





'''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


A :			Tuple							   =      1_000







class       lowerCamelCase       :


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





											'''simple docstring'''





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

											_snake_case       ,    _snake_case: Dict	       =		img.shape[1], img.shape[0]
											_snake_case: List[Any]	       =		mplfigure.Figure(frameon=__snake_case							)
											_snake_case: Optional[int]	       =		fig.get_dpi()
											_snake_case: Optional[Any]	       =		(width * scale + 1e-2) / dpi
											_snake_case: str	       =		(height * scale + 1e-2) / dpi
											fig.set_size_inches(__snake_case							,  __snake_case							)
											_snake_case: List[str]	       =		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: int	       =		saveas
											_snake_case: List[Any]	       =		rgb
											_snake_case: List[Any]	       =		pynb
											_snake_case: Tuple	       =		img
											_snake_case: Optional[Any]	       =		edgecolor
											_snake_case: Dict	       =		0.5
											_snake_case: int	       =		linestyle
											_snake_case: Dict	       =		int(np.sqrt(min(__snake_case							,  __snake_case							)							) * scale // 3							)
											_snake_case: Union[str, Any]	       =		width
											_snake_case: int	       =		height
											_snake_case: Optional[Any]	       =		scale
											_snake_case: Optional[int]	       =		fig
											_snake_case: str	       =		ax
											_snake_case: int	       =		pad
											_snake_case: Tuple	       =		idaobj
											_snake_case: Dict	       =		idaattr
											_snake_case: Tuple	       =		FigureCanvasAgg(__snake_case							)


					def  SCREAMING_SNAKE_CASE_		(       self						:	Tuple							,  __snake_case						:	int							,  __snake_case						:	List[str]=None							):





											'''simple docstring'''





											if color is None:
																	_snake_case: Union[str, Any]	       =		self.edgecolor
											((_snake_case)       ,    (_snake_case)       ,    (_snake_case)       ,    (_snake_case)): List[Any]	       =		box
											_snake_case: Optional[int]	       =		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  SCREAMING_SNAKE_CASE_		(       self						:	List[str]							,  __snake_case						:	List[Any]							,  __snake_case						:	Optional[int]=None							,  __snake_case						:	Dict=None							,  __snake_case						:	Any=None							,  __snake_case						:	Union[str, Any]=None							):





											'''simple docstring'''





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

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


					def  SCREAMING_SNAKE_CASE_		(       self						:	Any							,  __snake_case						:	Optional[int]							,  __snake_case						:	List[str]							,  __snake_case						:	Any							):





											'''simple docstring'''





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

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

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


					def  SCREAMING_SNAKE_CASE_		(       self						:	Any							,  __snake_case						:	str							,  __snake_case						:	Optional[int]							,  __snake_case						:	Tuple="g"							,  __snake_case						:	Optional[int]="left"							,  ):





											'''simple docstring'''





											_snake_case: Any	       =		0
											_snake_case: Optional[int]	       =		self.font_size
											_snake_case: Union[str, Any]	       =		np.maximum(list(mplc.to_rgb(__snake_case							)							)							,  0.2							)
											_snake_case: Optional[int]	       =		max(0.8							,  np.max(__snake_case							)							)
											_snake_case: str	       =		{
											    'facecolor': 'black',
											    'alpha': self.alpha,
											    'pad': self.pad,
											    'edgecolor': 'none',
											}
											_snake_case       ,    _snake_case: Optional[Any]	       =		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=10							,  rotation=__snake_case							,  )


					def  SCREAMING_SNAKE_CASE_		(       self						:	str							,  __snake_case						:	str=None							):





											'''simple docstring'''





											if saveas is None:
																	_snake_case: int	       =		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  SCREAMING_SNAKE_CASE_		(       self						:	Optional[int]							,  __snake_case						:	Any							,  __snake_case						:	int							,  __snake_case						:	List[str]							,  __snake_case						:	List[str]							):





											'''simple docstring'''





