



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


a_       :str				  =				1_000




class  snake_case__						:






     """simple docstring"""


     def __init__(	self  :  str,			_snake_case  :  List[Any],			_snake_case  :  List[str]=1.2,			_snake_case  :  int="g",			_snake_case  :  Any=0.5,			_snake_case  :  List[Any]="-",			_snake_case  :  Optional[int]="test_out.jpg",			_snake_case  :  Optional[Any]=True,			_snake_case  :  Union[str, Any]=False,			_snake_case  :  Any=None,			_snake_case  :  Any=None,			_snake_case  :  List[Any]=0.7,			)       ->Dict:

            if isinstance(snake_case_,			torch.Tensor ):
                   snake_case__							:     Union[str, Any]            =     img.numpy().astype('np.uint8' )
            if isinstance(snake_case_,			snake_case_ ):
                   snake_case__							:     str            =     img_tensorize(snake_case_ )
            assert isinstance(snake_case_,			np.ndarray )

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

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






     def        lowercase_       (	self  :  Dict,			_snake_case  :  Optional[Any],			_snake_case  :  Optional[Any]=None )       ->Optional[int]:

            if color is None:
                   snake_case__							:     Union[str, Any]            =     self.edgecolor
            (snake_case__)							:     int            =     box
            snake_case__							:     Any            =     xa - xa
            snake_case__							:     Any            =     ya - ya
            self.ax.add_patch(
                mpl.patches.Rectangle(
                    (xa, ya),			snake_case_,			snake_case_,			fill=snake_case_,			edgecolor=snake_case_,			linewidth=self.font_size // 3,			alpha=self.alpha,			linestyle=self.linestyle,			) )






     def        lowercase_       (	self  :  List[str],			_snake_case  :  Union[str, Any],			_snake_case  :  Tuple=None,			_snake_case  :  Dict=None,			_snake_case  :  Union[str, Any]=None,			_snake_case  :  Union[str, Any]=None )       ->Union[str, Any]:

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

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






     def        lowercase_       (	self  :  Optional[int],			_snake_case  :  Tuple,			_snake_case  :  Dict,			_snake_case  :  Any )       ->Dict:
            snake_case__							:     Dict            =     box
            snake_case__							:     Dict            =     (xa, ya)
            snake_case__							:     List[str]            =     (ya - ya) * (xa - xa)
            snake_case__							:     List[Any]            =     _SMALL_OBJ * self.scale
            if instance_area < small or ya - ya < 4_0 * self.scale:
                   if ya >= self.height - 5:
                          snake_case__							:     List[str]            =     (xa, ya)
                   else:
                          snake_case__							:     Tuple            =     (xa, ya)

            snake_case__							:     List[Any]            =     (ya - ya) / np.sqrt(self.height * self.width )
            snake_case__							:     Optional[int]            =     self._change_color_brightness(snake_case_,			brightness_factor=0.7 )
            snake_case__							:     Optional[Any]            =     np.clip((height_ratio - 0.0_2) / 0.0_8 + 1,			1.2,			2 )
            font_size *= 0.7_5 * self.font_size

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






     def        lowercase_       (	self  :  Optional[Any],			_snake_case  :  List[Any],			_snake_case  :  Optional[int],			_snake_case  :  str="g",			_snake_case  :  List[str]="left",			)       ->Optional[Any]:
            snake_case__							:     Any            =     0
            snake_case__							:     Optional[Any]            =     self.font_size
            snake_case__							:     Any            =     np.maximum(list(mplc.to_rgb(snake_case_ ) ),			0.2 )
            snake_case__							:     Tuple            =     max(0.8,			np.max(snake_case_ ) )
            snake_case__							:     Union[str, Any]            =     {
                'facecolor': 'black',
                'alpha': self.alpha,
                'pad': self.pad,
                'edgecolor': 'none',
            }
            snake_case__							:     Tuple            =     position
            self.ax.text(
                snake_case_,			snake_case_,			snake_case_,			size=font_size * self.scale,			family='sans-serif',			bbox=snake_case_,			verticalalignment='top',			horizontalalignment=snake_case_,			color=snake_case_,			zorder=1_0,			rotation=snake_case_,			)






     def        lowercase_       (	self  :  List[Any],			_snake_case  :  Optional[int]=None )       ->Optional[Any]:

