax
										snake_case							:  List[str]			=     pad
										snake_case							:  Tuple			=     idaobj
										snake_case							:  Tuple			=     idaattr
										snake_case							:  Dict			=     FigureCanvasAgg(SCREAMING_SNAKE_CASE_   )




				def 						__snake_case				(				self						:					Tuple,     SCREAMING_SNAKE_CASE_						:					Union[str, Any],     SCREAMING_SNAKE_CASE_						:					int=None   ):
										if color is None:
																snake_case							:  int			=     self.edgecolor
										((snake_case),       (snake_case),       (snake_case),       (snake_case))							:  Optional[int]			=     box
										snake_case							:  List[Any]			=     xa - xa
										snake_case							:  Optional[int]			=     ya - ya
										self.ax.add_patch(
										    mpl.patches.Rectangle(
										        (xa, ya),     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     fill=SCREAMING_SNAKE_CASE_,     edgecolor=SCREAMING_SNAKE_CASE_,     linewidth=self.font_size // 3,     alpha=self.alpha,     linestyle=self.linestyle,     )   )




				def 						__snake_case				(				self						:					Tuple,     SCREAMING_SNAKE_CASE_						:					Optional[Any],     SCREAMING_SNAKE_CASE_						:					str=None,     SCREAMING_SNAKE_CASE_						:					Union[str, Any]=None,     SCREAMING_SNAKE_CASE_						:					Optional[int]=None,     SCREAMING_SNAKE_CASE_						:					Tuple=None   ):
										if len(boxes.shape   ) > 2:
																snake_case							:  Dict			=     boxes[0]
										if len(obj_ids.shape   ) > 1:
																snake_case							:  Optional[int]			=     obj_ids[0]
										if len(obj_scores.shape   ) > 1:
																snake_case							:  str			=     obj_scores[0]
										if len(attr_ids.shape   ) > 1:
																snake_case							:  int			=     attr_ids[0]
										if len(attr_scores.shape   ) > 1:
																snake_case							:  Union[str, Any]			=     attr_scores[0]
										if isinstance(SCREAMING_SNAKE_CASE_,     torch.Tensor   ):
																snake_case							:  List[Any]			=     boxes.numpy()
										if isinstance(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_   ):
																snake_case							:  str			=     np.array(SCREAMING_SNAKE_CASE_   )
										assert isinstance(SCREAMING_SNAKE_CASE_,     np.ndarray   )
										snake_case							:  Optional[int]			=     np.prod(boxes[:, 2:] - boxes[:, :2],     axis=1   )
										snake_case							:  str			=     np.argsort(-areas   ).tolist()
										snake_case							:  Union[str, Any]			=     boxes[sorted_idxs] if boxes is not None else None
										snake_case							:  Dict			=     obj_ids[sorted_idxs] if obj_ids is not None else None
										snake_case							:  Tuple			=     obj_scores[sorted_idxs] if obj_scores is not None else None
										snake_case							:  List[str]			=     attr_ids[sorted_idxs] if attr_ids is not None else None
										snake_case							:  Optional[int]			=     attr_scores[sorted_idxs] if attr_scores is not None else None

										snake_case							:  Union[str, Any]			=     [self._random_color(maximum=1   ) for _ in range(len(SCREAMING_SNAKE_CASE_   )   )]
										snake_case							:  List[Any]			=     [assigned_colors[idx] for idx in sorted_idxs]
										if obj_ids is not None:
																snake_case							:  Dict			=     self._create_text_labels_attr(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_   )
																for i in range(len(SCREAMING_SNAKE_CASE_   )   ):
																						snake_case							:  Any			=     assigned_colors[i]
																						self.add_box(boxes[i],     SCREAMING_SNAKE_CASE_   )
																						self.draw_labels(labels[i],     boxes[i],     SCREAMING_SNAKE_CASE_   )