											_snake_case: Dict	       =		[self.idaobj[i] for i in classes]
											_snake_case: Dict	       =		[self.idaattr[i] for i in attr_classes]
											_snake_case: str	       =		[
											    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  SCREAMING_SNAKE_CASE_		(       self						:	Tuple							,  __snake_case						:	int							,  __snake_case						:	List[str]							):





											'''simple docstring'''





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


					def  SCREAMING_SNAKE_CASE_		(       self						:	Any							,  __snake_case						:	int=2_55							):





											'''simple docstring'''





											_snake_case: List[Any]	       =		np.random.randint(0							,  len(_COLORS							)							)
											_snake_case: str	       =		_COLORS[idx] * maximum
											if not self.rgb:
																	_snake_case: Any	       =		ret[::-1]
											return ret


					def  SCREAMING_SNAKE_CASE_		(       self						:	Optional[int]							):





											'''simple docstring'''





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

											_snake_case: Optional[Any]	       =		np.frombuffer(__snake_case							,  dtype='uint8'							)
											_snake_case: Union[str, Any]	       =		buffer.reshape(__snake_case							,  __snake_case							,  4							)
											_snake_case       ,    _snake_case: int	       =		np.split(__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: List[str]	       =		alpha.astype('float32'							) / 255.0
																	_snake_case: int	       =		img * (1 - alpha) + rgb * alpha

											return visualized_image.astype('uint8'							)




					def  SCREAMING_SNAKE_CASE_		(       self						:	str							,  __snake_case						:	Dict							,  __snake_case						:	Union[str, Any]							):





											'''simple docstring'''





											assert brightness_factor >= -1.0 and brightness_factor <= 1.0
											_snake_case: Any	       =		mplc.to_rgb(__snake_case							)
											_snake_case: Dict	       =		colorsys.rgb_to_hls(*mplc.to_rgb(__snake_case							)							)
											_snake_case: List[Any]	       =		polygon_color[1] + (brightness_factor * polygon_color[1])
											_snake_case: Dict	       =		0.0 if modified_lightness < 0.0 else modified_lightness
											_snake_case: str	       =		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 :			List[str]							   =      (
    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)
)












'''simple docstring'''






import json
import os
import re
import warnings
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union

import sentencepiece

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A :			Optional[Any]							   =      logging.get_logger(__name__)

A :			Optional[Any]							   =      {
    'source_spm': 'source.spm',
    'target_spm': 'target.spm',
    'vocab': 'vocab.json',
    'target_vocab_file': 'target_vocab.json',
    'tokenizer_config_file': 'tokenizer_config.json',
}

A :			Tuple							   =      {
    'source_spm': {
        'Helsinki-NLP/opus-mt-en-de': 'https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/source.spm'
    },
    'target_spm': {
        'Helsinki-NLP/opus-mt-en-de': 'https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/target.spm'
    },
    'vocab': {
        'Helsinki-NLP/opus-mt-en-de': 'https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/vocab.json'
    },
    'tokenizer_config_file': {
        'Helsinki-NLP/opus-mt-en-de': (
            'https://huggingface.co/Helsinki-NLP/opus-mt-en-de/resolve/main/tokenizer_config.json'
        )
    },
}

A :			Optional[int]							   =      {'Helsinki-NLP/opus-mt-en-de': 512}
A :			Any							   =      {}







class       lowerCamelCase       (    __UpperCAmelCase	):
					_SCREAMING_SNAKE_CASE				 =     VOCAB_FILES_NAMES
					_SCREAMING_SNAKE_CASE				 =     PRETRAINED_VOCAB_FILES_MAP
					_SCREAMING_SNAKE_CASE				 =     PRETRAINED_INIT_CONFIGURATION
					_SCREAMING_SNAKE_CASE				 =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					_SCREAMING_SNAKE_CASE				 =     ["input_ids", "attention_mask"]
					_SCREAMING_SNAKE_CASE				 =     re.compile(">>.+<<"	)  # type: re.Pattern


