
'''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__				:	Dict					=						10_00






class 				A       :





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


				"""simple docstring"""

				if isinstance(__magic_name__ ,							torch.Tensor							):
							lowerCAmelCase__									=							img.numpy().astype("np.uint8"							)
				if isinstance(__magic_name__ ,							__magic_name__							):
							lowerCAmelCase__									=							img_tensorize(__magic_name__							)
				assert isinstance(__magic_name__ ,							np.ndarray							)

				lowerCAmelCase__		,lowerCAmelCase__									=							img.shape[1], img.shape[0]
				lowerCAmelCase__									=							mplfigure.Figure(frameon=__magic_name__							)
				lowerCAmelCase__									=							fig.get_dpi()
				lowerCAmelCase__									=							(width * scale + 1E-2) / dpi
				lowerCAmelCase__									=							(height * scale + 1E-2) / dpi
				fig.set_size_inches(__magic_name__ ,							__magic_name__							)
				lowerCAmelCase__									=							fig.add_axes([0.0, 0.0, 1.0, 1.0]							)
				ax.axis("off"							)
				ax.set_xlim(0.0 ,							__magic_name__							)
				ax.set_ylim(__magic_name__							)

				lowerCAmelCase__									=							saveas
				lowerCAmelCase__									=							rgb
				lowerCAmelCase__									=							pynb
				lowerCAmelCase__									=							img
				lowerCAmelCase__									=							edgecolor
				lowerCAmelCase__									=							0.5
				lowerCAmelCase__									=							linestyle
				lowerCAmelCase__									=							int(np.sqrt(min(__magic_name__ ,							__magic_name__							)							) * scale // 3							)
				lowerCAmelCase__									=							width
				lowerCAmelCase__									=							height
				lowerCAmelCase__									=							scale
				lowerCAmelCase__									=							fig
				lowerCAmelCase__									=							ax
				lowerCAmelCase__									=							pad
				lowerCAmelCase__									=							idaobj
				lowerCAmelCase__									=							idaattr
				lowerCAmelCase__									=							FigureCanvasAgg(__magic_name__							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Tuple ,							__magic_name__     :    Any ,							__magic_name__     :    Tuple=None							):


				"""simple docstring"""

				if color is None:
							lowerCAmelCase__									=							self.edgecolor
				((lowerCAmelCase__)		,(lowerCAmelCase__)		,(lowerCAmelCase__)		,(lowerCAmelCase__))									=							box
				lowerCAmelCase__									=							xa - xa
				lowerCAmelCase__									=							ya - ya
				self.ax.add_patch(
				    mpl.patches.Rectangle(
				        (xa, ya) ,							__magic_name__ ,							__magic_name__ ,							fill=__magic_name__ ,							edgecolor=__magic_name__ ,							linewidth=self.font_size // 3 ,							alpha=self.alpha ,							linestyle=self.linestyle ,							)							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    str ,							__magic_name__     :    Optional[Any] ,							__magic_name__     :    Dict=None ,							__magic_name__     :    Tuple=None ,							__magic_name__     :    Any=None ,							__magic_name__     :    Union[str, Any]=None							):


				"""simple docstring"""

				if len(boxes.shape							) > 2:
							lowerCAmelCase__									=							boxes[0]
				if len(obj_ids.shape							) > 1:
							lowerCAmelCase__									=							obj_ids[0]
				if len(obj_scores.shape							) > 1:
							lowerCAmelCase__									=							obj_scores[0]
				if len(attr_ids.shape							) > 1:
							lowerCAmelCase__									=							attr_ids[0]
				if len(attr_scores.shape							) > 1:
							lowerCAmelCase__									=							attr_scores[0]
				if isinstance(__magic_name__ ,							torch.Tensor							):
							lowerCAmelCase__									=							boxes.numpy()
				if isinstance(__magic_name__ ,							__magic_name__							):
							lowerCAmelCase__									=							np.array(__magic_name__							)
				assert isinstance(__magic_name__ ,							np.ndarray							)
				lowerCAmelCase__									=							np.prod(boxes[:, 2:] - boxes[:, :2] ,							axis=1							)
				lowerCAmelCase__									=							np.argsort(-areas							).tolist()
				lowerCAmelCase__									=							boxes[sorted_idxs] if boxes is not None else None
				lowerCAmelCase__									=							obj_ids[sorted_idxs] if obj_ids is not None else None
				lowerCAmelCase__									=							obj_scores[sorted_idxs] if obj_scores is not None else None
				lowerCAmelCase__									=							attr_ids[sorted_idxs] if attr_ids is not None else None
				lowerCAmelCase__									=							attr_scores[sorted_idxs] if attr_scores is not None else None