				def 						__snake_case				(				self						:					List[str],     SCREAMING_SNAKE_CASE_						:					int,     SCREAMING_SNAKE_CASE_						:					Optional[int],     SCREAMING_SNAKE_CASE_						:					Union[str, Any]   ):
										snake_case,       snake_case,       snake_case,       snake_case							:  Dict			=     box
										snake_case							:  Union[str, Any]			=     (xa, ya)
										snake_case							:  Any			=     (ya - ya) * (xa - xa)
										snake_case							:  Any			=     _SMALL_OBJ * self.scale
										if instance_area < small or ya - ya < 40 * self.scale:
																if ya >= self.height - 5:
																						snake_case							:  Union[str, Any]			=     (xa, ya)
																else:
																						snake_case							:  Dict			=     (xa, ya)

										snake_case							:  List[str]			=     (ya - ya) / np.sqrt(self.height * self.width   )
										snake_case							:  Union[str, Any]			=     self._change_color_brightness(SCREAMING_SNAKE_CASE_,     brightness_factor=0.7   )
										snake_case							:  int			=     np.clip((height_ratio - 0.02) / 0.08 + 1,     1.2,     2   )
										font_size *= 0.75 * self.font_size

										self.draw_text(
										    text=SCREAMING_SNAKE_CASE_,     position=SCREAMING_SNAKE_CASE_,     color=SCREAMING_SNAKE_CASE_,     )




				def 						__snake_case				(				self						:					Optional[Any],     SCREAMING_SNAKE_CASE_						:					Union[str, Any],     SCREAMING_SNAKE_CASE_						:					Tuple,     SCREAMING_SNAKE_CASE_						:					List[str]="g",     SCREAMING_SNAKE_CASE_						:					List[str]="left",     ):
										snake_case							:  Optional[int]			=     0
										snake_case							:  Tuple			=     self.font_size
										snake_case							:  Tuple			=     np.maximum(list(mplc.to_rgb(SCREAMING_SNAKE_CASE_   )   ),     0.2   )
										snake_case							:  Dict			=     max(0.8,     np.max(SCREAMING_SNAKE_CASE_   )   )
										snake_case							:  List[Any]			=     {
										    '''facecolor''': '''black''',
										    '''alpha''': self.alpha,
										    '''pad''': self.pad,
										    '''edgecolor''': '''none''',
										}
										snake_case,       snake_case							:  str			=     position
										self.ax.text(
										    SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     size=font_size * self.scale,     family='''sans-serif''',     bbox=SCREAMING_SNAKE_CASE_,     verticalalignment='''top''',     horizontalalignment=SCREAMING_SNAKE_CASE_,     color=SCREAMING_SNAKE_CASE_,     zorder=10,     rotation=SCREAMING_SNAKE_CASE_,     )




				def 						__snake_case				(				self						:					Any,     SCREAMING_SNAKE_CASE_						:					Any=None   ):
										if saveas is None:
																snake_case							:  List[str]			=     self.saveas
										if saveas.lower().endswith('''.jpg'''   ) or saveas.lower().endswith('''.png'''   ):
																cva.imwrite(
																    SCREAMING_SNAKE_CASE_,     self._get_buffer()[:, :, ::-1],     )
										else:
																self.fig.savefig(SCREAMING_SNAKE_CASE_   )




				def 						__snake_case				(				self						:					Tuple,     SCREAMING_SNAKE_CASE_						:					Optional[int],     SCREAMING_SNAKE_CASE_						:					str,     SCREAMING_SNAKE_CASE_						:					str,     SCREAMING_SNAKE_CASE_						:					int   ):
										snake_case							:  int			=     [self.idaobj[i] for i in classes]
										snake_case							:  str			=     [self.idaattr[i] for i in attr_classes]
										snake_case							:  Optional[Any]			=     [
										    F"""{label} {score:.2f} {attr} {attr_score:.2f}"""
										    for label, score, attr, attr_score in zip(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_   )
										]
										return labels




