"""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         =		10_00
class 	__UpperCAmelCase						:







			'''simple docstring'''





			def __init__( self      ,			snake_case_      ,			snake_case_=1.2      ,			snake_case_="g"      ,			snake_case_=0.5      ,			snake_case_="-"      ,			snake_case_="test_out.jpg"      ,			snake_case_=True      ,			snake_case_=False      ,			snake_case_=None      ,			snake_case_=None      ,			snake_case_=0.7      ,			):







										'''simple docstring'''


										if isinstance(snake_case_      ,			torch.Tensor       ):
																	A__					:    Any														= img.numpy().astype("""np.uint8"""       )
										if isinstance(snake_case_      ,			snake_case_       ):
																	A__					:    Optional[int]														= img_tensorize(snake_case_       )
										assert isinstance(snake_case_      ,			np.ndarray       )

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

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





			def 		lowerCamelCase				( self      ,			snake_case_      ,			snake_case_=None       ):







										'''simple docstring'''


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





			def 		lowerCamelCase				( self      ,			snake_case_      ,			snake_case_=None      ,			snake_case_=None      ,			snake_case_=None      ,			snake_case_=None       ):







										'''simple docstring'''


										if len(boxes.shape       ) > 2:
																	A__					:    Any														= boxes[0]
										if len(obj_ids.shape       ) > 1:
																	A__					:    List[str]														= obj_ids[0]
										if len(obj_scores.shape       ) > 1:
																	A__					:    str														= obj_scores[0]
										if len(attr_ids.shape       ) > 1:
																	A__					:    List[str]														= attr_ids[0]
										if len(attr_scores.shape       ) > 1:
																	A__					:    str														= attr_scores[0]
										if isinstance(snake_case_      ,			torch.Tensor       ):
																	A__					:    Optional[Any]														= boxes.numpy()
										if isinstance(snake_case_      ,			snake_case_       ):
																	A__					:    Any														= np.array(snake_case_       )
										assert isinstance(snake_case_      ,			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__					:    Dict														= obj_ids[sorted_idxs] if obj_ids is not None else None
										A__					:    Optional[int]														= obj_scores[sorted_idxs] if obj_scores is not None else None
										A__					:    int														= attr_ids[sorted_idxs] if attr_ids is not None else None
										A__					:    Any														= attr_scores[sorted_idxs] if attr_scores is not None else None

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





			def 		lowerCamelCase				( self      ,			snake_case_      ,			snake_case_      ,			snake_case_       ):







										'''simple docstring'''


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

										A__					:    List[Any]														= (ya - ya) / np.sqrt(self.height * self.width       )
										A__					:    Optional[int]														= self._change_color_brightness(snake_case_      ,			brightness_factor=0.7       )
										A__					:    Optional[int]														= np.clip((height_ratio - 0.02) / 0.08 + 1      ,			1.2      ,			2       )
										font_size *= 0.75 * self.font_size

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





			def 		lowerCamelCase				( self      ,			snake_case_      ,			snake_case_      ,			snake_case_="g"      ,			snake_case_="left"      ,			):







										'''simple docstring'''


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





			def 		lowerCamelCase				( self      ,			snake_case_=None       ):







										'''simple docstring'''


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





			def 		lowerCamelCase				( self      ,			snake_case_      ,			snake_case_      ,			snake_case_      ,			snake_case_       ):







										'''simple docstring'''


										A__					:    Dict														= [self.idaobj[i] for i in classes]
										A__					:    Optional[int]														= [self.idaattr[i] for i in attr_classes]
										A__					:    str														= [
										    F'''{label} {score:.2f} {attr} {attr_score:.2f}'''
										    for label, score, attr, attr_score in zip(snake_case_      ,			snake_case_      ,			snake_case_      ,			snake_case_       )
										]
										return labels





			def 		lowerCamelCase				( self      ,			snake_case_      ,			snake_case_       ):







										'''simple docstring'''


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





			def 		lowerCamelCase				( self      ,			snake_case_=255       ):







										'''simple docstring'''


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





			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


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

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

										try:
																	import numexpr as ne  # fuse them with numexpr

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

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





			def 		lowerCamelCase				( self      ,			snake_case_      ,			snake_case_       ):







										'''simple docstring'''


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






"""simple docstring"""



import inspect
import os
import unittest

import torch

import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
    execute_subprocess_async,
    require_cpu,
    require_multi_gpu,
    require_single_gpu,
    test_sync,
)
from accelerate.utils import patch_environment
class 	__UpperCAmelCase						(unittest.TestCase    ):







			'''simple docstring'''





			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										A__					:    Optional[int]														= inspect.getfile(accelerate.test_utils       )
										A__					:    Tuple														= os.path.sep.join(mod_file.split(os.path.sep       )[:-1] + ["""scripts""", """test_sync.py"""]       )





			@require_cpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										debug_launcher(test_sync.main      ,			num_processes=1       )





			@require_cpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										debug_launcher(test_sync.main       )





			@require_single_gpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										test_sync.main()





			@require_multi_gpu
			def 		lowerCamelCase				( self       ):







										'''simple docstring'''


										print(F'''Found {torch.cuda.device_count()} devices.'''       )
										A__					:    List[str]														= ["""torchrun""", F'''--nproc_per_node={torch.cuda.device_count()}''', self.test_file_path]
										with patch_environment(omp_num_threads=1       ):
																	execute_subprocess_async(snake_case_      ,			env=os.environ.copy()       )





