import colorsys
import io

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

from utils import img_tensorize


UpperCAmelCase							=       1_0_0_0



class 					snake_case__       :



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




         '''simple docstring'''




         if isinstance(__a			,	torch.Tensor   ):
               snake_case_     :			Dict       =       img.numpy().astype("np.uint8"   )
         if isinstance(__a			,	__a   ):
               snake_case_     :			Tuple       =       img_tensorize(__a   )
         assert isinstance(__a			,	np.ndarray   )

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

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



   def 					UpperCAmelCase__       (				self   :   int			,	A__   :   Union[str, Any]			,	A__   :   List[str]=None   )							->     Any:




         '''simple docstring'''




         if color is None:
               snake_case_     :			Any       =       self.edgecolor
         (snake_case_)     :			Optional[int]       =       box
         snake_case_     :			Any       =       xa - xa
         snake_case_     :			Tuple       =       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 					UpperCAmelCase__       (				self   :   str			,	A__   :   int			,	A__   :   Tuple=None			,	A__   :   Union[str, Any]=None			,	A__   :   int=None			,	A__   :   Union[str, Any]=None   )							->     Optional[Any]:




         '''simple docstring'''




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

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



   def 					UpperCAmelCase__       (				self   :   List[str]			,	A__   :   str			,	A__   :   Any			,	A__   :   Tuple   )							->     Optional[int]:




         '''simple docstring'''




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

         snake_case_     :			List[str]       =       (ya - ya) / np.sqrt(self.height * self.width   )
         snake_case_     :			Dict       =       self._change_color_brightness(__a			,	brightness_factor=0.7   )
         snake_case_     :			Optional[Any]       =       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 					UpperCAmelCase__       (				self   :   List[str]			,	A__   :   Union[str, Any]			,	A__   :   Dict			,	A__   :   int="g"			,	A__   :   int="left"			,	)							->     Any:




         '''simple docstring'''




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



   def 					UpperCAmelCase__       (				self   :   Union[str, Any]			,	A__   :   Optional[int]=None   )							->     Tuple:




         '''simple docstring'''




         if saveas is None:
               snake_case_     :			Optional[int]       =       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 					UpperCAmelCase__       (				self   :   Tuple			,	A__   :   Optional[Any]			,	A__   :   Tuple			,	A__   :   Dict			,	A__   :   Optional[int]   )							->     Any:




         '''simple docstring'''




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



   def 					UpperCAmelCase__       (				self   :   Any			,	A__   :   Union[str, Any]			,	A__   :   Optional[int]   )							->     str:




         '''simple docstring'''




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



   def 					UpperCAmelCase__       (				self   :   List[Any]			,	A__   :   Optional[int]=2_55   )							->     List[Any]:




         '''simple docstring'''




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



   def 					UpperCAmelCase__       (				self   :   Optional[int]   )							->     List[str]:




         '''simple docstring'''




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

         snake_case_     :			List[Any]       =       np.frombuffer(__a			,	dtype="uint8"   )
         snake_case_     :			Union[str, Any]       =       buffer.reshape(__a			,	__a			,	4   )
         snake_case_     :			List[Any]       =       np.split(__a			,	[3]			,	axis=2   )

         try:
               import numexpr as ne  # fuse them with numexpr

               snake_case_     :			List[str]       =       ne.evaluate("img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)"   )
         except ImportError:
               snake_case_     :			List[Any]       =       alpha.astype("float32"   ) / 255.0
               snake_case_     :			Any       =       img * (1 - alpha) + rgb * alpha

         return visualized_image.astype("uint8"   )



   def 					UpperCAmelCase__       (				self   :   List[str]			,	A__   :   List[str]			,	A__   :   Optional[Any]   )							->     Tuple:




         '''simple docstring'''




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


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




from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging


UpperCAmelCase							=       logging.get_logger(__name__)