				def 						__snake_case				(				self						:					Any,     SCREAMING_SNAKE_CASE_						:					List[Any],     SCREAMING_SNAKE_CASE_						:					List[str]   ):
										snake_case							:  Union[str, Any]			=     [self.idaobj[i] for i in classes]
										if scores is not None:
																if labels is None:
																						snake_case							:  Optional[Any]			=     ['''{:.0f}%'''.format(s * 1_00   ) for s in scores]
																else:
																						snake_case							:  str			=     ['''{} {:.0f}%'''.format(SCREAMING_SNAKE_CASE_,     s * 1_00   ) for li, s in zip(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_   )]
										return labels




				def 						__snake_case				(				self						:					Union[str, Any],     SCREAMING_SNAKE_CASE_						:					int=2_55   ):
										snake_case							:  Union[str, Any]			=     np.random.randint(0,     len(_COLORS   )   )
										snake_case							:  Optional[int]			=     _COLORS[idx] * maximum
										if not self.rgb:
																snake_case							:  str			=     ret[::-1]
										return ret




				def 						__snake_case				(				self						:					List[Any]   ):
										if not self.pynb:
																snake_case,       snake_case							:  int			=     self.canvas.print_to_buffer()
																if (width, height) != (self.width, self.height):
																						snake_case							:  List[Any]			=     cva.resize(self.img,     (width, height)   )
																else:
																						snake_case							:  Tuple			=     self.img
										else:
																snake_case							:  List[str]			=     io.BytesIO()  # works for cairo backend
																self.canvas.print_rgba(SCREAMING_SNAKE_CASE_   )
																snake_case,       snake_case							:  Union[str, Any]			=     self.width, self.height
																snake_case							:  Optional[Any]			=     buf.getvalue()
																snake_case							:  List[Any]			=     self.img

										snake_case							:  Union[str, Any]			=     np.frombuffer(SCREAMING_SNAKE_CASE_,     dtype='''uint8'''   )
										snake_case							:  Union[str, Any]			=     buffer.reshape(SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_,     4   )
										snake_case,       snake_case							:  Any			=     np.split(SCREAMING_SNAKE_CASE_,     [3],     axis=2   )

										try:
																import numexpr as ne  # fuse them with numexpr

																snake_case							:  str			=     ne.evaluate('''img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)'''   )
										except ImportError:
																snake_case							:  Dict			=     alpha.astype('''float32'''   ) / 255.0
																snake_case							:  Tuple			=     img * (1 - alpha) + rgb * alpha

										return visualized_image.astype('''uint8'''   )




				def 						__snake_case				(				self						:					List[str],     SCREAMING_SNAKE_CASE_						:					Optional[int],     SCREAMING_SNAKE_CASE_						:					Any   ):
										assert brightness_factor >= -1.0 and brightness_factor <= 1.0
										snake_case							:  Any			=     mplc.to_rgb(SCREAMING_SNAKE_CASE_   )
										snake_case							:  List[str]			=     colorsys.rgb_to_hls(*mplc.to_rgb(SCREAMING_SNAKE_CASE_   )   )
										snake_case							:  Union[str, Any]			=     polygon_color[1] + (brightness_factor * polygon_color[1])
										snake_case							:  List[Any]			=     0.0 if modified_lightness < 0.0 else modified_lightness
										snake_case							:  Dict			=     1.0 if modified_lightness > 1.0 else modified_lightness
										snake_case							:  Dict			=     colorsys.hls_to_rgb(polygon_color[0],     SCREAMING_SNAKE_CASE_,     polygon_color[2]   )
										return modified_color