				lowerCAmelCase__									=							[self._random_color(maximum=1							) for _ in range(len(__magic_name__							)							)]
				lowerCAmelCase__									=							[assigned_colors[idx] for idx in sorted_idxs]
				if obj_ids is not None:
							lowerCAmelCase__									=							self._create_text_labels_attr(__magic_name__ ,							__magic_name__ ,							__magic_name__ ,							__magic_name__							)
							for i in range(len(__magic_name__							)							):
										lowerCAmelCase__									=							assigned_colors[i]
										self.add_box(boxes[i] ,							__magic_name__							)
										self.draw_labels(labels[i] ,							boxes[i] ,							__magic_name__							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[str] ,							__magic_name__     :    str ,							__magic_name__     :    List[str] ,							__magic_name__     :    Tuple							):


				"""simple docstring"""

				lowerCAmelCase__		,lowerCAmelCase__		,lowerCAmelCase__		,lowerCAmelCase__									=							box
				lowerCAmelCase__									=							(xa, ya)
				lowerCAmelCase__									=							(ya - ya) * (xa - xa)
				lowerCAmelCase__									=							_SMALL_OBJ * self.scale
				if instance_area < small or ya - ya < 40 * self.scale:
							if ya >= self.height - 5:
										lowerCAmelCase__									=							(xa, ya)
							else:
										lowerCAmelCase__									=							(xa, ya)

				lowerCAmelCase__									=							(ya - ya) / np.sqrt(self.height * self.width							)
				lowerCAmelCase__									=							self._change_color_brightness(__magic_name__ ,							brightness_factor=0.7							)
				lowerCAmelCase__									=							np.clip((height_ratio - 0.02) / 0.08 + 1 ,							1.2 ,							2							)
				font_size *= 0.75 * self.font_size

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Union[str, Any] ,							__magic_name__     :    str ,							__magic_name__     :    Dict ,							__magic_name__     :    List[str]="g" ,							__magic_name__     :    Optional[int]="left" ,							):


				"""simple docstring"""

				lowerCAmelCase__									=							0
				lowerCAmelCase__									=							self.font_size
				lowerCAmelCase__									=							np.maximum(list(mplc.to_rgb(__magic_name__							)							) ,							0.2							)
				lowerCAmelCase__									=							max(0.8 ,							np.max(__magic_name__							)							)
				lowerCAmelCase__									=							{
				    "facecolor": "black",
				    "alpha": self.alpha,
				    "pad": self.pad,
				    "edgecolor": "none",
				}
				lowerCAmelCase__		,lowerCAmelCase__									=							position
				self.ax.text(
				    __magic_name__ ,							__magic_name__ ,							__magic_name__ ,							size=font_size * self.scale ,							family="sans-serif" ,							bbox=__magic_name__ ,							verticalalignment="top" ,							horizontalalignment=__magic_name__ ,							color=__magic_name__ ,							zorder=10 ,							rotation=__magic_name__ ,							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Optional[int] ,							__magic_name__     :    Tuple=None							):


				"""simple docstring"""

				if saveas is None:
							lowerCAmelCase__									=							self.saveas
				if saveas.lower().endswith(".jpg"							) or saveas.lower().endswith(".png"							):
							cva.imwrite(
							    __magic_name__ ,							self._get_buffer()[:, :, ::-1] ,							)
				else:
							self.fig.savefig(__magic_name__							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    int ,							__magic_name__     :    Optional[int] ,							__magic_name__     :    List[Any] ,							__magic_name__     :    Union[str, Any] ,							__magic_name__     :    Optional[Any]							):


				"""simple docstring"""

				lowerCAmelCase__									=							[self.idaobj[i] for i in classes]
				lowerCAmelCase__									=							[self.idaattr[i] for i in attr_classes]
				lowerCAmelCase__									=							[
				    f"""{label} {score:.2f} {attr} {attr_score:.2f}"""
				    for label, score, attr, attr_score in zip(__magic_name__ ,							__magic_name__ ,							__magic_name__ ,							__magic_name__							)
				]
				return labels





