




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


__SCREAMING_SNAKE_CASE    :   Any       =1_000






class 			A			:
     """simple docstring"""

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

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

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




     def  __snake_case   (    self  :   Any	,  A__  :   Optional[Any]	,  A__  :   int=None			)				->       Union[str, Any]:
           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)	,  A__	,  A__	,  fill=A__	,  edgecolor=A__	,  linewidth=self.font_size // 3	,  alpha=self.alpha	,  linestyle=self.linestyle	,  )			)




     def  __snake_case   (    self  :   Dict	,  A__  :   Optional[Any]	,  A__  :   Optional[int]=None	,  A__  :   int=None	,  A__  :   Union[str, Any]=None	,  A__  :   Union[str, Any]=None			)				->       Optional[Any]:
           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(A__	,  torch.Tensor			):
                 lowerCamelCase__        =				boxes.numpy()
           if isinstance(A__	,  A__			):
                 lowerCamelCase__        =				np.array(A__			)
           assert isinstance(A__	,  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(A__			)			)]
           lowerCamelCase__        =				[assigned_colors[idx] for idx in sorted_idxs]
           if obj_ids is not None:
                 lowerCamelCase__        =				self._create_text_labels_attr(A__	,  A__	,  A__	,  A__			)
                 for i in range(len(A__			)			):
                       lowerCamelCase__        =				assigned_colors[i]
                       self.add_box(boxes[i]	,  A__			)
                       self.draw_labels(labels[i]	,  boxes[i]	,  A__			)




     def  __snake_case   (    self  :   Optional[Any]	,  A__  :   Any	,  A__  :   Tuple	,  A__  :   Optional[int]			)				->       Dict:
           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 < 4_0 * 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(A__	,  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=A__	,  position=A__	,  color=A__	,  )




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




     def  __snake_case   (    self  :   Tuple	,  A__  :   int=None			)				->       List[Any]:
           if saveas is None:
                 lowerCamelCase__        =				self.saveas
           if saveas.lower().endswith('.jpg'			) or saveas.lower().endswith('.png'			):
                 cva.imwrite(
                     A__	,  self._get_buffer()[:, :, ::-1]	,  )
           else:
                 self.fig.savefig(A__			)




     def  __snake_case   (    self  :   Any	,  A__  :   List[str]	,  A__  :   List[str]	,  A__  :   Union[str, Any]	,  A__  :   Tuple			)				->       Union[str, Any]:
           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(A__	,  A__	,  A__	,  A__			)
           ]
           return labels




     def  __snake_case   (    self  :   str	,  A__  :   List[str]	,  A__  :   List[Any]			)				->       Optional[Any]:
           lowerCamelCase__        =				[self.idaobj[i] for i in classes]
           if scores is not None:
                 if labels is None:
                       lowerCamelCase__        =				['{:.0f}%'.format(s * 1_0_0			) for s in scores]
                 else:
                       lowerCamelCase__        =				['{} {:.0f}%'.format(A__	,  s * 1_0_0			) for li, s in zip(A__	,  A__			)]
           return labels




     def  __snake_case   (    self  :   List[Any]	,  A__  :   List[Any]=2_5_5			)				->       Optional[int]:
           lowerCamelCase__        =				np.random.randint(0	,  len(_COLORS			)			)
           lowerCamelCase__        =				_COLORS[idx] * maximum
           if not self.rgb:
                 lowerCamelCase__        =				ret[::-1]
           return ret




     def  __snake_case   (    self  :   Union[str, Any]			)				->       List[str]:
           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(A__			)
                 lowerCamelCase__  ,		lowerCamelCase__        =				self.width, self.height
                 lowerCamelCase__        =				buf.getvalue()
                 lowerCamelCase__        =				self.img