            if saveas is None:
                   snake_case__							:     Tuple            =     self.saveas
            if saveas.lower().endswith('.jpg' ) or saveas.lower().endswith('.png' ):
                   cva.imwrite(
                       snake_case_,			self._get_buffer()[:, :, ::-1],			)
            else:
                   self.fig.savefig(snake_case_ )






     def        lowercase_       (	self  :  Dict,			_snake_case  :  Union[str, Any],			_snake_case  :  Dict,			_snake_case  :  List[str],			_snake_case  :  str )       ->Union[str, Any]:
            snake_case__							:     Tuple            =     [self.idaobj[i] for i in classes]
            snake_case__							:     Union[str, Any]            =     [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(snake_case_,			snake_case_,			snake_case_,			snake_case_ )
            ]
            return labels






     def        lowercase_       (	self  :  Any,			_snake_case  :  Optional[Any],			_snake_case  :  Any )       ->Optional[int]:
            snake_case__							:     Optional[int]            =     [self.idaobj[i] for i in classes]
            if scores is not None:
                   if labels is None:
                          snake_case__							:     Dict            =     ['{:.0f}%'.format(s * 1_0_0 ) for s in scores]
                   else:
                          snake_case__							:     int            =     ['{} {:.0f}%'.format(snake_case_,			s * 1_0_0 ) for li, s in zip(snake_case_,			snake_case_ )]
            return labels






     def        lowercase_       (	self  :  List[str],			_snake_case  :  Dict=2_5_5 )       ->Tuple:
            snake_case__							:     Tuple            =     np.random.randint(0,			len(_COLORS ) )
            snake_case__							:     Optional[int]            =     _COLORS[idx] * maximum
            if not self.rgb:
                   snake_case__							:     List[str]            =     ret[::-1]
            return ret






     def        lowercase_       (	self  :  Dict )       ->Tuple:

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

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

            try:
                   import numexpr as ne  # fuse them with numexpr

                   snake_case__							:     Optional[int]            =     ne.evaluate('img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)' )
            except ImportError:
                   snake_case__							:     str            =     alpha.astype('float32' ) / 2_5_5.0
                   snake_case__							:     Dict            =     img * (1 - alpha) + rgb * alpha

            return visualized_image.astype('uint8' )






     def        lowercase_       (	self  :  List[Any],			_snake_case  :  Any,			_snake_case  :  Tuple )       ->List[Any]:
            assert brightness_factor >= -1.0 and brightness_factor <= 1.0
            snake_case__							:     Union[str, Any]            =     mplc.to_rgb(snake_case_ )
            snake_case__							:     Tuple            =     colorsys.rgb_to_hls(*mplc.to_rgb(snake_case_ ) )
            snake_case__							:     int            =     polygon_color[1] + (brightness_factor * polygon_color[1])
            snake_case__							:     Optional[int]            =     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__							:     List[str]            =     colorsys.hls_to_rgb(polygon_color[0],			snake_case_,			polygon_color[2] )
            return modified_color