					def __init__(       self						:	Optional[Any]							,  __snake_case						:	Tuple							,  __snake_case						:	Optional[int]							,  __snake_case						:	Optional[Any]							,  __snake_case						:	List[Any]=None							,  __snake_case						:	int=None							,  __snake_case						:	Optional[Any]=None							,  __snake_case						:	Optional[int]="<unk>"							,  __snake_case						:	str="</s>"							,  __snake_case						:	Tuple="<pad>"							,  __snake_case						:	List[str]=5_12							,  __snake_case						:	Optional[Dict[str, Any]] = None							,  __snake_case						:	Union[str, Any]=False							,  **__snake_case						:	int							,  ):





											'''simple docstring'''





											_snake_case: List[str]	       =		{} if sp_model_kwargs is None else sp_model_kwargs

											super().__init__(
											    # bos_token=bos_token,  unused. Start decoding with config.decoder_start_token_id
											    source_lang=__snake_case							,  target_lang=__snake_case							,  unk_token=__snake_case							,  eos_token=__snake_case							,  pad_token=__snake_case							,  model_max_length=__snake_case							,  sp_model_kwargs=self.sp_model_kwargs							,  target_vocab_file=__snake_case							,  separate_vocabs=__snake_case							,  **__snake_case							,  )
											assert Path(__snake_case							).exists(), f'''cannot find spm source {source_spm}'''

											_snake_case: List[Any]	       =		separate_vocabs
											_snake_case: List[Any]	       =		load_json(__snake_case							)
											if self.unk_token not in self.encoder:
																	raise KeyError('<unk> token must be in vocab'							)
											assert self.pad_token in self.encoder

											if separate_vocabs:
																	_snake_case: List[str]	       =		load_json(__snake_case							)
																	_snake_case: Optional[int]	       =		{v: k for k, v in self.target_encoder.items()}
																	_snake_case: Tuple	       =		[]
											else:
																	_snake_case: Any	       =		{v: k for k, v in self.encoder.items()}
																	_snake_case: list	       =		[k for k in self.encoder if k.startswith('>>'							) and k.endswith('<<'							)]

											_snake_case: List[Any]	       =		source_lang
											_snake_case: List[str]	       =		target_lang
											_snake_case: List[str]	       =		[source_spm, target_spm]

											# load SentencePiece model for pre-processing
											_snake_case: Optional[Any]	       =		load_spm(__snake_case							,  self.sp_model_kwargs							)
											_snake_case: List[str]	       =		load_spm(__snake_case							,  self.sp_model_kwargs							)
											_snake_case: str	       =		self.spm_source
											_snake_case: int	       =		self.encoder

											# Multilingual target side: default to using first supported language code.

											self._setup_normalizer()


					def  SCREAMING_SNAKE_CASE_		(       self						:	str							):





											'''simple docstring'''





											try:
																	from sacremoses import MosesPunctNormalizer

																	_snake_case: List[Any]	       =		MosesPunctNormalizer(self.source_lang							).normalize
											except (ImportError, FileNotFoundError):
																	warnings.warn('Recommended: pip install sacremoses.'							)
																	_snake_case: List[Any]	       =		lambda __snake_case							: x


					def  SCREAMING_SNAKE_CASE_		(       self						:	Optional[int]							,  __snake_case						:	str							):





											'''simple docstring'''





											return self.punc_normalizer(__snake_case							) if x else ""


					def  SCREAMING_SNAKE_CASE_		(       self						:	Optional[int]							,  __snake_case						:	Tuple							):





											'''simple docstring'''





											return self.current_encoder.get(__snake_case							,  self.current_encoder[self.unk_token]							)


					def  SCREAMING_SNAKE_CASE_		(       self						:	List[str]							,  __snake_case						:	str							):





											'''simple docstring'''





											_snake_case: List[Any]	       =		self.language_code_re.match(__snake_case							)
											_snake_case: list	       =		[match.group(0							)] if match else []
											return code, self.language_code_re.sub(''							,  __snake_case							)


					def  SCREAMING_SNAKE_CASE_		(       self						:	Optional[int]							,  __snake_case						:	str							):