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[str] ,							__magic_name__     :    List[str] ,							__magic_name__     :    Optional[Any]							):


				"""simple docstring"""

				lowerCAmelCase__									=							[self.idaobj[i] for i in classes]
				if scores is not None:
							if labels is None:
										lowerCAmelCase__									=							["{:.0f}%".format(s * 100							) for s in scores]
							else:
										lowerCAmelCase__									=							["{} {:.0f}%".format(__magic_name__ ,							s * 100							) for li, s in zip(__magic_name__ ,							__magic_name__							)]
				return labels





	def 							__SCREAMING_SNAKE_CASE					(   self     :    str ,							__magic_name__     :    int=255							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[str]							):


				"""simple docstring"""

				if not self.pynb:
							lowerCAmelCase__		,lowerCAmelCase__									=							self.canvas.print_to_buffer()
							if (width, height) != (self.width, self.height):
										lowerCAmelCase__									=							cva.resize(self.img ,							(width, height)							)
							else:
										lowerCAmelCase__									=							self.img
				else:
							lowerCAmelCase__									=							io.BytesIO()  # works for cairo backend
							self.canvas.print_rgba(__magic_name__							)
							lowerCAmelCase__		,lowerCAmelCase__									=							self.width, self.height
							lowerCAmelCase__									=							buf.getvalue()
							lowerCAmelCase__									=							self.img

				lowerCAmelCase__									=							np.frombuffer(__magic_name__ ,							dtype="uint8"							)
				lowerCAmelCase__									=							buffer.reshape(__magic_name__ ,							__magic_name__ ,							4							)
				lowerCAmelCase__		,lowerCAmelCase__									=							np.split(__magic_name__ ,							[3] ,							axis=2							)

				try:
							import numexpr as ne  # fuse them with numexpr

							lowerCAmelCase__									=							ne.evaluate("img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)"							)
				except ImportError:
							lowerCAmelCase__									=							alpha.astype("float32"							) / 255.0
							lowerCAmelCase__									=							img * (1 - alpha) + rgb * alpha

				return visualized_image.astype("uint8"							)







	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[str] ,							__magic_name__     :    str ,							__magic_name__     :    Dict							):


				"""simple docstring"""

				assert brightness_factor >= -1.0 and brightness_factor <= 1.0
				lowerCAmelCase__									=							mplc.to_rgb(__magic_name__							)
				lowerCAmelCase__									=							colorsys.rgb_to_hls(*mplc.to_rgb(__magic_name__							)							)
				lowerCAmelCase__									=							polygon_color[1] + (brightness_factor * polygon_color[1])
				lowerCAmelCase__									=							0.0 if modified_lightness < 0.0 else modified_lightness
				lowerCAmelCase__									=							1.0 if modified_lightness > 1.0 else modified_lightness
				lowerCAmelCase__									=							colorsys.hls_to_rgb(polygon_color[0] ,							__magic_name__ ,							polygon_color[2]							)
				return modified_color