a_       :Any				  =				(
    np.array(
        [
            0.0_00,
            0.4_47,
            0.7_41,
            0.8_50,
            0.3_25,
            0.0_98,
            0.9_29,
            0.6_94,
            0.1_25,
            0.4_94,
            0.1_84,
            0.5_56,
            0.4_66,
            0.6_74,
            0.1_88,
            0.3_01,
            0.7_45,
            0.9_33,
            0.6_35,
            0.0_78,
            0.1_84,
            0.3_00,
            0.3_00,
            0.3_00,
            0.6_00,
            0.6_00,
            0.6_00,
            1.0_00,
            0.0_00,
            0.0_00,
            1.0_00,
            0.5_00,
            0.0_00,
            0.7_49,
            0.7_49,
            0.0_00,
            0.0_00,
            1.0_00,
            0.0_00,
            0.0_00,
            0.0_00,
            1.0_00,
            0.6_67,
            0.0_00,
            1.0_00,
            0.3_33,
            0.3_33,
            0.0_00,
            0.3_33,
            0.6_67,
            0.0_00,
            0.3_33,
            1.0_00,
            0.0_00,
            0.6_67,
            0.3_33,
            0.0_00,
            0.6_67,
            0.6_67,
            0.0_00,
            0.6_67,
            1.0_00,
            0.0_00,
            1.0_00,
            0.3_33,
            0.0_00,
            1.0_00,
            0.6_67,
            0.0_00,
            1.0_00,
            1.0_00,
            0.0_00,
            0.0_00,
            0.3_33,
            0.5_00,
            0.0_00,
            0.6_67,
            0.5_00,
            0.0_00,
            1.0_00,
            0.5_00,
            0.3_33,
            0.0_00,
            0.5_00,
            0.3_33,
            0.3_33,
            0.5_00,
            0.3_33,
            0.6_67,
            0.5_00,
            0.3_33,
            1.0_00,
            0.5_00,
            0.6_67,
            0.0_00,
            0.5_00,
            0.6_67,
            0.3_33,
            0.5_00,
            0.6_67,
            0.6_67,
            0.5_00,
            0.6_67,
            1.0_00,
            0.5_00,
            1.0_00,
            0.0_00,
            0.5_00,
            1.0_00,
            0.3_33,
            0.5_00,
            1.0_00,
            0.6_67,
            0.5_00,
            1.0_00,
            1.0_00,
            0.5_00,
            0.0_00,
            0.3_33,
            1.0_00,
            0.0_00,
            0.6_67,
            1.0_00,
            0.0_00,
            1.0_00,
            1.0_00,
            0.3_33,
            0.0_00,
            1.0_00,
            0.3_33,
            0.3_33,
            1.0_00,
            0.3_33,
            0.6_67,
            1.0_00,
            0.3_33,
            1.0_00,
            1.0_00,
            0.6_67,
            0.0_00,
            1.0_00,
            0.6_67,
            0.3_33,
            1.0_00,
            0.6_67,
            0.6_67,
            1.0_00,
            0.6_67,
            1.0_00,
            1.0_00,
            1.0_00,
            0.0_00,
            1.0_00,
            1.0_00,
            0.3_33,
            1.0_00,
            1.0_00,
            0.6_67,
            1.0_00,
            0.3_33,
            0.0_00,
            0.0_00,
            0.5_00,
            0.0_00,
            0.0_00,
            0.6_67,
            0.0_00,
            0.0_00,
            0.8_33,
            0.0_00,
            0.0_00,
            1.0_00,
            0.0_00,
            0.0_00,
            0.0_00,
            0.1_67,
            0.0_00,
            0.0_00,
            0.3_33,
            0.0_00,
            0.0_00,
            0.5_00,
            0.0_00,
            0.0_00,
            0.6_67,
            0.0_00,
            0.0_00,
            0.8_33,
            0.0_00,
            0.0_00,
            1.0_00,
            0.0_00,
            0.0_00,
            0.0_00,
            0.1_67,
            0.0_00,
            0.0_00,
            0.3_33,
            0.0_00,
            0.0_00,
            0.5_00,
            0.0_00,
            0.0_00,
            0.6_67,
            0.0_00,
            0.0_00,
            0.8_33,
            0.0_00,
            0.0_00,
            1.0_00,
            0.0_00,
            0.0_00,
            0.0_00,
            0.1_43,
            0.1_43,
            0.1_43,
            0.8_57,
            0.8_57,
            0.8_57,
            1.0_00,
            1.0_00,
            1.0_00,
        ]
    )
    .astype(np.floataa)
    .reshape(-1, 3)
)











import json
import os
import re
import unicodedata
from typing import Optional, Tuple

from ...tokenization_utils import PreTrainedTokenizer, _is_control, _is_punctuation, _is_whitespace
from ...utils import logging


a_       :Tuple				  =				logging.get_logger(__name__)

a_       :Dict				  =				{
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
}

a_       :List[str]				  =				{
    "vocab_file": {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/vocab.json"},
    "merges_file": {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/merges.txt"},
}

a_       :Union[str, Any]				  =				{
    "openai-gpt": 512,
}
def 	lowercase_							(A			:			Dict				):
       snake_case__							:     Optional[int]            =     text.strip()
       if not text:
              return []
       snake_case__							:     List[str]            =     text.split()
       return tokens




class  snake_case__						(	lowerCAmelCase_					):






     """simple docstring"""


     def __init__(	self  :  List[Any],			_snake_case  :  Any=True,			_snake_case  :  Optional[Any]=None,			_snake_case  :  Dict=True,			_snake_case  :  List[str]=None,			_snake_case  :  List[Any]=True,			)       ->Any:
            if never_split is None:
                   snake_case__							:     int            =     []
            snake_case__							:     Any            =     do_lower_case
            snake_case__							:     Union[str, Any]            =     set(_snake_case )
            snake_case__							:     Union[str, Any]            =     tokenize_chinese_chars
            snake_case__							:     str            =     strip_accents
            snake_case__							:     Optional[Any]            =     do_split_on_punc






     def        lowercase_       (	self  :  Dict,			_snake_case  :  Optional[int],			_snake_case  :  List[Any]=None )       ->List[str]:
            snake_case__							:     Tuple            =     self.never_split.union(set(_snake_case ) ) if never_split else self.never_split
            snake_case__							:     Optional[int]            =     self._clean_text(_snake_case )