           lowerCamelCase__        =				np.frombuffer(A__	,  dtype='uint8'			)
           lowerCamelCase__        =				buffer.reshape(A__	,  A__	,  4			)
           lowerCamelCase__  ,		lowerCamelCase__        =				np.split(A__	,  [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  __snake_case   (    self  :   str	,  A__  :   Optional[Any]	,  A__  :   int			)				->       Dict:
           assert brightness_factor >= -1.0 and brightness_factor <= 1.0
           lowerCamelCase__        =				mplc.to_rgb(A__			)
           lowerCamelCase__        =				colorsys.rgb_to_hls(*mplc.to_rgb(A__			)			)
           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]	,  A__	,  polygon_color[2]			)
           return modified_color
__SCREAMING_SNAKE_CASE    :   int       =(
    np.array(
        [
            0.000,
            0.447,
            0.741,
            0.850,
            0.325,
            0.098,
            0.929,
            0.694,
            0.125,
            0.494,
            0.184,
            0.556,
            0.466,
            0.674,
            0.188,
            0.301,
            0.745,
            0.933,
            0.635,
            0.078,
            0.184,
            0.300,
            0.300,
            0.300,
            0.600,
            0.600,
            0.600,
            1.000,
            0.000,
            0.000,
            1.000,
            0.500,
            0.000,
            0.749,
            0.749,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            1.000,
            0.667,
            0.000,
            1.000,
            0.333,
            0.333,
            0.000,
            0.333,
            0.667,
            0.000,
            0.333,
            1.000,
            0.000,
            0.667,
            0.333,
            0.000,
            0.667,
            0.667,
            0.000,
            0.667,
            1.000,
            0.000,
            1.000,
            0.333,
            0.000,
            1.000,
            0.667,
            0.000,
            1.000,
            1.000,
            0.000,
            0.000,
            0.333,
            0.500,
            0.000,
            0.667,
            0.500,
            0.000,
            1.000,
            0.500,
            0.333,
            0.000,
            0.500,
            0.333,
            0.333,
            0.500,
            0.333,
            0.667,
            0.500,
            0.333,
            1.000,
            0.500,
            0.667,
            0.000,
            0.500,
            0.667,
            0.333,
            0.500,
            0.667,
            0.667,
            0.500,
            0.667,
            1.000,
            0.500,
            1.000,
            0.000,
            0.500,
            1.000,
            0.333,
            0.500,
            1.000,
            0.667,
            0.500,
            1.000,
            1.000,
            0.500,
            0.000,
            0.333,
            1.000,
            0.000,
            0.667,
            1.000,
            0.000,
            1.000,
            1.000,
            0.333,
            0.000,
            1.000,
            0.333,
            0.333,
            1.000,
            0.333,
            0.667,
            1.000,
            0.333,
            1.000,
            1.000,
            0.667,
            0.000,
            1.000,
            0.667,
            0.333,
            1.000,
            0.667,
            0.667,
            1.000,
            0.667,
            1.000,
            1.000,
            1.000,
            0.000,
            1.000,
            1.000,
            0.333,
            1.000,
            1.000,
            0.667,
            1.000,
            0.333,
            0.000,
            0.000,
            0.500,
            0.000,
            0.000,
            0.667,
            0.000,
            0.000,
            0.833,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            0.167,
            0.000,
            0.000,
            0.333,
            0.000,
            0.000,
            0.500,
            0.000,
            0.000,
            0.667,
            0.000,
            0.000,
            0.833,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            0.167,
            0.000,
            0.000,
            0.333,
            0.000,
            0.000,
            0.500,
            0.000,
            0.000,
            0.667,
            0.000,
            0.000,
            0.833,
            0.000,
            0.000,
            1.000,
            0.000,
            0.000,
            0.000,
            0.143,
            0.143,
            0.143,
            0.857,
            0.857,
            0.857,
            1.000,
            1.000,
            1.000,
        ]
    )
    .astype(np.floataa)
    .reshape(-1, 3)
)





import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_longformer import LongformerTokenizer


__SCREAMING_SNAKE_CASE    :   Dict       =logging.get_logger(__name__)

__SCREAMING_SNAKE_CASE    :   str       ={"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt""", """tokenizer_file""": """tokenizer.json"""}

__SCREAMING_SNAKE_CASE    :   Dict       ={
    """vocab_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
    },
    """merges_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
    },
    """tokenizer_file""": {
        """allenai/longformer-base-4096""": (
            """https://huggingface.co/allenai/longformer-base-4096/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/tokenizer.json"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/tokenizer.json"""
        ),
    },
}

__SCREAMING_SNAKE_CASE    :   int       ={
    """allenai/longformer-base-4096""": 4_096,
    """allenai/longformer-large-4096""": 4_096,
    """allenai/longformer-large-4096-finetuned-triviaqa""": 4_096,
    """allenai/longformer-base-4096-extra.pos.embd.only""": 4_096,
    """allenai/longformer-large-4096-extra.pos.embd.only""": 4_096,
}






class 			A			(		_lowerCAmelCase		):
     """simple docstring"""