											'''simple docstring'''





											_snake_case       ,    _snake_case: Optional[Any]	       =		self.remove_language_code(__snake_case							)
											_snake_case: Union[str, Any]	       =		self.current_spm.encode(__snake_case							,  out_type=__snake_case							)
											return code + pieces


					def  SCREAMING_SNAKE_CASE_		(       self						:	Dict							,  __snake_case						:	int							):





											'''simple docstring'''





											return self.decoder.get(__snake_case							,  self.unk_token							)


					def  SCREAMING_SNAKE_CASE_		(       self						:	int							,  __snake_case						:	Tuple							,  **__snake_case						:	int							):





											'''simple docstring'''





											return super().batch_decode(__snake_case							,  **__snake_case							)


					def  SCREAMING_SNAKE_CASE_		(       self						:	Any							,  __snake_case						:	Any							,  **__snake_case						:	List[str]							):





											'''simple docstring'''





											return super().decode(__snake_case							,  **__snake_case							)


					def  SCREAMING_SNAKE_CASE_		(       self						:	int							,  __snake_case						:	List[str]							):





											'''simple docstring'''





											_snake_case: Optional[int]	       =		self.spm_source if self._decode_use_source_tokenizer else self.spm_target
											_snake_case: List[Any]	       =		[]
											_snake_case: Any	       =		''
											for token in tokens:
																	# make sure that special tokens are not decoded using sentencepiece model
																	if token in self.all_special_tokens:
																							out_string += sp_model.decode_pieces(__snake_case							) + token + " "
																							_snake_case: Any	       =		[]
																	else:
																							current_sub_tokens.append(__snake_case							)
											out_string += sp_model.decode_pieces(__snake_case							)
											return out_string.strip()


					def  SCREAMING_SNAKE_CASE_		(       self						:	Optional[Any]							,  __snake_case						:	Tuple							,  __snake_case						:	Union[str, Any]=None							):





											'''simple docstring'''





											if token_ids_a is None:
																	return token_ids_a + [self.eos_token_id]
											# We don't expect to process pairs, but leave the pair logic for API consistency
											return token_ids_a + token_ids_a + [self.eos_token_id]


					def  SCREAMING_SNAKE_CASE_		(       self						:	Optional[Any]							):





											'''simple docstring'''





											_snake_case: List[Any]	       =		self.spm_source
											_snake_case: List[str]	       =		self.encoder


					def  SCREAMING_SNAKE_CASE_		(       self						:	int							):





											'''simple docstring'''





											_snake_case: int	       =		self.spm_target
											if self.separate_vocabs:
																	_snake_case: Union[str, Any]	       =		self.target_encoder


					@property
					def  SCREAMING_SNAKE_CASE_		(       self						:	Optional[int]							):





											'''simple docstring'''





											return len(self.encoder							)


					def  SCREAMING_SNAKE_CASE_		(       self						:	Tuple							,  __snake_case						:	str							,  __snake_case						:	Optional[str] = None							):





											'''simple docstring'''





											if not os.path.isdir(__snake_case							):
																	logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''							)
																	return
											_snake_case: str	       =		[]

											if self.separate_vocabs:
																	_snake_case: Optional[int]	       =		os.path.join(
																	    __snake_case							,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab']							,  )
																	_snake_case: Optional[int]	       =		os.path.join(
																	    __snake_case							,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['target_vocab_file']							,  )
																	save_json(self.encoder							,  __snake_case							)
																	save_json(self.target_encoder							,  __snake_case							)
																	saved_files.append(__snake_case							)
																	saved_files.append(__snake_case							)
											else:
																	_snake_case: int	       =		os.path.join(
																	    __snake_case							,  (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab']							)
																	save_json(self.encoder							,  __snake_case							)
																	saved_files.append(__snake_case							)