            # This was added on November 1st, 2018 for the multilingual and Chinese
            # models. This is also applied to the English models now, but it doesn't
            # matter since the English models were not trained on any Chinese data
            # and generally don't have any Chinese data in them (there are Chinese
            # characters in the vocabulary because Wikipedia does have some Chinese
            # words in the English Wikipedia.).
            if self.tokenize_chinese_chars:
                   snake_case__							:     List[str]            =     self._tokenize_chinese_chars(_snake_case )
            # prevents treating the same character with different unicode codepoints as different characters
            snake_case__							:     Optional[int]            =     unicodedata.normalize('NFC',			_snake_case )
            snake_case__							:     str            =     whitespace_tokenize(_snake_case )
            snake_case__							:     Optional[Any]            =     []
            for token in orig_tokens:
                   if token not in never_split:
                          if self.do_lower_case:
                                 snake_case__							:     int            =     token.lower()
                                 if self.strip_accents is not False:
                                        snake_case__							:     Any            =     self._run_strip_accents(_snake_case )
                          elif self.strip_accents:
                                 snake_case__							:     Optional[Any]            =     self._run_strip_accents(_snake_case )
                   split_tokens.extend(self._run_split_on_punc(_snake_case,			_snake_case ) )

            snake_case__							:     Dict            =     whitespace_tokenize(' '.join(_snake_case ) )
            return output_tokens






     def        lowercase_       (	self  :  int,			_snake_case  :  List[str] )       ->int:
            snake_case__							:     Dict            =     unicodedata.normalize('NFD',			_snake_case )
            snake_case__							:     Dict            =     []
            for char in text:
                   snake_case__							:     List[Any]            =     unicodedata.category(_snake_case )
                   if cat == "Mn":
                          continue
                   output.append(_snake_case )
            return "".join(_snake_case )






     def        lowercase_       (	self  :  str,			_snake_case  :  Dict,			_snake_case  :  Optional[int]=None )       ->Dict:
            if not self.do_split_on_punc or (never_split is not None and text in never_split):
                   return [text]
            snake_case__							:     Dict            =     list(_snake_case )
            snake_case__							:     List[str]            =     0
            snake_case__							:     Union[str, Any]            =     True
            snake_case__							:     Tuple            =     []
            while i < len(_snake_case ):
                   snake_case__							:     Any            =     chars[i]
                   if _is_punctuation(_snake_case ):
                          output.append([char] )
                          snake_case__							:     int            =     True
                   else:
                          if start_new_word:
                                 output.append([] )
                          snake_case__							:     Union[str, Any]            =     False
                          output[-1].append(_snake_case )
                   i += 1

            return ["".join(_snake_case ) for x in output]






     def        lowercase_       (	self  :  Any,			_snake_case  :  int )       ->Any:
            snake_case__							:     Dict            =     []
            for char in text:
                   snake_case__							:     Union[str, Any]            =     ord(_snake_case )
                   if self._is_chinese_char(_snake_case ):
                          output.append(' ' )
                          output.append(_snake_case )
                          output.append(' ' )
                   else:
                          output.append(_snake_case )
            return "".join(_snake_case )






     def        lowercase_       (	self  :  Any,			_snake_case  :  List[str] )       ->Dict:
            # This defines a "chinese character" as anything in the CJK Unicode block:
            #   https://en.wikipedia.org/wiki/CJK_Unified_Ideographs_(Unicode_block)
            #
            # Note that the CJK Unicode block is NOT all Japanese and Korean characters,
            # despite its name. The modern Korean Hangul alphabet is a different block,
            # as is Japanese Hiragana and Katakana. Those alphabets are used to write
            # space-separated words, so they are not treated specially and handled
            # like the all of the other languages.
            if (
                (cp >= 0X4_E_0_0 and cp <= 0X9_F_F_F)
                or (cp >= 0X3_4_0_0 and cp <= 0X4_D_B_F)  #
                or (cp >= 0X2_0_0_0_0 and cp <= 0X2_A_6_D_F)  #
                or (cp >= 0X2_A_7_0_0 and cp <= 0X2_B_7_3_F)  #
                or (cp >= 0X2_B_7_4_0 and cp <= 0X2_B_8_1_F)  #
                or (cp >= 0X2_B_8_2_0 and cp <= 0X2_C_E_A_F)  #
                or (cp >= 0XF_9_0_0 and cp <= 0XF_A_F_F)
                or (cp >= 0X2_F_8_0_0 and cp <= 0X2_F_A_1_F)  #
            ):  #
                   return True

