from collections import Counter
from pathlib import Path
from typing import Optional, Tuple

import yaml

class    snake_case       (   yaml.SafeLoader    ):




  def 						__lowercase(   self  :						Any  ,			a_  :						Dict					)->							Any:




       """simple docstring"""
       SCREAMING_SNAKE_CASE__					:					str      =		[self.constructed_objects[key_node] for key_node, _ in node.value]
       SCREAMING_SNAKE_CASE__					:					List[Any]      =		[tuple(a_					) if isinstance(a_  ,			a_					) else key for key in keys]
       SCREAMING_SNAKE_CASE__					:					Union[str, Any]      =		Counter(a_					)
       SCREAMING_SNAKE_CASE__					:					Optional[int]      =		[key for key in counter if counter[key] > 1]
       if duplicate_keys:
            raise TypeError(F'''Got duplicate yaml keys: {duplicate_keys}'''					)




  def 						__lowercase(   self  :						Any  ,			a_  :						Union[str, Any]  ,			a_  :						Optional[Any]=False					)->							Union[str, Any]:




       """simple docstring"""
       SCREAMING_SNAKE_CASE__					:					int      =		super().construct_mapping(a_  ,			deep=a_					)
       self._check_no_duplicates_on_constructed_node(a_					)
       return mapping







def      _a					(   lowercase__	:      str			):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__					:					Union[str, Any]      =		list(readme_content.splitlines()			)
     if full_content and full_content[0] == "---" and "---" in full_content[1:]:
          SCREAMING_SNAKE_CASE__					:					int      =		full_content[1:].index('---'			) + 1
          SCREAMING_SNAKE_CASE__					:					List[Any]      =		'\n'.join(full_content[1:sep_idx]			)
          return yamlblock, "\n".join(full_content[sep_idx + 1 :]			)

     return None, "\n".join(lowercase__			)

class    snake_case       (   UpperCamelCase_    ):
  # class attributes
  lowercase_								=  {'train_eval_index'}  # train-eval-index in the YAML metadata




  @classmethod
  def 						__lowercase(   cls  :						Tuple  ,			a_  :						Path					)->							"DatasetMetadata":




       """simple docstring"""
       with open(a_  ,			encoding='utf-8'					) as readme_file:
            SCREAMING_SNAKE_CASE__      ,				SCREAMING_SNAKE_CASE__					:					Optional[Any]      =		_split_yaml_from_readme(readme_file.read()					)
       if yaml_string is not None:
            return cls.from_yaml_string(a_					)
       else:
            return cls()




  def 						__lowercase(   self  :						Union[str, Any]  ,			a_  :						Path					)->							Union[str, Any]:




       """simple docstring"""
       if path.exists():
            with open(a_  ,			encoding='utf-8'					) as readme_file:
                 SCREAMING_SNAKE_CASE__					:					Dict      =		readme_file.read()
       else:
            SCREAMING_SNAKE_CASE__					:					Optional[Any]      =		None
       SCREAMING_SNAKE_CASE__					:					int      =		self._to_readme(a_					)
       with open(a_  ,			'w'  ,			encoding='utf-8'					) as readme_file:
            readme_file.write(a_					)




  def 						__lowercase(   self  :						str  ,			a_  :						Optional[str] = None					)->							str:




       """simple docstring"""
       if readme_content is not None:
            SCREAMING_SNAKE_CASE__      ,				SCREAMING_SNAKE_CASE__					:					List[str]      =		_split_yaml_from_readme(a_					)
            SCREAMING_SNAKE_CASE__					:					Tuple      =		'---\n' + self.to_yaml_string() + '---\n' + content
       else:
            SCREAMING_SNAKE_CASE__					:					List[str]      =		'---\n' + self.to_yaml_string() + '---\n'
       return full_content




  @classmethod
  def 						__lowercase(   cls  :						List[str]  ,			a_  :						str					)->							"DatasetMetadata":




       """simple docstring"""
       SCREAMING_SNAKE_CASE__					:					str      =		yaml.load(a_  ,			Loader=_NoDuplicateSafeLoader					) or {}

       # Convert the YAML keys to DatasetMetadata fields
       SCREAMING_SNAKE_CASE__					:					Tuple      =		{
           (key.replace('-'  ,			'_'					) if key.replace('-'  ,			'_'					) in cls._FIELDS_WITH_DASHES else key): value
           for key, value in metadata_dict.items()
       }
       return cls(**a_					)




  def 						__lowercase(   self  :						List[str]					)->							str:




       """simple docstring"""
       return yaml.safe_dump(
           {
               (key.replace('_'  ,			'-'					) if key in self._FIELDS_WITH_DASHES else key): value
               for key, value in self.items()
           }  ,			sort_keys=a_  ,			allow_unicode=a_  ,			encoding='utf-8'  ,			).decode('utf-8'					)




SCREAMING_SNAKE_CASE__		:       Optional[int]       						=       {
    "image-classification": [],
    "translation": [],
    "image-segmentation": [],
    "fill-mask": [],
    "automatic-speech-recognition": [],
    "token-classification": [],
    "sentence-similarity": [],
    "audio-classification": [],
    "question-answering": [],
    "summarization": [],
    "zero-shot-classification": [],
    "table-to-text": [],
    "feature-extraction": [],
    "other": [],
    "multiple-choice": [],
    "text-classification": [],
    "text-to-image": [],
    "text2text-generation": [],
    "zero-shot-image-classification": [],
    "tabular-classification": [],
    "tabular-regression": [],
    "image-to-image": [],
    "tabular-to-text": [],
    "unconditional-image-generation": [],
    "text-retrieval": [],
    "text-to-speech": [],
    "object-detection": [],
    "audio-to-audio": [],
    "text-generation": [],
    "conversational": [],
    "table-question-answering": [],
    "visual-question-answering": [],
    "image-to-text": [],
    "reinforcement-learning": [],
    "voice-activity-detection": [],
    "time-series-forecasting": [],
    "document-question-answering": [],
}


if __name__ == "__main__":
      from argparse import ArgumentParser

      SCREAMING_SNAKE_CASE__		:       str       						=       ArgumentParser(usage="Validate the yaml metadata block of a README.md file.")
      ap.add_argument("readme_filepath")
      SCREAMING_SNAKE_CASE__		:       Union[str, Any]       						=       ap.parse_args()