											for spm_save_filename, spm_orig_path, spm_model in zip(
											    [VOCAB_FILES_NAMES['source_spm'], VOCAB_FILES_NAMES['target_spm']]							,  self.spm_files							,  [self.spm_source, self.spm_target]							,  ):
																	_snake_case: Any	       =		os.path.join(
																	    __snake_case							,  (filename_prefix + '-' if filename_prefix else '') + spm_save_filename							)
																	if os.path.abspath(__snake_case							) != os.path.abspath(__snake_case							) and os.path.isfile(__snake_case							):
																							copyfile(__snake_case							,  __snake_case							)
																							saved_files.append(__snake_case							)
																	elif not os.path.isfile(__snake_case							):
																							with open(__snake_case							,  'wb'							) as fi:
																													_snake_case: Any	       =		spm_model.serialized_model_proto()
																													fi.write(__snake_case							)
																							saved_files.append(__snake_case							)

											return tuple(__snake_case							)


					def  SCREAMING_SNAKE_CASE_		(       self						:	List[Any]							):





											'''simple docstring'''





											return self.get_src_vocab()


					def  SCREAMING_SNAKE_CASE_		(       self						:	Any							):





											'''simple docstring'''





											return dict(self.encoder							,  **self.added_tokens_encoder							)


					def  SCREAMING_SNAKE_CASE_		(       self						:	Dict							):





											'''simple docstring'''





											return dict(self.target_encoder							,  **self.added_tokens_decoder							)


					def __getstate__(       self						:	Union[str, Any]							):





											'''simple docstring'''





											_snake_case: str	       =		self.__dict__.copy()
											state.update(
											    {k: None for k in ['spm_source', 'spm_target', 'current_spm', 'punc_normalizer', 'target_vocab_file']}							)
											return state


					def __setstate__(       self						:	str							,  __snake_case						:	Dict							):





											'''simple docstring'''





											_snake_case: str	       =		d

											# for backward compatibility
											if not hasattr(self							,  'sp_model_kwargs'							):
																	_snake_case: List[Any]	       =		{}

											_snake_case       ,    _snake_case: Dict	       =		(load_spm(__snake_case							,  self.sp_model_kwargs							) for f in self.spm_files)
											_snake_case: str	       =		self.spm_source
											self._setup_normalizer()


					def  SCREAMING_SNAKE_CASE_		(       self						:	Optional[int]							,  *__snake_case						:	Tuple							,  **__snake_case						:	Tuple							):





											'''simple docstring'''





											return 1


					def  SCREAMING_SNAKE_CASE_		(       self						:	Any							,  __snake_case						:	Optional[int]							):





											'''simple docstring'''





											_snake_case: Dict	       =		set(self.all_special_ids							)  # call it once instead of inside list comp
											all_special_ids.remove(self.unk_token_id							)  # <unk> is only sometimes special
											return [1 if x in all_special_ids else 0 for x in seq]




					def  SCREAMING_SNAKE_CASE_		(       self						:	Optional[Any]							,  __snake_case						:	List							,  __snake_case						:	Optional[List] = None							,  __snake_case						:	bool = False							):





											'''simple docstring'''





											if already_has_special_tokens:
																	return self._special_token_mask(__snake_case							)
											elif token_ids_a is None:
																	return self._special_token_mask(__snake_case							) + [1]
											else:
																	return self._special_token_mask(token_ids_a + token_ids_a							) + [1]





def    lowercase_   (		lowercase__					,	lowercase__    ) ->sentencepiece.SentencePieceProcessor:
						_snake_case: Union[str, Any]	       =		sentencepiece.SentencePieceProcessor(**lowercase__    )
						spm.Load(lowercase__    )
						return spm





def    lowercase_   (		lowercase__					,	lowercase__    ) ->None:
						with open(lowercase__					,	'w'    ) as f:
												json.dump(lowercase__					,	lowercase__					,	indent=2    )





def    lowercase_   (		lowercase__    ) ->Union[Dict, List]:
						with open(lowercase__					,	'r'    ) as f:
												return json.load(lowercase__    )