UpperCAmelCase__				:	Union[str, Any]					=						(
    np.array(
        [
            0.0_0_0,
            0.4_4_7,
            0.7_4_1,
            0.8_5_0,
            0.3_2_5,
            0.0_9_8,
            0.9_2_9,
            0.6_9_4,
            0.1_2_5,
            0.4_9_4,
            0.1_8_4,
            0.5_5_6,
            0.4_6_6,
            0.6_7_4,
            0.1_8_8,
            0.3_0_1,
            0.7_4_5,
            0.9_3_3,
            0.6_3_5,
            0.0_7_8,
            0.1_8_4,
            0.3_0_0,
            0.3_0_0,
            0.3_0_0,
            0.6_0_0,
            0.6_0_0,
            0.6_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.7_4_9,
            0.7_4_9,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.3_3_3,
            0.0_0_0,
            0.3_3_3,
            0.6_6_7,
            0.0_0_0,
            0.3_3_3,
            1.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.3_3_3,
            0.0_0_0,
            0.6_6_7,
            0.6_6_7,
            0.0_0_0,
            0.6_6_7,
            1.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.3_3_3,
            0.5_0_0,
            0.0_0_0,
            0.6_6_7,
            0.5_0_0,
            0.0_0_0,
            1.0_0_0,
            0.5_0_0,
            0.3_3_3,
            0.0_0_0,
            0.5_0_0,
            0.3_3_3,
            0.3_3_3,
            0.5_0_0,
            0.3_3_3,
            0.6_6_7,
            0.5_0_0,
            0.3_3_3,
            1.0_0_0,
            0.5_0_0,
            0.6_6_7,
            0.0_0_0,
            0.5_0_0,
            0.6_6_7,
            0.3_3_3,
            0.5_0_0,
            0.6_6_7,
            0.6_6_7,
            0.5_0_0,
            0.6_6_7,
            1.0_0_0,
            0.5_0_0,
            1.0_0_0,
            0.0_0_0,
            0.5_0_0,
            1.0_0_0,
            0.3_3_3,
            0.5_0_0,
            1.0_0_0,
            0.6_6_7,
            0.5_0_0,
            1.0_0_0,
            1.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.3_3_3,
            1.0_0_0,
            0.0_0_0,
            0.6_6_7,
            1.0_0_0,
            0.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.0_0_0,
            1.0_0_0,
            0.3_3_3,
            0.3_3_3,
            1.0_0_0,
            0.3_3_3,
            0.6_6_7,
            1.0_0_0,
            0.3_3_3,
            1.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.0_0_0,
            1.0_0_0,
            0.6_6_7,
            0.3_3_3,
            1.0_0_0,
            0.6_6_7,
            0.6_6_7,
            1.0_0_0,
            0.6_6_7,
            1.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.0_0_0,
            1.0_0_0,
            1.0_0_0,
            0.3_3_3,
            1.0_0_0,
            1.0_0_0,
            0.6_6_7,
            1.0_0_0,
            0.3_3_3,
            0.0_0_0,
            0.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.0_0_0,
            0.0_0_0,
            0.8_3_3,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.1_6_7,
            0.0_0_0,
            0.0_0_0,
            0.3_3_3,
            0.0_0_0,
            0.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.0_0_0,
            0.0_0_0,
            0.8_3_3,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.1_6_7,
            0.0_0_0,
            0.0_0_0,
            0.3_3_3,
            0.0_0_0,
            0.0_0_0,
            0.5_0_0,
            0.0_0_0,
            0.0_0_0,
            0.6_6_7,
            0.0_0_0,
            0.0_0_0,
            0.8_3_3,
            0.0_0_0,
            0.0_0_0,
            1.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.0_0_0,
            0.1_4_3,
            0.1_4_3,
            0.1_4_3,
            0.8_5_7,
            0.8_5_7,
            0.8_5_7,
            1.0_0_0,
            1.0_0_0,
            1.0_0_0,
        ]
    )
    .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


UpperCAmelCase__				:	Tuple					=						logging.get_logger(__name__)

UpperCAmelCase__				:	int					=						{
    "source_spm": "source.spm",
    "target_spm": "target.spm",
    "vocab": "vocab.json",
    "target_vocab_file": "target_vocab.json",
    "tokenizer_config_file": "tokenizer_config.json",
}

UpperCAmelCase__				:	Dict					=						{
    "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"
        )
    },
}

UpperCAmelCase__				:	Union[str, Any]					=						{"Helsinki-NLP/opus-mt-en-de": 5_12}
UpperCAmelCase__				:	str					=						{}






class 				A       (		SCREAMING_SNAKE_CASE__      ):
	snake_case__ :Union[str, Any]				       =       VOCAB_FILES_NAMES
	snake_case__ :Optional[int]				       =       PRETRAINED_VOCAB_FILES_MAP
	snake_case__ :Dict				       =       PRETRAINED_INIT_CONFIGURATION
	snake_case__ :List[str]				       =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	snake_case__ :str				       =       ['input_ids', 'attention_mask']
	snake_case__ :Optional[int]				       =       re.compile('>>.+<<'      )  # type: re.Pattern





	def __init__(   self     :    Tuple ,							__magic_name__     :    str ,							__magic_name__     :    Tuple ,							__magic_name__     :    Optional[int] ,							__magic_name__     :    Optional[Any]=None ,							__magic_name__     :    Optional[Any]=None ,							__magic_name__     :    str=None ,							__magic_name__     :    str="<unk>" ,							__magic_name__     :    Dict="</s>" ,							__magic_name__     :    List[str]="<pad>" ,							__magic_name__     :    str=512 ,							__magic_name__     :    Optional[Dict[str, Any]] = None ,							__magic_name__     :    Union[str, Any]=False ,							**__magic_name__     :    int ,							):