      SCREAMING_SNAKE_CASE__		:       Union[str, Any]       						=       Path(args.readme_filepath)
      SCREAMING_SNAKE_CASE__		:       List[str]       						=       DatasetMetadata.from_readme(readme_filepath)
      print(dataset_metadata)
      dataset_metadata.to_readme(readme_filepath)








from manim import *






class     __a			(  SCREAMING_SNAKE_CASE					):



	def 		UpperCamelCase				(    self				:     Tuple)->				Dict:
						__lowerCAmelCase						 =Rectangle(height=0.5					,						width=0.5)
						__lowerCAmelCase						 =Rectangle(height=0.4_6					,						width=0.4_6).set_stroke(width=0)

						__lowerCAmelCase						 =[mem.copy() for i in range(6)]
						__lowerCAmelCase						 =[mem.copy() for i in range(6)]
						__lowerCAmelCase						 =VGroup(*snake_case_).arrange(snake_case_					,						buff=0)
						__lowerCAmelCase						 =VGroup(*snake_case_).arrange(snake_case_					,						buff=0)
						__lowerCAmelCase						 =VGroup(snake_case_					,						snake_case_).arrange(snake_case_					,						buff=0)
						__lowerCAmelCase						 =Text("""CPU"""					,						font_size=24)
						__lowerCAmelCase						 =Group(snake_case_					,						snake_case_).arrange(snake_case_					,						buff=0.5					,						aligned_edge=snake_case_)
						cpu.move_to([-2.5, -0.5, 0])
						self.add(snake_case_)

						__lowerCAmelCase						 =[mem.copy() for i in range(1)]
						__lowerCAmelCase						 =VGroup(*snake_case_).arrange(snake_case_					,						buff=0)
						__lowerCAmelCase						 =Text("""GPU"""					,						font_size=24)
						__lowerCAmelCase						 =Group(snake_case_					,						snake_case_).arrange(snake_case_					,						buff=0.5					,						aligned_edge=snake_case_)
						gpu.align_to(snake_case_					,						snake_case_)
						gpu.set_x(gpu.get_x() - 1)

						self.add(snake_case_)

						__lowerCAmelCase						 =[mem.copy() for i in range(6)]
						__lowerCAmelCase						 =VGroup(*snake_case_).arrange(snake_case_					,						buff=0)

						__lowerCAmelCase						 =Text("""Model"""					,						font_size=24)
						__lowerCAmelCase						 =Group(snake_case_					,						snake_case_).arrange(snake_case_					,						buff=0.5					,						aligned_edge=snake_case_)
						model.move_to([3, -1.0, 0])

						self.play(
						    Create(snake_case_					,						run_time=1)					,						Create(snake_case_					,						run_time=1)					,						Create(snake_case_					,						run_time=1)					,						)

						__lowerCAmelCase						 =MarkupText(
						    F"""First, an empty model skeleton is loaded\ninto <span fgcolor='{YELLOW}'>memory</span> without using much RAM."""					,						font_size=24					,						)

						__lowerCAmelCase						 =Square(side_length=2.2)
						key.move_to([-5, 2, 0])

						__lowerCAmelCase						 =MarkupText(
						    F"""<b>Key:</b>\n\n<span fgcolor='{YELLOW}'>●</span> Empty Model"""					,						font_size=18					,						)

						key_text.move_to([-5, 2.4, 0])

						step_a.move_to([2, 2, 0])
						self.play(Write(snake_case_					,						run_time=2.5)					,						Write(snake_case_)					,						Write(snake_case_))

						self.add(snake_case_)

						__lowerCAmelCase						 =[]
						__lowerCAmelCase						 =[]
						__lowerCAmelCase						 =[]
						for i, rect in enumerate(snake_case_):
											__lowerCAmelCase						 =Rectangle(height=0.4_6					,						width=0.4_6).set_stroke(width=0.0).set_fill(snake_case_					,						opacity=0.7)
											cpu_target.move_to(snake_case_)
											cpu_target.generate_target()
											__lowerCAmelCase						 =0.4_6 / 4
											__lowerCAmelCase						 =0.4_6 / 3

											if i == 0:
																cpu_target.target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT)					,						buff=0.0_2					,						direction=snake_case_)
																cpu_target.target.set_x(cpu_target.target.get_x() + 0.1)
											elif i == 3:
																cpu_target.target.next_to(cpu_targs[0].target					,						direction=snake_case_					,						buff=0.0)
											else:
																cpu_target.target.next_to(cpu_targs[i - 1].target					,						direction=snake_case_					,						buff=0.0)
											cpu_targs.append(snake_case_)

											first_animations.append(rect.animate(run_time=0.5).set_stroke(snake_case_))
											second_animations.append(MoveToTarget(snake_case_					,						run_time=1.5))

						self.play(*snake_case_)
						self.play(*snake_case_)

						self.wait()