            return False






     def        lowercase_       (	self  :  List[str],			_snake_case  :  str )       ->Any:
            snake_case__							:     Optional[int]            =     []
            for char in text:
                   snake_case__							:     Any            =     ord(_snake_case )
                   if cp == 0 or cp == 0XF_F_F_D or _is_control(_snake_case ):
                          continue
                   if _is_whitespace(_snake_case ):
                          output.append(' ' )
                   else:
                          output.append(_snake_case )
            return "".join(_snake_case )


def 	lowercase_							(A			:			Dict				):
       snake_case__							:     Dict            =     set()
       snake_case__							:     List[str]            =     word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)				)
              snake_case__							:     str            =     char
       return pairs
def 	lowercase_							(A			:			int				):
       snake_case__							:     Union[str, Any]            =     text.replace('—'		, '-'				)
       snake_case__							:     List[str]            =     text.replace('–'		, '-'				)
       snake_case__							:     List[str]            =     text.replace('―'		, '-'				)
       snake_case__							:     Any            =     text.replace('…'		, '...'				)
       snake_case__							:     Union[str, Any]            =     text.replace('´'		, '\''				)
       snake_case__							:     str            =     re.sub(r'(-+|~+|!+|"+|;+|\?+|\++|,+|\)+|\(+|\\+|\/+|\*+|\[+|\]+|}+|{+|\|+|_+)'		, r' \1 '		, A				)
       snake_case__							:     int            =     re.sub(r'\s*\n\s*'		, ' \n '		, A				)
       snake_case__							:     Dict            =     re.sub(r'[^\S\n]+'		, ' '		, A				)
       return text.strip()





class  snake_case__						(	lowerCAmelCase_					):






     """simple docstring"""


     _SCREAMING_SNAKE_CASE            =     VOCAB_FILES_NAMES
     _SCREAMING_SNAKE_CASE            =     PRETRAINED_VOCAB_FILES_MAP
     _SCREAMING_SNAKE_CASE            =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _SCREAMING_SNAKE_CASE            =     ["""input_ids""", """attention_mask"""]






     def __init__(	self  :  Optional[Any],			_snake_case  :  Union[str, Any],			_snake_case  :  Tuple,			_snake_case  :  Optional[int]="<unk>",			**_snake_case  :  int )       ->Optional[Any]:
            super().__init__(unk_token=_snake_case,			**_snake_case )

            try:
                   import ftfy
                   from spacy.lang.en import English

                   snake_case__							:     List[Any]            =     English()
                   snake_case__							:     List[Any]            =     _nlp.tokenizer
                   snake_case__							:     List[Any]            =     ftfy.fix_text
            except ImportError:
                   logger.warning('ftfy or spacy is not installed using BERT BasicTokenizer instead of SpaCy & ftfy.' )
                   snake_case__							:     Union[str, Any]            =     BasicTokenizer(do_lower_case=_snake_case )
                   snake_case__							:     Optional[int]            =     None

            with open(_snake_case,			encoding='utf-8' ) as vocab_handle:
                   snake_case__							:     Union[str, Any]            =     json.load(_snake_case )
            snake_case__							:     List[str]            =     {v: k for k, v in self.encoder.items()}
            with open(_snake_case,			encoding='utf-8' ) as merges_handle:
                   snake_case__							:     int            =     merges_handle.read().split('\n' )[1:-1]
            snake_case__							:     Dict            =     [tuple(merge.split() ) for merge in merges]
            snake_case__							:     Optional[Any]            =     dict(zip(_snake_case,			range(len(_snake_case ) ) ) )
            snake_case__							:     int            =     {}






     @property
     def        lowercase_       (	self  :  Any )       ->str:
            return True