UpperCAmelCase            = (
    np.array(
        [
            0.000,
            0.447,
            0.741,
            0.850,
            0.325,
            0.098,
            0.929,
            0.694,
            0.125,
            0.494,
            0.184,
            0.556,
            0.466,
            0.674,
            0.188,
            0.301,
            0.745,
            0.933,
            0.635,
            0.078,
            0.184,
            0.300,
            0.300,
            0.300,
            0.600,
            0.600,
            0.600,
            1.000,
            0.000,
            0.000,
            1.000,
            0.500,
            0.000,
            0.749,
            0.749,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            1.000,
            0.667,
            0.000,
            1.000,
            0.333,
            0.333,
            0.000,
            0.333,
            0.667,
            0.000,
            0.333,
            1.000,
            0.000,
            0.667,
            0.333,
            0.000,
            0.667,
            0.667,
            0.000,
            0.667,
            1.000,
            0.000,
            1.000,
            0.333,
            0.000,
            1.000,
            0.667,
            0.000,
            1.000,
            1.000,
            0.000,
            0.000,
            0.333,
            0.500,
            0.000,
            0.667,
            0.500,
            0.000,
            1.000,
            0.500,
            0.333,
            0.000,
            0.500,
            0.333,
            0.333,
            0.500,
            0.333,
            0.667,
            0.500,
            0.333,
            1.000,
            0.500,
            0.667,
            0.000,
            0.500,
            0.667,
            0.333,
            0.500,
            0.667,
            0.667,
            0.500,
            0.667,
            1.000,
            0.500,
            1.000,
            0.000,
            0.500,
            1.000,
            0.333,
            0.500,
            1.000,
            0.667,
            0.500,
            1.000,
            1.000,
            0.500,
            0.000,
            0.333,
            1.000,
            0.000,
            0.667,
            1.000,
            0.000,
            1.000,
            1.000,
            0.333,
            0.000,
            1.000,
            0.333,
            0.333,
            1.000,
            0.333,
            0.667,
            1.000,
            0.333,
            1.000,
            1.000,
            0.667,
            0.000,
            1.000,
            0.667,
            0.333,
            1.000,
            0.667,
            0.667,
            1.000,
            0.667,
            1.000,
            1.000,
            1.000,
            0.000,
            1.000,
            1.000,
            0.333,
            1.000,
            1.000,
            0.667,
            1.000,
            0.333,
            0.000,
            0.000,
            0.500,
            0.000,
            0.000,
            0.667,
            0.000,
            0.000,
            0.833,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            0.167,
            0.000,
            0.000,
            0.333,
            0.000,
            0.000,
            0.500,
            0.000,
            0.000,
            0.667,
            0.000,
            0.000,
            0.833,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            0.167,
            0.000,
            0.000,
            0.333,
            0.000,
            0.000,
            0.500,
            0.000,
            0.000,
            0.667,
            0.000,
            0.000,
            0.833,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            0.143,
            0.143,
            0.143,
            0.857,
            0.857,
            0.857,
            1.000,
            1.000,
            1.000,
        ]
    )
    .astype(np.floataa)
    .reshape(-1, 3)
)


import os
import unittest

from transformers import RealmTokenizerFast
from transformers.models.bert.tokenization_bert import (
    VOCAB_FILES_NAMES,
    BasicTokenizer,
    WordpieceTokenizer,
    _is_control,
    _is_punctuation,
    _is_whitespace,
)
from transformers.models.realm.tokenization_realm import RealmTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin, filter_non_english





@require_tokenizers
class 					__snake_case    (     _lowerCamelCase       ,unittest.TestCase      ):
					__lowerCamelCase			   =  RealmTokenizer
					__lowerCamelCase			   =  RealmTokenizerFast
					__lowerCamelCase			   =  True
					__lowerCamelCase			   =  True
					__lowerCamelCase			   =  filter_non_english




					def      __a     (  self						)	->    Optional[Any]:



