




'''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


A							:				Any			     =	1_000






class 	SCREAMING_SNAKE_CASE:

       def __init__(   self ,		lowerCamelCase__ ,		lowerCamelCase__=1.2 ,		lowerCamelCase__="g" ,		lowerCamelCase__=0.5 ,		lowerCamelCase__="-" ,		lowerCamelCase__="test_out.jpg" ,		lowerCamelCase__=True ,		lowerCamelCase__=False ,		lowerCamelCase__=None ,		lowerCamelCase__=None ,		lowerCamelCase__=0.7 ,		)   -> List[str]:

           """simple docstring"""



           if isinstance(lowerCamelCase__ ,		torch.Tensor					):
               __lowercase          =						img.numpy().astype("""np.uint8"""					)
           if isinstance(lowerCamelCase__ ,		lowerCamelCase__					):
               __lowercase          =						img_tensorize(lowerCamelCase__					)
           assert isinstance(lowerCamelCase__ ,		np.ndarray					)

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

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

       def    snake_case__      (   self ,		lowerCamelCase__ ,		lowerCamelCase__=None					)   -> Tuple:

           """simple docstring"""



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

       def    snake_case__      (   self ,		lowerCamelCase__ ,		lowerCamelCase__=None ,		lowerCamelCase__=None ,		lowerCamelCase__=None ,		lowerCamelCase__=None					)   -> List[Any]:

           """simple docstring"""



           if len(boxes.shape					) > 2:
               __lowercase          =						boxes[0]
           if len(obj_ids.shape					) > 1:
               __lowercase          =						obj_ids[0]
           if len(obj_scores.shape					) > 1:
               __lowercase          =						obj_scores[0]
           if len(attr_ids.shape					) > 1:
               __lowercase          =						attr_ids[0]
           if len(attr_scores.shape					) > 1:
               __lowercase          =						attr_scores[0]
           if isinstance(lowerCamelCase__ ,		torch.Tensor					):
               __lowercase          =						boxes.numpy()
           if isinstance(lowerCamelCase__ ,		lowerCamelCase__					):
               __lowercase          =						np.array(lowerCamelCase__					)
           assert isinstance(lowerCamelCase__ ,		np.ndarray					)
           __lowercase          =						np.prod(boxes[:, 2:] - boxes[:, :2] ,		axis=1					)
           __lowercase          =						np.argsort(-areas					).tolist()
           __lowercase          =						boxes[sorted_idxs] if boxes is not None else None
           __lowercase          =						obj_ids[sorted_idxs] if obj_ids is not None else None
           __lowercase          =						obj_scores[sorted_idxs] if obj_scores is not None else None
           __lowercase          =						attr_ids[sorted_idxs] if attr_ids is not None else None
           __lowercase          =						attr_scores[sorted_idxs] if attr_scores is not None else None

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

       def    snake_case__      (   self ,		lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__					)   -> Any:

           """simple docstring"""



           __lowercase          =						box
           __lowercase          =						(xa, ya)
           __lowercase          =						(ya - ya) * (xa - xa)
           __lowercase          =						_SMALL_OBJ * self.scale
           if instance_area < small or ya - ya < 40 * self.scale:
               if ya >= self.height - 5:
                   __lowercase          =						(xa, ya)
               else:
                   __lowercase          =						(xa, ya)

           __lowercase          =						(ya - ya) / np.sqrt(self.height * self.width					)
           __lowercase          =						self._change_color_brightness(lowerCamelCase__ ,		brightness_factor=0.7					)
           __lowercase          =						np.clip((height_ratio - 0.02) / 0.08 + 1 ,		1.2 ,		2					)
           font_size *= 0.75 * self.font_size

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

       def    snake_case__      (   self ,		lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__="g" ,		lowerCamelCase__="left" ,		)   -> Dict:

           """simple docstring"""



           __lowercase          =						0
           __lowercase          =						self.font_size
           __lowercase          =						np.maximum(list(mplc.to_rgb(lowerCamelCase__					)					) ,		0.2					)
           __lowercase          =						max(0.8 ,		np.max(lowerCamelCase__					)					)
           __lowercase          =						{
               "facecolor": "black",
               "alpha": self.alpha,
               "pad": self.pad,
               "edgecolor": "none",
           }
           __lowercase          =						position
           self.ax.text(
               lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__ ,		size=font_size * self.scale ,		family="""sans-serif""" ,		bbox=lowerCamelCase__ ,		verticalalignment="""top""" ,		horizontalalignment=lowerCamelCase__ ,		color=lowerCamelCase__ ,		zorder=10 ,		rotation=lowerCamelCase__ ,		)

       def    snake_case__      (   self ,		lowerCamelCase__=None					)   -> Union[str, Any]:

