'''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       :     Union[str, Any]			=    1_000



class   UpperCamelCase					:







    """simple docstring"""





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


         """simple docstring"""







         if isinstance(UpperCAmelCase_							,							torch.Tensor):
              a					:							int							= img.numpy().astype('np.uint8')
         if isinstance(UpperCAmelCase_							,							UpperCAmelCase_):
              a					:							Optional[int]							= img_tensorize(UpperCAmelCase_)
         assert isinstance(UpperCAmelCase_							,							np.ndarray)

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

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





    def    SCREAMING_SNAKE_CASE_     (					self     :						Tuple							,							UpperCAmelCase_     :						List[str]							,							UpperCAmelCase_     :						Dict=None):


         """simple docstring"""







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





    def    SCREAMING_SNAKE_CASE_     (					self     :						Dict							,							UpperCAmelCase_     :						int							,							UpperCAmelCase_     :						Optional[Any]=None							,							UpperCAmelCase_     :						Union[str, Any]=None							,							UpperCAmelCase_     :						Optional[Any]=None							,							UpperCAmelCase_     :						Union[str, Any]=None):


         """simple docstring"""







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

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





    def    SCREAMING_SNAKE_CASE_     (					self     :						Optional[int]							,							UpperCAmelCase_     :						int							,							UpperCAmelCase_     :						Optional[int]							,							UpperCAmelCase_     :						int):


         """simple docstring"""







         a							,			a							,			a							,			a					:							Any							= box
         a					:							List[Any]							= (xa, ya)
         a					:							List[Any]							= (ya - ya) * (xa - xa)
         a					:							str							= _SMALL_OBJ * self.scale
         if instance_area < small or ya - ya < 4_0 * self.scale:
              if ya >= self.height - 5:
                   a					:							int							= (xa, ya)
              else:
                   a					:							List[Any]							= (xa, ya)

         a					:							str							= (ya - ya) / np.sqrt(self.height * self.width)
         a					:							Union[str, Any]							= self._change_color_brightness(UpperCAmelCase_							,							brightness_factor=0.7)
         a					:							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=UpperCAmelCase_							,							position=UpperCAmelCase_							,							color=UpperCAmelCase_							,							)





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


         """simple docstring"""







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





    def    SCREAMING_SNAKE_CASE_     (					self     :						Any							,							UpperCAmelCase_     :						Optional[Any]=None):


         """simple docstring"""







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





    def    SCREAMING_SNAKE_CASE_     (					self     :						Optional[int]							,							UpperCAmelCase_     :						Union[str, Any]							,							UpperCAmelCase_     :						int							,							UpperCAmelCase_     :						int							,							UpperCAmelCase_     :						Any):


         """simple docstring"""







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





    def    SCREAMING_SNAKE_CASE_     (					self     :						List[str]							,							UpperCAmelCase_     :						Any							,							UpperCAmelCase_     :						Dict):


         """simple docstring"""







         a					:							Union[str, Any]							= [self.idaobj[i] for i in classes]
         if scores is not None:
              if labels is None:
                   a					:							Optional[int]							= ['{:.0f}%'.format(s * 1_0_0) for s in scores]
              else:
                   a					:							str							= ['{} {:.0f}%'.format(UpperCAmelCase_							,							s * 1_0_0) for li, s in zip(UpperCAmelCase_							,							UpperCAmelCase_)]
         return labels





    def    SCREAMING_SNAKE_CASE_     (					self     :						Dict							,							UpperCAmelCase_     :						List[Any]=2_5_5):


         """simple docstring"""







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





    def    SCREAMING_SNAKE_CASE_     (					self     :						Optional[Any]):


         """simple docstring"""







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

         a					:							Dict							= np.frombuffer(UpperCAmelCase_							,							dtype='uint8')
         a					:							Optional[int]							= buffer.reshape(UpperCAmelCase_							,							UpperCAmelCase_							,							4)
         a							,			a					:							List[Any]							= np.split(UpperCAmelCase_							,							[3]							,							axis=2)

         try:
              import numexpr as ne  # fuse them with numexpr

              a					:							Union[str, Any]							= ne.evaluate('img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)')
         except ImportError:
              a					:							Dict							= alpha.astype('float32') / 2_55.0
              a					:							List[Any]							= img * (1 - alpha) + rgb * alpha

         return visualized_image.astype('uint8')







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


         """simple docstring"""







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






UpperCamelCase       :     int			=    (
    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 glob
import os

from get_test_info import get_tester_classes


if __name__ == "__main__":
      UpperCamelCase       :     List[Any]			=    []

      UpperCamelCase       :     Tuple			=    os.path.join("""tests""", """models""", """**""", """test_modeling_*.py""")
      UpperCamelCase       :     List[str]			=    glob.glob(pattern)
      # TODO: deal with TF/Flax too
      UpperCamelCase       :     List[Any]			=    [
          x for x in test_files if not (x.startswith("""test_modeling_tf_""") or x.startswith("""test_modeling_flax_"""))
      ]

      for test_file in test_files:
            UpperCamelCase       :     List[str]			=    get_tester_classes(test_file)
            for tester_class in tester_classes:
                  # A few tester classes don't have `parent` parameter in `__init__`.
                  # TODO: deal this better
                  try:
                        UpperCamelCase       :     int			=    tester_class(parent=None)
                  except Exception:
                        continue
                  if hasattr(tester, """get_config"""):
                        UpperCamelCase       :     Union[str, Any]			=    tester.get_config()
                        for k, v in config.to_dict().items():
                              if isinstance(v, int):
                                    UpperCamelCase       :     List[Any]			=    None
                                    if k in ["vocab_size"]:
                                          UpperCamelCase       :     List[Any]			=    100
                                    elif k in ["max_position_embeddings"]:
                                          UpperCamelCase       :     Tuple			=    128
                                    elif k in ["hidden_size", "d_model"]:
                                          UpperCamelCase       :     Any			=    40
                                    elif k == ["num_layers", "num_hidden_layers", "num_encoder_layers", "num_decoder_layers"]:
                                          UpperCamelCase       :     Tuple			=    5
                                    if target is not None and v > target:
                                          failures.append(
                                              f'''{tester_class.__name__} will produce a `config` of type `{config.__class__.__name__}`'''
                                              f''' with config["{k}"] = {v} which is too large for testing! Set its value to be smaller'''
                                              f''' than {target}.'''
                                          )

      if len(failures) > 0:
            raise Exception(f'''There were {len(failures)} failures:\n''' + """\n""".join(failures))