									'''simple docstring'''







									super().setUp()

									snake_case__   :      Any   				= [
									    '[UNK]',
									    '[CLS]',
									    '[SEP]',
									    '[PAD]',
									    '[MASK]',
									    'want',
									    '##want',
									    '##ed',
									    'wa',
									    'un',
									    'runn',
									    '##ing',
									    ',',
									    'low',
									    'lowest',
									]
									snake_case__   :      int   				= os.path.join(self.tmpdirname       ,			VOCAB_FILES_NAMES['vocab_file']						)
									with open(self.vocab_file       ,			'w'       ,			encoding='utf-8'						) as vocab_writer:
													vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]						)						)




					def      __a     (  self       ,			__UpperCamelCase						)	->    Optional[Any]:



									'''simple docstring'''







									snake_case__   :      Optional[int]   				= 'UNwant\u00E9d,running'
									snake_case__   :      Optional[Any]   				= 'unwanted, running'
									return input_text, output_text




					def      __a     (  self						)	->    Union[str, Any]:



									'''simple docstring'''







									snake_case__   :      Optional[Any]   				= self.tokenizer_class(self.vocab_file						)

									snake_case__   :      Any   				= tokenizer.tokenize('UNwant\u00E9d,running'						)
									self.assertListEqual(__UpperCamelCase       ,			['un', '##want', '##ed', ',', 'runn', '##ing']						)
									self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCamelCase						)       ,			[9, 6, 7, 12, 10, 11]						)




					def      __a     (  self						)	->    Union[str, Any]:



									'''simple docstring'''







									if not self.test_rust_tokenizer:
													return

									snake_case__   :      Any   				= self.get_tokenizer()
									snake_case__   :      Tuple   				= self.get_rust_tokenizer()

									snake_case__   :      Tuple   				= 'UNwant\u00E9d,running'

									snake_case__   :      Optional[int]   				= tokenizer.tokenize(__UpperCamelCase						)
									snake_case__   :      Dict   				= rust_tokenizer.tokenize(__UpperCamelCase						)
									self.assertListEqual(__UpperCamelCase       ,			__UpperCamelCase						)

									snake_case__   :      Optional[int]   				= tokenizer.encode(__UpperCamelCase       ,			add_special_tokens=__UpperCamelCase						)
									snake_case__   :      int   				= rust_tokenizer.encode(__UpperCamelCase       ,			add_special_tokens=__UpperCamelCase						)
									self.assertListEqual(__UpperCamelCase       ,			__UpperCamelCase						)

									snake_case__   :      Optional[int]   				= self.get_rust_tokenizer()
									snake_case__   :      Optional[Any]   				= tokenizer.encode(__UpperCamelCase						)
									snake_case__   :      Union[str, Any]   				= rust_tokenizer.encode(__UpperCamelCase						)
									self.assertListEqual(__UpperCamelCase       ,			__UpperCamelCase						)

									# With lower casing
									snake_case__   :      Union[str, Any]   				= self.get_tokenizer(do_lower_case=__UpperCamelCase						)
									snake_case__   :      Union[str, Any]   				= self.get_rust_tokenizer(do_lower_case=__UpperCamelCase						)

									snake_case__   :      str   				= 'UNwant\u00E9d,running'

									snake_case__   :      List[Any]   				= tokenizer.tokenize(__UpperCamelCase						)
									snake_case__   :      str   				= rust_tokenizer.tokenize(__UpperCamelCase						)
									self.assertListEqual(__UpperCamelCase       ,			__UpperCamelCase						)

									snake_case__   :      Union[str, Any]   				= tokenizer.encode(__UpperCamelCase       ,			add_special_tokens=__UpperCamelCase						)
									snake_case__   :      str   				= rust_tokenizer.encode(__UpperCamelCase       ,			add_special_tokens=__UpperCamelCase						)
									self.assertListEqual(__UpperCamelCase       ,			__UpperCamelCase						)

									snake_case__   :      Any   				= self.get_rust_tokenizer()
									snake_case__   :      int   				= tokenizer.encode(__UpperCamelCase						)
									snake_case__   :      List[str]   				= rust_tokenizer.encode(__UpperCamelCase						)
									self.assertListEqual(__UpperCamelCase       ,			__UpperCamelCase						)




					def      __a     (  self						)	->    Optional[int]:



