




import colorsys
import io

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

from utils import img_tensorize


__A    :				List[str]    						=	1_0_0_0




class       UpperCAmelCase_   :




							'''simple docstring'''



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

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

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





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

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





							def  _UpperCAmelCase  (       self							:						str							,  a							:						Dict							,  a							:						Optional[Any]							,  a							:						int      )      ->       Union[str, Any]:
										SCREAMING_SNAKE_CASE  ,	SCREAMING_SNAKE_CASE  ,	SCREAMING_SNAKE_CASE  ,	SCREAMING_SNAKE_CASE     =       box
										SCREAMING_SNAKE_CASE     =       (xa, ya)
										SCREAMING_SNAKE_CASE     =       (ya - ya) * (xa - xa)
										SCREAMING_SNAKE_CASE     =       _SMALL_OBJ * self.scale
										if instance_area < small or ya - ya < 40 * self.scale:
													if ya >= self.height - 5:
																SCREAMING_SNAKE_CASE     =       (xa, ya)
													else:
																SCREAMING_SNAKE_CASE     =       (xa, ya)

										SCREAMING_SNAKE_CASE     =       (ya - ya) / np.sqrt(self.height * self.width      )
										SCREAMING_SNAKE_CASE     =       self._change_color_brightness(a							,  brightness_factor=0.7      )
										SCREAMING_SNAKE_CASE     =       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							:						Dict							,  a							:						int							,  a							:						Optional[int]							,  a							:						Optional[int]="g"							,  a							:						Any="left"							,  )      ->       Any:
										SCREAMING_SNAKE_CASE     =       0
										SCREAMING_SNAKE_CASE     =       self.font_size
										SCREAMING_SNAKE_CASE     =       np.maximum(list(mplc.to_rgb(a      )      )							,  0.2      )
										SCREAMING_SNAKE_CASE     =       max(0.8							,  np.max(a      )      )
										SCREAMING_SNAKE_CASE     =       {
										    """facecolor""": """black""",
										    """alpha""": self.alpha,
										    """pad""": self.pad,
										    """edgecolor""": """none""",
										}
										SCREAMING_SNAKE_CASE  ,	SCREAMING_SNAKE_CASE     =       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							:						str							,  a							:						int=None      )      ->       Optional[int]:
										if saveas is None:
													SCREAMING_SNAKE_CASE     =       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							:						str							,  a							:						int							,  a							:						int							,  a							:						Optional[int]							,  a							:						Dict      )      ->       Union[str, Any]:
										SCREAMING_SNAKE_CASE     =       [self.idaobj[i] for i in classes]
										SCREAMING_SNAKE_CASE     =       [self.idaattr[i] for i in attr_classes]
										SCREAMING_SNAKE_CASE     =       [
										    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							:						Optional[Any]							,  a							:						Dict							,  a							:						Any      )      ->       Optional[Any]:
										SCREAMING_SNAKE_CASE     =       [self.idaobj[i] for i in classes]
										if scores is not None:
													if labels is None:
																SCREAMING_SNAKE_CASE     =       ["""{:.0f}%""".format(s * 100      ) for s in scores]
													else:
																SCREAMING_SNAKE_CASE     =       ["""{} {:.0f}%""".format(a							,  s * 100      ) for li, s in zip(a							,  a      )]
										return labels





							def  _UpperCAmelCase  (       self							:						Union[str, Any]							,  a							:						str=255      )      ->       str:
										SCREAMING_SNAKE_CASE     =       np.random.randint(0							,  len(_COLORS      )      )
										SCREAMING_SNAKE_CASE     =       _COLORS[idx] * maximum
										if not self.rgb:
													SCREAMING_SNAKE_CASE     =       ret[::-1]
										return ret





							def  _UpperCAmelCase  (       self							:						Optional[int]      )      ->       Dict:
										if not self.pynb:
													SCREAMING_SNAKE_CASE  ,	SCREAMING_SNAKE_CASE     =       self.canvas.print_to_buffer()
													if (width, height) != (self.width, self.height):
																SCREAMING_SNAKE_CASE     =       cva.resize(self.img							,  (width, height)      )
													else:
																SCREAMING_SNAKE_CASE     =       self.img
										else:
													SCREAMING_SNAKE_CASE     =       io.BytesIO()  # works for cairo backend
													self.canvas.print_rgba(a      )
													SCREAMING_SNAKE_CASE  ,	SCREAMING_SNAKE_CASE     =       self.width, self.height
													SCREAMING_SNAKE_CASE     =       buf.getvalue()
													SCREAMING_SNAKE_CASE     =       self.img

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

										try:
													import numexpr as ne  # fuse them with numexpr

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

										return visualized_image.astype("""uint8"""      )







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





__A    :				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)
)












import argparse

from transformers import ConvBertConfig, ConvBertModel, TFConvBertModel, load_tf_weights_in_convbert
from transformers.utils import logging


logging.set_verbosity_info()
def        lowerCamelCase_     (     SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE ):
			'''simple docstring'''
			SCREAMING_SNAKE_CASE     =       ConvBertConfig.from_json_file(SCREAMING_SNAKE_CASE )
			SCREAMING_SNAKE_CASE     =       ConvBertModel(SCREAMING_SNAKE_CASE )

			SCREAMING_SNAKE_CASE     =       load_tf_weights_in_convbert(SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE       ,						SCREAMING_SNAKE_CASE )
			model.save_pretrained(SCREAMING_SNAKE_CASE )

			SCREAMING_SNAKE_CASE     =       TFConvBertModel.from_pretrained(SCREAMING_SNAKE_CASE       ,						from_pt=SCREAMING_SNAKE_CASE )
			tf_model.save_pretrained(SCREAMING_SNAKE_CASE )


if __name__ == "__main__":
		__A    :				str    						=	argparse.ArgumentParser()
		# Required parameters
		parser.add_argument(
		    """--tf_checkpoint_path""", default=None, type=str, required=True, help="""Path to the TensorFlow checkpoint path."""
		)
		parser.add_argument(
		    """--convbert_config_file""",
		    default=None,
		    type=str,
		    required=True,
		    help=(
		        """The config json file corresponding to the pre-trained ConvBERT model. \n"""
		        """This specifies the model architecture."""
		    ),
		)
		parser.add_argument(
		    """--pytorch_dump_path""", default=None, type=str, required=True, help="""Path to the output PyTorch model."""
		)
		__A    :				List[Any]    						=	parser.parse_args()
		convert_orig_tfa_checkpoint_to_pytorch(args.tf_checkpoint_path, args.convbert_config_file, args.pytorch_dump_path)