     _snake_case:	Optional[Any]     =VOCAB_FILES_NAMES
     _snake_case:	List[str]     =PRETRAINED_VOCAB_FILES_MAP
     _snake_case:	str     =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _snake_case:	str     =["input_ids", "attention_mask"]
     _snake_case:	Union[str, Any]     =LongformerTokenizer




     def __init__(    self  :   str	,  A__  :   Optional[Any]=None	,  A__  :   Dict=None	,  A__  :   Any=None	,  A__  :   Optional[Any]="replace"	,  A__  :   Tuple="<s>"	,  A__  :   Any="</s>"	,  A__  :   Dict="</s>"	,  A__  :   Any="<s>"	,  A__  :   Optional[Any]="<unk>"	,  A__  :   Tuple="<pad>"	,  A__  :   Union[str, Any]="<mask>"	,  A__  :   List[str]=False	,  A__  :   List[str]=True	,  **A__  :   Optional[int]	,  )				->       List[str]:
           super().__init__(
               A__	,  A__	,  tokenizer_file=A__	,  errors=A__	,  bos_token=A__	,  eos_token=A__	,  sep_token=A__	,  cls_token=A__	,  unk_token=A__	,  pad_token=A__	,  mask_token=A__	,  add_prefix_space=A__	,  trim_offsets=A__	,  **A__	,  )

           lowerCamelCase__        =				json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()			)
           if pre_tok_state.get('add_prefix_space'	,  A__			) != add_prefix_space:
                 lowerCamelCase__        =				getattr(A__	,  pre_tok_state.pop('type'			)			)
                 lowerCamelCase__        =				add_prefix_space
                 lowerCamelCase__        =				pre_tok_class(**A__			)

           lowerCamelCase__        =				add_prefix_space

           lowerCamelCase__        =				'post_processor'
           lowerCamelCase__        =				getattr(self.backend_tokenizer	,  A__	,  A__			)
           if tokenizer_component_instance:
                 lowerCamelCase__        =				json.loads(tokenizer_component_instance.__getstate__()			)

                 # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
                 if "sep" in state:
                       lowerCamelCase__        =				tuple(state['sep']			)
                 if "cls" in state:
                       lowerCamelCase__        =				tuple(state['cls']			)

                 lowerCamelCase__        =				False

                 if state.get('add_prefix_space'	,  A__			) != add_prefix_space:
                       lowerCamelCase__        =				add_prefix_space
                       lowerCamelCase__        =				True

                 if state.get('trim_offsets'	,  A__			) != trim_offsets:
                       lowerCamelCase__        =				trim_offsets
                       lowerCamelCase__        =				True

                 if changes_to_apply:
                       lowerCamelCase__        =				getattr(A__	,  state.pop('type'			)			)
                       lowerCamelCase__        =				component_class(**A__			)
                       setattr(self.backend_tokenizer	,  A__	,  A__			)




     @property
     def  __snake_case   (    self  :   Tuple			)				->       str:
           if self._mask_token is None:
                 if self.verbose:
                       logger.error('Using mask_token, but it is not set yet.'			)
                 return None
           return str(self._mask_token			)




     @mask_token.setter
     def  __snake_case   (    self  :   Dict	,  A__  :   Tuple			)				->       int:
           lowerCamelCase__        =				AddedToken(A__	,  lstrip=A__	,  rstrip=A__			) if isinstance(A__	,  A__			) else value
           lowerCamelCase__        =				value




     def  __snake_case   (    self  :   Any	,  *A__  :   Any	,  **A__  :   Any			)				->       BatchEncoding:
           lowerCamelCase__        =				kwargs.get('is_split_into_words'	,  A__			)
           assert self.add_prefix_space or not is_split_into_words, (
               F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
               "to use it with pretokenized inputs."
           )

           return super()._batch_encode_plus(*A__	,  **A__			)




     def  __snake_case   (    self  :   Tuple	,  *A__  :   str	,  **A__  :   int			)				->       BatchEncoding:
           lowerCamelCase__        =				kwargs.get('is_split_into_words'	,  A__			)

           assert self.add_prefix_space or not is_split_into_words, (
               F"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
               "to use it with pretokenized inputs."
           )

           return super()._encode_plus(*A__	,  **A__			)




     def  __snake_case   (    self  :   Union[str, Any]	,  A__  :   str	,  A__  :   Optional[str] = None			)				->       Tuple[str]:
           lowerCamelCase__        =				self._tokenizer.model.save(A__	,  name=A__			)
           return tuple(A__			)




     def  __snake_case   (    self  :   Any	,  A__  :   int	,  A__  :   List[str]=None			)				->       Dict:
           lowerCamelCase__        =				[self.bos_token_id] + token_ids_a + [self.eos_token_id]
           if token_ids_a is None:
                 return output

           return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




     def  __snake_case   (    self  :   Union[str, Any]	,  A__  :   List[int]	,  A__  :   Optional[List[int]] = None			)				->       List[int]:
           lowerCamelCase__        =				[self.sep_token_id]
           lowerCamelCase__        =				[self.cls_token_id]

           if token_ids_a is None:
                 return len(cls + token_ids_a + sep			) * [0]
           return len(cls + token_ids_a + sep + sep + token_ids_a + sep			) * [0]