									'''simple docstring'''







									snake_case__   :      Optional[int]   				= BasicTokenizer()

									self.assertListEqual(tokenizer.tokenize('ah\u535A\u63A8zz'						)       ,			['ah', '\u535A', '\u63A8', 'zz']						)




					def      __a     (  self						)	->    str:



									'''simple docstring'''







									snake_case__   :      Any   				= BasicTokenizer(do_lower_case=__UpperCamelCase						)

									self.assertListEqual(
									    tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '						)       ,			['hello', '!', 'how', 'are', 'you', '?']						)
									self.assertListEqual(tokenizer.tokenize('H\u00E9llo'						)       ,			['hello']						)




					def      __a     (  self						)	->    Union[str, Any]:



									'''simple docstring'''







									snake_case__   :      Optional[Any]   				= BasicTokenizer(do_lower_case=__UpperCamelCase       ,			strip_accents=__UpperCamelCase						)

									self.assertListEqual(
									    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '						)       ,			['hällo', '!', 'how', 'are', 'you', '?']						)
									self.assertListEqual(tokenizer.tokenize('H\u00E9llo'						)       ,			['h\u00E9llo']						)




					def      __a     (  self						)	->    Dict:



									'''simple docstring'''







									snake_case__   :      int   				= BasicTokenizer(do_lower_case=__UpperCamelCase       ,			strip_accents=__UpperCamelCase						)

									self.assertListEqual(
									    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '						)       ,			['hallo', '!', 'how', 'are', 'you', '?']						)
									self.assertListEqual(tokenizer.tokenize('H\u00E9llo'						)       ,			['hello']						)




					def      __a     (  self						)	->    Dict:



									'''simple docstring'''







									snake_case__   :      Any   				= BasicTokenizer(do_lower_case=__UpperCamelCase						)

									self.assertListEqual(
									    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '						)       ,			['hallo', '!', 'how', 'are', 'you', '?']						)
									self.assertListEqual(tokenizer.tokenize('H\u00E9llo'						)       ,			['hello']						)




					def      __a     (  self						)	->    List[Any]:



									'''simple docstring'''







									snake_case__   :      List[str]   				= BasicTokenizer(do_lower_case=__UpperCamelCase						)

									self.assertListEqual(
									    tokenizer.tokenize(' \tHeLLo!how  \n Are yoU?  '						)       ,			['HeLLo', '!', 'how', 'Are', 'yoU', '?']						)




					def      __a     (  self						)	->    int:



									'''simple docstring'''







									snake_case__   :      Optional[Any]   				= BasicTokenizer(do_lower_case=__UpperCamelCase       ,			strip_accents=__UpperCamelCase						)

									self.assertListEqual(
									    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '						)       ,			['HäLLo', '!', 'how', 'Are', 'yoU', '?']						)




					def      __a     (  self						)	->    Optional[int]:



									'''simple docstring'''







									snake_case__   :      Dict   				= BasicTokenizer(do_lower_case=__UpperCamelCase       ,			strip_accents=__UpperCamelCase						)

									self.assertListEqual(
									    tokenizer.tokenize(' \tHäLLo!how  \n Are yoU?  '						)       ,			['HaLLo', '!', 'how', 'Are', 'yoU', '?']						)




					def      __a     (  self						)	->    str:



									'''simple docstring'''







									snake_case__   :      Union[str, Any]   				= BasicTokenizer(do_lower_case=__UpperCamelCase       ,			never_split=['[UNK]']						)

									self.assertListEqual(
									    tokenizer.tokenize(' \tHeLLo!how  \n Are yoU? [UNK]'						)       ,			['HeLLo', '!', 'how', 'Are', 'yoU', '?', '[UNK]']						)




					def      __a     (  self						)	->    Tuple:



