





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

import yaml




class 	UpperCamelCase_							(  yaml.SafeLoader     ):


							def   _snake_case	(				self     :List[str]				,					__A     :List[Any]		) -> Optional[int]:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   [self.constructed_objects[key_node] for key_node, _ in node.value]
									SCREAMING_SNAKE_CASE__								=   [tuple(__A		) if isinstance(__A				,					__A		) else key for key in keys]
									SCREAMING_SNAKE_CASE__								=   Counter(__A		)
									SCREAMING_SNAKE_CASE__								=   [key for key in counter if counter[key] > 1]
									if duplicate_keys:
											raise TypeError(f'''Got duplicate yaml keys: {duplicate_keys}'''		)


							def   _snake_case	(				self     :Optional[int]				,					__A     :List[Any]				,					__A     :Union[str, Any]=False		) -> int:



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   super().construct_mapping(__A				,					deep=__A		)
									self._check_no_duplicates_on_constructed_node(__A		)
									return mapping






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

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




class 	UpperCamelCase_							(  UpperCamelCase__     ):
							# class attributes
							lowerCamelCase_							     =       {"train_eval_index"}  # train-eval-index in the YAML metadata


							@classmethod
							def   _snake_case	(				cls     :int				,					__A     :Path		) -> "DatasetMetadata":



									"""simple docstring"""



									with open(__A				,					encoding="""utf-8"""		) as readme_file:
											SCREAMING_SNAKE_CASE__						,    SCREAMING_SNAKE_CASE__								=   _split_yaml_from_readme(readme_file.read()		)
									if yaml_string is not None:
											return cls.from_yaml_string(__A		)
									else:
											return cls()


							def   _snake_case	(				self     :int				,					__A     :Path		) -> str:



									"""simple docstring"""



									if path.exists():
											with open(__A				,					encoding="""utf-8"""		) as readme_file:
													SCREAMING_SNAKE_CASE__								=   readme_file.read()
									else:
											SCREAMING_SNAKE_CASE__								=   None
									SCREAMING_SNAKE_CASE__								=   self._to_readme(__A		)
									with open(__A				,					"""w"""				,					encoding="""utf-8"""		) as readme_file:
											readme_file.write(__A		)


							def   _snake_case	(				self     :int				,					__A     :Optional[str] = None		) -> str:



									"""simple docstring"""



									if readme_content is not None:
											SCREAMING_SNAKE_CASE__						,    SCREAMING_SNAKE_CASE__								=   _split_yaml_from_readme(__A		)
											SCREAMING_SNAKE_CASE__								=   """---\n""" + self.to_yaml_string() + """---\n""" + content
									else:
											SCREAMING_SNAKE_CASE__								=   """---\n""" + self.to_yaml_string() + """---\n"""
									return full_content


							@classmethod
							def   _snake_case	(				cls     :Tuple				,					__A     :str		) -> "DatasetMetadata":



									"""simple docstring"""



									SCREAMING_SNAKE_CASE__								=   yaml.load(__A				,					Loader=_NoDuplicateSafeLoader		) or {}

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


							def   _snake_case	(				self     :Union[str, Any]		) -> 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"""		)



_lowerCamelCase 					=      {
    '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

	_lowerCamelCase 					=      ArgumentParser(usage='Validate the yaml metadata block of a README.md file.')
	ap.add_argument('readme_filepath')
	_lowerCamelCase 					=      ap.parse_args()

	_lowerCamelCase 					=      Path(args.readme_filepath)
	_lowerCamelCase 					=      DatasetMetadata.from_readme(readme_filepath)
	print(dataset_metadata)
	dataset_metadata.to_readme(readme_filepath)

'''simple docstring'''



from manim import *




class     UpperCAmelCase_	(						_SCREAMING_SNAKE_CASE					):






						'''simple docstring'''






						def    _lowercase      (   self ):

												"""simple docstring"""



												_lowerCAmelCase    		=					Rectangle(height=0.5       ,  width=0.5 )
												_lowerCAmelCase    		=					Rectangle(height=0.46       ,  width=0.46 ).set_stroke(width=0 )

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

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

												self.add(_lowercase )

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

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

												self.play(
												    Create(_lowercase       ,  run_time=1 )       ,  Create(_lowercase       ,  run_time=1 )       ,  Create(_lowercase       ,  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(_lowercase       ,  run_time=2.5 )       ,  Write(_lowercase )       ,  Write(_lowercase ) )

												self.add(_lowercase )

												_lowerCAmelCase    		=					[]
												_lowerCAmelCase    		=					[]
												_lowerCAmelCase    		=					[]
												for i, rect in enumerate(_lowercase ):
																		_lowerCAmelCase    		=					Rectangle(height=0.46       ,  width=0.46 ).set_stroke(width=0.0 ).set_fill(_lowercase       ,  opacity=0.7 )
																		cpu_target.move_to(_lowercase )
																		cpu_target.generate_target()
																		_lowerCAmelCase    		=					0.46 / 4
																		_lowerCAmelCase    		=					0.46 / 3

																		if i == 0:
																								cpu_target.target.next_to(cpu_left_col_base[0].get_corner(DOWN + LEFT )       ,  buff=0.02       ,  direction=_lowercase )
																								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=_lowercase       ,  buff=0.0 )
																		else:
																								cpu_target.target.next_to(cpu_targs[i - 1].target       ,  direction=_lowercase       ,  buff=0.0 )
																		cpu_targs.append(_lowercase )

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

												self.play(*_lowercase )
												self.play(*_lowercase )

												self.wait()