     @property
     def        lowercase_       (	self  :  Dict )       ->str:
            return len(self.encoder )






     def        lowercase_       (	self  :  Dict )       ->Optional[int]:
            return dict(self.encoder,			**self.added_tokens_encoder )






     def        lowercase_       (	self  :  List[Any],			_snake_case  :  Union[str, Any] )       ->Any:
            snake_case__							:     Tuple            =     tuple(token[:-1] ) + (token[-1] + '</w>',)
            if token in self.cache:
                   return self.cache[token]
            snake_case__							:     List[Any]            =     get_pairs(_snake_case )

            if not pairs:
                   return token + "</w>"

            while True:
                   snake_case__							:     Optional[int]            =     min(_snake_case,			key=lambda _snake_case : self.bpe_ranks.get(_snake_case,			float('inf' ) ) )
                   if bigram not in self.bpe_ranks:
                          break
                   snake_case__     ,    snake_case__							:     Tuple            =     bigram
                   snake_case__							:     str            =     []
                   snake_case__							:     int            =     0
                   while i < len(_snake_case ):
                          try:
                                 snake_case__							:     List[str]            =     word.index(_snake_case,			_snake_case )
                          except ValueError:
                                 new_word.extend(word[i:] )
                                 break
                          else:
                                 new_word.extend(word[i:j] )
                                 snake_case__							:     Tuple            =     j

                          if word[i] == first and i < len(_snake_case ) - 1 and word[i + 1] == second:
                                 new_word.append(first + second )
                                 i += 2
                          else:
                                 new_word.append(word[i] )
                                 i += 1
                   snake_case__							:     Optional[int]            =     tuple(_snake_case )
                   snake_case__							:     Union[str, Any]            =     new_word
                   if len(_snake_case ) == 1:
                          break
                   else:
                          snake_case__							:     List[Any]            =     get_pairs(_snake_case )
            snake_case__							:     List[Any]            =     ' '.join(_snake_case )
            if word == "\n  </w>":
                   snake_case__							:     Any            =     '\n</w>'
            snake_case__							:     Optional[int]            =     word
            return word






     def        lowercase_       (	self  :  Union[str, Any],			_snake_case  :  Optional[int] )       ->Dict:
            snake_case__							:     Optional[Any]            =     []
            if self.fix_text is None:
                   # Using BERT's BasicTokenizer
                   snake_case__							:     List[str]            =     self.nlp.tokenize(_snake_case )
                   for token in text:
                          split_tokens.extend(list(self.bpe(_snake_case ).split(' ' ) ) )
            else:
                   # Using SpaCy & ftfy (original tokenization process of OpenAI GPT)
                   snake_case__							:     Optional[Any]            =     self.nlp(text_standardize(self.fix_text(_snake_case ) ) )
                   for token in text:
                          split_tokens.extend(list(self.bpe(token.text.lower() ).split(' ' ) ) )
            return split_tokens






     def        lowercase_       (	self  :  Tuple,			_snake_case  :  Union[str, Any] )       ->List[Any]:
            return self.encoder.get(_snake_case,			self.encoder.get(self.unk_token ) )






     def        lowercase_       (	self  :  Tuple,			_snake_case  :  Dict )       ->Any:
            return self.decoder.get(_snake_case,			self.unk_token )






     def        lowercase_       (	self  :  str,			_snake_case  :  List[Any] )       ->List[Any]:
            snake_case__							:     Dict            =     ''.join(_snake_case ).replace('</w>',			' ' ).strip()
            return out_string






     def        lowercase_       (	self  :  Dict,			_snake_case  :  str,			_snake_case  :  Optional[str] = None )       ->Tuple[str]:
            if not os.path.isdir(_snake_case ):
                   logger.error(F'''Vocabulary path ({save_directory}) should be a directory''' )
                   return
            snake_case__							:     Union[str, Any]            =     os.path.join(
                _snake_case,			(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] )
            snake_case__							:     List[Any]            =     os.path.join(
                _snake_case,			(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['merges_file'] )

            with open(_snake_case,			'w',			encoding='utf-8' ) as f:
                   f.write(json.dumps(self.encoder,			indent=2,			sort_keys=_snake_case,			ensure_ascii=_snake_case ) + '\n' )

            snake_case__							:     Union[str, Any]            =     0
            with open(_snake_case,			'w',			encoding='utf-8' ) as writer:
                   writer.write('#version: 0.2\n' )
                   for bpe_tokens, token_index in sorted(self.bpe_ranks.items(),			key=lambda _snake_case : kv[1] ):
                          if index != token_index:
                                 logger.warning(
                                     F'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
                                     ' Please check that the tokenizer is not corrupted!' )
                                 snake_case__							:     Dict            =     token_index
                          writer.write(' '.join(_snake_case ) + '\n' )
                          index += 1

            return vocab_file, merge_file