									'''simple docstring'''







									snake_case__   :      List[str]   				= ['[UNK]', '[CLS]', '[SEP]', 'want', '##want', '##ed', 'wa', 'un', 'runn', '##ing']

									snake_case__   :      List[str]   				= {}
									for i, token in enumerate(__UpperCamelCase						):
													snake_case__   :      Union[str, Any]   				= i
									snake_case__   :      List[Any]   				= WordpieceTokenizer(vocab=__UpperCamelCase       ,			unk_token='[UNK]'						)

									self.assertListEqual(tokenizer.tokenize(''						)       ,			[]						)

									self.assertListEqual(tokenizer.tokenize('unwanted running'						)       ,			['un', '##want', '##ed', 'runn', '##ing']						)

									self.assertListEqual(tokenizer.tokenize('unwantedX running'						)       ,			['[UNK]', 'runn', '##ing']						)




					def      __a     (  self						)	->    int:



									'''simple docstring'''







									self.assertTrue(_is_whitespace(' '						)						)
									self.assertTrue(_is_whitespace('\t'						)						)
									self.assertTrue(_is_whitespace('\r'						)						)
									self.assertTrue(_is_whitespace('\n'						)						)
									self.assertTrue(_is_whitespace('\u00A0'						)						)

									self.assertFalse(_is_whitespace('A'						)						)
									self.assertFalse(_is_whitespace('-'						)						)




					def      __a     (  self						)	->    List[Any]:



									'''simple docstring'''







									self.assertTrue(_is_control('\u0005'						)						)

									self.assertFalse(_is_control('A'						)						)
									self.assertFalse(_is_control(' '						)						)
									self.assertFalse(_is_control('\t'						)						)
									self.assertFalse(_is_control('\r'						)						)




					def      __a     (  self						)	->    Optional[Any]:



									'''simple docstring'''







									self.assertTrue(_is_punctuation('-'						)						)
									self.assertTrue(_is_punctuation('$'						)						)
									self.assertTrue(_is_punctuation('`'						)						)
									self.assertTrue(_is_punctuation('.'						)						)

									self.assertFalse(_is_punctuation('A'						)						)
									self.assertFalse(_is_punctuation(' '						)						)




					def      __a     (  self						)	->    Optional[int]:



									'''simple docstring'''







									snake_case__   :      List[str]   				= self.get_tokenizer()

									# Example taken from the issue https://github.com/huggingface/tokenizers/issues/340
									self.assertListEqual([tokenizer.tokenize(__UpperCamelCase						) for t in ['Test', '\xad', 'test']]       ,			[['[UNK]'], [], ['[UNK]']]						)

									if self.test_rust_tokenizer:
													snake_case__   :      int   				= self.get_rust_tokenizer()
													self.assertListEqual(
													    [rust_tokenizer.tokenize(__UpperCamelCase						) for t in ['Test', '\xad', 'test']]       ,			[['[UNK]'], [], ['[UNK]']]						)




					@slow
					def      __a     (  self						)	->    Tuple:



									'''simple docstring'''







									snake_case__   :      Any   				= self.tokenizer_class.from_pretrained('bert-base-uncased'						)

									snake_case__   :      Optional[int]   				= tokenizer.encode('sequence builders'       ,			add_special_tokens=__UpperCamelCase						)
									snake_case__   :      Optional[int]   				= tokenizer.encode('multi-sequence build'       ,			add_special_tokens=__UpperCamelCase						)

									snake_case__   :      str   				= tokenizer.build_inputs_with_special_tokens(__UpperCamelCase						)
									snake_case__   :      Tuple   				= tokenizer.build_inputs_with_special_tokens(__UpperCamelCase       ,			__UpperCamelCase						)

									assert encoded_sentence == [101] + text + [102]
									assert encoded_pair == [101] + text + [102] + text_a + [102]




					def      __a     (  self						)	->    Dict:



									'''simple docstring'''