           """simple docstring"""



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

       def    snake_case__      (   self ,		lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__					)   -> Tuple:

           """simple docstring"""



           __lowercase          =						[self.idaobj[i] for i in classes]
           __lowercase          =						[self.idaattr[i] for i in attr_classes]
           __lowercase          =						[
               F'{label} {score:.2f} {attr} {attr_score:.2f}'
               for label, score, attr, attr_score in zip(lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__ ,		lowerCamelCase__					)
           ]
           return labels

       def    snake_case__      (   self ,		lowerCamelCase__ ,		lowerCamelCase__					)   -> Optional[int]:

           """simple docstring"""



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

       def    snake_case__      (   self ,		lowerCamelCase__=255					)   -> str:

           """simple docstring"""



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

       def    snake_case__      (   self					)   -> int:

           """simple docstring"""



           if not self.pynb:
               __lowercase          =						self.canvas.print_to_buffer()
               if (width, height) != (self.width, self.height):
                   __lowercase          =						cva.resize(self.img ,		(width, height)					)
               else:
                   __lowercase          =						self.img
           else:
               __lowercase          =						io.BytesIO()  # works for cairo backend
               self.canvas.print_rgba(lowerCamelCase__					)
               __lowercase          =						self.width, self.height
               __lowercase          =						buf.getvalue()
               __lowercase          =						self.img

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

           try:
               import numexpr as ne  # fuse them with numexpr

               __lowercase          =						ne.evaluate("""img * (1 - alpha / 255.0) + rgb * (alpha / 255.0)"""					)
           except ImportError:
               __lowercase          =						alpha.astype("""float32"""					) / 2_55.0
               __lowercase          =						img * (1 - alpha) + rgb * alpha

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




       def    snake_case__      (   self ,		lowerCamelCase__ ,		lowerCamelCase__					)   -> List[str]:

           """simple docstring"""



           assert brightness_factor >= -1.0 and brightness_factor <= 1.0
           __lowercase          =						mplc.to_rgb(lowerCamelCase__					)
           __lowercase          =						colorsys.rgb_to_hls(*mplc.to_rgb(lowerCamelCase__					)					)
           __lowercase          =						polygon_color[1] + (brightness_factor * polygon_color[1])
           __lowercase          =						0.0 if modified_lightness < 0.0 else modified_lightness
           __lowercase          =						1.0 if modified_lightness > 1.0 else modified_lightness
           __lowercase          =						colorsys.hls_to_rgb(polygon_color[0] ,		lowerCamelCase__ ,		polygon_color[2]					)
           return modified_color





A							:				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'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool


A							:				Dict			     =	"""Here is a text containing a lot of information: '''{text}'''.

Can you answer this question about the text: '{question}'"""






class 	SCREAMING_SNAKE_CASE(    __A					):
       snake_case_			:					List[Any]   = """google/flan-t5-base"""
       snake_case_			:					int   = (
           """This is a tool that answers questions related to a text. It takes two arguments named `text`, which is the """
           """text where to find the answer, and `question`, which is the question, and returns the answer to the question."""
       )
       snake_case_			:					Optional[int]   = """text_qa"""
       snake_case_			:					List[Any]   = AutoTokenizer
       snake_case_			:					List[str]   = AutoModelForSeqaSeqLM

       snake_case_			:					int   = ["""text""", """text"""]
       snake_case_			:					Dict   = ["""text"""]

       def    snake_case__      (   self ,		lowerCamelCase__ ,		lowerCamelCase__					)   -> Optional[int]:

           """simple docstring"""



           __lowercase          =						QA_PROMPT.format(text=lowerCamelCase__ ,		question=lowerCamelCase__					)
           return self.pre_processor(lowerCamelCase__ ,		return_tensors="""pt"""					)

       def    snake_case__      (   self ,		lowerCamelCase__					)   -> int:

           """simple docstring"""



           __lowercase          =						self.model.generate(**lowerCamelCase__					)

           __lowercase    ,__lowercase          =						inputs["""input_ids"""].shape
           __lowercase          =						output_ids.shape[0]

           return output_ids.reshape(lowerCamelCase__ ,		out_b // in_b ,		*output_ids.shape[1:]					)[0][0]




       def    snake_case__      (   self ,		lowerCamelCase__					)   -> Tuple:

           """simple docstring"""



           return self.pre_processor.decode(lowerCamelCase__ ,		skip_special_tokens=lowerCamelCase__ ,		clean_up_tokenization_spaces=lowerCamelCase__					)