				"""simple docstring"""

				lowerCAmelCase__									=							{} 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=__magic_name__ ,							target_lang=__magic_name__ ,							unk_token=__magic_name__ ,							eos_token=__magic_name__ ,							pad_token=__magic_name__ ,							model_max_length=__magic_name__ ,							sp_model_kwargs=self.sp_model_kwargs ,							target_vocab_file=__magic_name__ ,							separate_vocabs=__magic_name__ ,							**__magic_name__ ,							)
				assert Path(__magic_name__							).exists(), f"""cannot find spm source {source_spm}"""

				lowerCAmelCase__									=							separate_vocabs
				lowerCAmelCase__									=							load_json(__magic_name__							)
				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:
							lowerCAmelCase__									=							load_json(__magic_name__							)
							lowerCAmelCase__									=							{v: k for k, v in self.target_encoder.items()}
							lowerCAmelCase__									=							[]
				else:
							lowerCAmelCase__									=							{v: k for k, v in self.encoder.items()}
							lowerCAmelCase__									=							[k for k in self.encoder if k.startswith(">>"							) and k.endswith("<<"							)]

				lowerCAmelCase__									=							source_lang
				lowerCAmelCase__									=							target_lang
				lowerCAmelCase__									=							[source_spm, target_spm]

				# load SentencePiece model for pre-processing
				lowerCAmelCase__									=							load_spm(__magic_name__ ,							self.sp_model_kwargs							)
				lowerCAmelCase__									=							load_spm(__magic_name__ ,							self.sp_model_kwargs							)
				lowerCAmelCase__									=							self.spm_source
				lowerCAmelCase__									=							self.encoder

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

				self._setup_normalizer()





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Dict							):


				"""simple docstring"""

				try:
							from sacremoses import MosesPunctNormalizer

							lowerCAmelCase__									=							MosesPunctNormalizer(self.source_lang							).normalize
				except (ImportError, FileNotFoundError):
							warnings.warn("Recommended: pip install sacremoses."							)
							lowerCAmelCase__									=							lambda __magic_name__							: x





	def 							__SCREAMING_SNAKE_CASE					(   self     :    int ,							__magic_name__     :    str							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[str] ,							__magic_name__     :    List[str]							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    int ,							__magic_name__     :    str							):


				"""simple docstring"""

				lowerCAmelCase__									=							self.language_code_re.match(__magic_name__							)
				lowerCAmelCase__									=							[match.group(0							)] if match else []
				return code, self.language_code_re.sub("" ,							__magic_name__							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    str ,							__magic_name__     :    str							):


				"""simple docstring"""

				lowerCAmelCase__		,lowerCAmelCase__									=							self.remove_language_code(__magic_name__							)
				lowerCAmelCase__									=							self.current_spm.encode(__magic_name__ ,							out_type=__magic_name__							)
				return code + pieces





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Tuple ,							__magic_name__     :    int							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Tuple ,							__magic_name__     :    Optional[int] ,							**__magic_name__     :    Union[str, Any]							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Dict ,							__magic_name__     :    Union[str, Any] ,							**__magic_name__     :    Optional[int]							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Optional[Any] ,							__magic_name__     :    List[str]							):


				"""simple docstring"""

				lowerCAmelCase__									=							self.spm_source if self._decode_use_source_tokenizer else self.spm_target
				lowerCAmelCase__									=							[]
				lowerCAmelCase__									=							""
				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(__magic_name__							) + token + " "
										lowerCAmelCase__									=							[]
							else:
										current_sub_tokens.append(__magic_name__							)
				out_string += sp_model.decode_pieces(__magic_name__							)
				return out_string.strip()





	def 							__SCREAMING_SNAKE_CASE					(   self     :    int ,							__magic_name__     :    Dict ,							__magic_name__     :    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[int]							):


				"""simple docstring"""

				lowerCAmelCase__									=							self.spm_source
				lowerCAmelCase__									=							self.encoder





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[Any]							):