									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""						):
																	snake_case__   :      Union[str, Any]   				= self.rust_tokenizer_class.from_pretrained(__UpperCamelCase       ,			**__UpperCamelCase						)

																	snake_case__   :      int   				= F"""A, naïve {tokenizer_r.mask_token} AllenNLP sentence."""
																	snake_case__   :      Optional[Any]   				= tokenizer_r.encode_plus(
																	    __UpperCamelCase       ,			return_attention_mask=__UpperCamelCase       ,			return_token_type_ids=__UpperCamelCase       ,			return_offsets_mapping=__UpperCamelCase       ,			add_special_tokens=__UpperCamelCase       ,			)

																	snake_case__   :      List[str]   				= tokenizer_r.do_lower_case if hasattr(__UpperCamelCase       ,			'do_lower_case'						) else False
																	snake_case__   :      Union[str, Any]   				= (
																	    [
																	        ((0, 0), tokenizer_r.cls_token),
																	        ((0, 1), 'A'),
																	        ((1, 2), ','),
																	        ((3, 5), 'na'),
																	        ((5, 6), '##ï'),
																	        ((6, 8), '##ve'),
																	        ((9, 15), tokenizer_r.mask_token),
																	        ((16, 21), 'Allen'),
																	        ((21, 23), '##NL'),
																	        ((23, 24), '##P'),
																	        ((25, 33), 'sentence'),
																	        ((33, 34), '.'),
																	        ((0, 0), tokenizer_r.sep_token),
																	    ]
																	    if not do_lower_case
																	    else [
																	        ((0, 0), tokenizer_r.cls_token),
																	        ((0, 1), 'a'),
																	        ((1, 2), ','),
																	        ((3, 8), 'naive'),
																	        ((9, 15), tokenizer_r.mask_token),
																	        ((16, 21), 'allen'),
																	        ((21, 23), '##nl'),
																	        ((23, 24), '##p'),
																	        ((25, 33), 'sentence'),
																	        ((33, 34), '.'),
																	        ((0, 0), tokenizer_r.sep_token),
																	    ]
																	)

																	self.assertEqual(
																	    [e[1] for e in expected_results]       ,			tokenizer_r.convert_ids_to_tokens(tokens['input_ids']						)						)
																	self.assertEqual([e[0] for e in expected_results]       ,			tokens['offset_mapping']						)




					@slow
					def      __a     (  self						)	->    Tuple:



									'''simple docstring'''







									for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
													with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""						):
																	snake_case__   :      Dict   				= self.rust_tokenizer_class.from_pretrained(__UpperCamelCase       ,			**__UpperCamelCase						)
																	snake_case__   :      Optional[Any]   				= self.tokenizer_class.from_pretrained(__UpperCamelCase       ,			**__UpperCamelCase						)
																	snake_case__   :      int   				= [['Hello world!', 'Nice to meet you!'], ['The cute cat.', 'The adorable dog.']]

																	snake_case__   :      Optional[int]   				= tokenizer_r.batch_encode_candidates(__UpperCamelCase       ,			max_length=10       ,			return_tensors='np'						)
																	snake_case__   :      Tuple   				= tokenizer_p.batch_encode_candidates(__UpperCamelCase       ,			max_length=10       ,			return_tensors='np'						)

																	snake_case__   :      Optional[int]   				= (2, 2, 10)

																	self.assertEqual(encoded_sentence_r['input_ids'].shape       ,			__UpperCamelCase						)
																	self.assertEqual(encoded_sentence_r['attention_mask'].shape       ,			__UpperCamelCase						)
																	self.assertEqual(encoded_sentence_r['token_type_ids'].shape       ,			__UpperCamelCase						)

																	self.assertEqual(encoded_sentence_p['input_ids'].shape       ,			__UpperCamelCase						)
																	self.assertEqual(encoded_sentence_p['attention_mask'].shape       ,			__UpperCamelCase						)
																	self.assertEqual(encoded_sentence_p['token_type_ids'].shape       ,			__UpperCamelCase						)