UpperCAmelCase							=       {
    "uclanlp/plbart-base": "https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json",
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}



class 					snake_case__       (				_UpperCamelCase							):
   _SCREAMING_SNAKE_CASE	: List[str]						    =      "plbart"
   _SCREAMING_SNAKE_CASE	: Union[str, Any]						    =      ["past_key_values"]
   _SCREAMING_SNAKE_CASE	: Dict						    =      {"num_attention_heads": "encoder_attention_heads", "hidden_size": "d_model"}



   def __init__(				self   :   Dict			,	A__   :   Any=5_00_05			,	A__   :   Optional[int]=10_24			,	A__   :   Tuple=6			,	A__   :   Optional[Any]=30_72			,	A__   :   Dict=12			,	A__   :   Union[str, Any]=6			,	A__   :   Union[str, Any]=30_72			,	A__   :   Tuple=12			,	A__   :   List[str]=0.0			,	A__   :   Dict=0.0			,	A__   :   int=True			,	A__   :   Tuple=True			,	A__   :   List[str]="gelu"			,	A__   :   List[Any]=7_68			,	A__   :   Optional[Any]=0.1			,	A__   :   List[Any]=0.1			,	A__   :   Any=0.0			,	A__   :   int=0.02			,	A__   :   Optional[Any]=0.0			,	A__   :   List[str]=True			,	A__   :   Any=1			,	A__   :   Tuple=0			,	A__   :   Any=2			,	A__   :   int=2			,	**A__   :   Dict			,	)							->     int:




         '''simple docstring'''




         snake_case_     :			int       =       vocab_size
         snake_case_     :			List[Any]       =       max_position_embeddings
         snake_case_     :			str       =       d_model
         snake_case_     :			Tuple       =       encoder_ffn_dim
         snake_case_     :			Union[str, Any]       =       encoder_layers
         snake_case_     :			Dict       =       encoder_attention_heads
         snake_case_     :			Union[str, Any]       =       decoder_ffn_dim
         snake_case_     :			Union[str, Any]       =       decoder_layers
         snake_case_     :			List[str]       =       decoder_attention_heads
         snake_case_     :			List[Any]       =       dropout
         snake_case_     :			Union[str, Any]       =       attention_dropout
         snake_case_     :			Optional[int]       =       activation_dropout
         snake_case_     :			List[str]       =       activation_function
         snake_case_     :			Tuple       =       init_std
         snake_case_     :			str       =       encoder_layerdrop
         snake_case_     :			int       =       decoder_layerdrop
         snake_case_     :			Optional[int]       =       classifier_dropout
         snake_case_     :			List[str]       =       use_cache
         snake_case_     :			List[Any]       =       encoder_layers
         snake_case_     :			Tuple       =       scale_embedding  # scale factor will be sqrt(d_model) if True
         super().__init__(
             pad_token_id=A__			,	bos_token_id=A__			,	eos_token_id=A__			,	is_encoder_decoder=A__			,	forced_eos_token_id=A__			,	**A__			,	)



class 					snake_case__       (				_UpperCamelCase							):



   @property
   def 					UpperCAmelCase__       (				self   :   str   )							->     Mapping[str, Mapping[int, str]]:




         '''simple docstring'''




         return OrderedDict(
             [
                 ("input_ids", {0: "batch", 1: "sequence"}),
                 ("attention_mask", {0: "batch", 1: "sequence"}),
             ]   )



   @property
   def 					UpperCAmelCase__       (				self   :   List[str]   )							->     Mapping[str, Mapping[int, str]]:




         '''simple docstring'''




         if self.use_past:
               return OrderedDict(
                   [
                       ("last_hidden_state", {0: "batch", 1: "sequence"}),
                       ("past_keys", {0: "batch", 2: "sequence"}),
                       ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
                   ]   )
         else:
               return OrderedDict(
                   [
                       ("last_hidden_state", {0: "batch", 1: "sequence"}),
                       ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
                   ]   )