				"""simple docstring"""

				lowerCAmelCase__									=							self.spm_target
				if self.separate_vocabs:
							lowerCAmelCase__									=							self.target_encoder





	@property
	def 							__SCREAMING_SNAKE_CASE					(   self     :    int							):


				"""simple docstring"""

				return len(self.encoder							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Optional[int] ,							__magic_name__     :    str ,							__magic_name__     :    Optional[str] = None							):


				"""simple docstring"""

				if not os.path.isdir(__magic_name__							):
							logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""							)
							return
				lowerCAmelCase__									=							[]

				if self.separate_vocabs:
							lowerCAmelCase__									=							os.path.join(
							    __magic_name__ ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab"] ,							)
							lowerCAmelCase__									=							os.path.join(
							    __magic_name__ ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["target_vocab_file"] ,							)
							save_json(self.encoder ,							__magic_name__							)
							save_json(self.target_encoder ,							__magic_name__							)
							saved_files.append(__magic_name__							)
							saved_files.append(__magic_name__							)
				else:
							lowerCAmelCase__									=							os.path.join(
							    __magic_name__ ,							(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab"]							)
							save_json(self.encoder ,							__magic_name__							)
							saved_files.append(__magic_name__							)

				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] ,							):
							lowerCAmelCase__									=							os.path.join(
							    __magic_name__ ,							(filename_prefix + "-" if filename_prefix else "") + spm_save_filename							)
							if os.path.abspath(__magic_name__							) != os.path.abspath(__magic_name__							) and os.path.isfile(__magic_name__							):
										copyfile(__magic_name__ ,							__magic_name__							)
										saved_files.append(__magic_name__							)
							elif not os.path.isfile(__magic_name__							):
										with open(__magic_name__ ,							"wb"							) as fi:
													lowerCAmelCase__									=							spm_model.serialized_model_proto()
													fi.write(__magic_name__							)
										saved_files.append(__magic_name__							)

				return tuple(__magic_name__							)





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Any							):


				"""simple docstring"""

				return self.get_src_vocab()





	def 							__SCREAMING_SNAKE_CASE					(   self     :    Tuple							):


				"""simple docstring"""

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





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[Any]							):


				"""simple docstring"""

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





	def __getstate__(   self     :    List[Any]							):


				"""simple docstring"""

				lowerCAmelCase__									=							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     :    Dict ,							__magic_name__     :    Dict							):


				"""simple docstring"""

				lowerCAmelCase__									=							d

				# for backward compatibility
				if not hasattr(self ,							"sp_model_kwargs"							):
							lowerCAmelCase__									=							{}

				lowerCAmelCase__		,lowerCAmelCase__									=							(load_spm(__magic_name__ ,							self.sp_model_kwargs							) for f in self.spm_files)
				lowerCAmelCase__									=							self.spm_source
				self._setup_normalizer()





	def 							__SCREAMING_SNAKE_CASE					(   self     :    List[str] ,							*__magic_name__     :    Any ,							**__magic_name__     :    Tuple							):


				"""simple docstring"""

				return 1





	def 							__SCREAMING_SNAKE_CASE					(   self     :    str ,							__magic_name__     :    Optional[Any]							):


				"""simple docstring"""

				lowerCAmelCase__									=							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[int] ,							__magic_name__     :    List ,							__magic_name__     :    Optional[List] = None ,							__magic_name__     :    bool = False							):


				"""simple docstring"""

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







def 					A       ( UpperCamelCase_   :       str  ,		UpperCamelCase_   :       Dict[str, Any] )   ->    sentencepiece.SentencePieceProcessor:







			'''simple docstring'''



			lowerCAmelCase__									=							sentencepiece.SentencePieceProcessor(**UpperCamelCase_ )
			spm.Load(UpperCamelCase_ )
			return spm







def 					A       ( UpperCamelCase_   :       Optional[Any]  ,		UpperCamelCase_   :       str )   ->    None:







			'''simple docstring'''



			with open(UpperCamelCase_  ,		"w" ) as f:
						json.dump(UpperCamelCase_  ,		UpperCamelCase_  ,		indent=2 )







def 					A       ( UpperCamelCase_   :       str )   ->    Union[Dict, List]:







			'''simple docstring'''



			with open(UpperCamelCase_  ,		"r" ) as f:
						return json.load(UpperCamelCase_ )





