'''simple docstring'''





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

import yaml






class 		_lowerCamelCase		(   yaml.SafeLoader    ):
    def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					Any:
     SCREAMING_SNAKE_CASE__:   Any=      [self.constructed_objects[key_node] for key_node, _ in node.value]
     SCREAMING_SNAKE_CASE__:   int=      [tuple(UpperCamelCase__   ) if isinstance(UpperCamelCase__ , UpperCamelCase__   ) else key for key in keys]
     SCREAMING_SNAKE_CASE__:   List[Any]=      Counter(UpperCamelCase__   )
     SCREAMING_SNAKE_CASE__:   Tuple=      [key for key in counter if counter[key] > 1]
     if duplicate_keys:
      raise TypeError(f'Got duplicate yaml keys: {duplicate_keys}'   )



    def 						UpperCamelCase_				(  self , lowerCAmelCase , lowerCAmelCase=False   )       ->					Tuple:
     SCREAMING_SNAKE_CASE__:   Optional[Any]=      super().construct_mapping(UpperCamelCase__ , deep=UpperCamelCase__   )
     self._check_no_duplicates_on_constructed_node(UpperCamelCase__   )
     return mapping







def 			A__      (	snake_case_ :		str      ):
 SCREAMING_SNAKE_CASE__:   List[str]=      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__:   Any=      '''\n'''.join(full_content[1:sep_idx]      )
  return yamlblock, "\n".join(full_content[sep_idx + 1 :]      )

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






class 		_lowerCamelCase		(   lowercase_    ):
    __a  =      {'''train_eval_index'''}  # train-eval-index in the YAML metadata
    @classmethod
    def 						UpperCamelCase_				(  cls , lowerCAmelCase   )       ->					Optional[int]:







     with open(UpperCamelCase__ , 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(UpperCamelCase__   )
     else:
      return cls()
    def 						UpperCamelCase_				(  self , lowerCAmelCase   )       ->					str:







     if path.exists():
      with open(UpperCamelCase__ , encoding='''utf-8'''   ) as readme_file:
       SCREAMING_SNAKE_CASE__:   str=      readme_file.read()
     else:
      SCREAMING_SNAKE_CASE__:   Tuple=      None
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      self._to_readme(UpperCamelCase__   )
     with open(UpperCamelCase__ , '''w''' , encoding='''utf-8'''   ) as readme_file:
      readme_file.write(UpperCamelCase__   )
    def 						UpperCamelCase_				(  self , lowerCAmelCase = None   )       ->					Dict:







     if readme_content is not None:
      SCREAMING_SNAKE_CASE__,	SCREAMING_SNAKE_CASE__:   List[Any]=      _split_yaml_from_readme(UpperCamelCase__   )
      SCREAMING_SNAKE_CASE__:   Any=      '''---\n''' + self.to_yaml_string() + '''---\n''' + content
     else:
      SCREAMING_SNAKE_CASE__:   List[str]=      '''---\n''' + self.to_yaml_string() + '''---\n'''
     return full_content
    @classmethod
    def 						UpperCamelCase_				(  cls , lowerCAmelCase   )       ->					str:
     SCREAMING_SNAKE_CASE__:   Any=      yaml.load(UpperCamelCase__ , Loader=_NoDuplicateSafeLoader   ) or {}

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



    def 						UpperCamelCase_				(  self   )       ->					str:
     return yaml.safe_dump(
         {
             (key.replace('''_''' , '''-'''   ) if key in self._FIELDS_WITH_DASHES else key): value
             for key, value in self.items()
         } , sort_keys=UpperCamelCase__ , allow_unicode=UpperCamelCase__ , encoding='''utf-8''' , ).decode('''utf-8'''   )
lowercase_     :   str 				=				{
    '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

      lowercase_     :   Optional[Any] 				=				ArgumentParser(usage='Validate the yaml metadata block of a README.md file.')
      ap.add_argument('readme_filepath')
      lowercase_     :   Optional[int] 				=				ap.parse_args()

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


import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible






class 		_lowerCamelCase		(   unittest.TestCase    ):
    def 						UpperCamelCase_				(  self   )       ->					str:
     SCREAMING_SNAKE_CASE__:   List[Any]=      [
         '''safety_checker/pytorch_model.bin''',
         '''safety_checker/model.safetensors''',
         '''vae/diffusion_pytorch_model.bin''',
         '''vae/diffusion_pytorch_model.safetensors''',
         '''text_encoder/pytorch_model.bin''',
         '''text_encoder/model.safetensors''',
         '''unet/diffusion_pytorch_model.bin''',
         '''unet/diffusion_pytorch_model.safetensors''',
     ]
     self.assertTrue(is_safetensors_compatible(lowerCAmelCase   )   )
    def 						UpperCamelCase_				(  self   )       ->					int:
     SCREAMING_SNAKE_CASE__:   List[str]=      [
         '''unet/diffusion_pytorch_model.bin''',
         '''unet/diffusion_pytorch_model.safetensors''',
     ]
     self.assertTrue(is_safetensors_compatible(lowerCAmelCase   )   )
    def 						UpperCamelCase_				(  self   )       ->					Tuple:
     SCREAMING_SNAKE_CASE__:   Optional[int]=      [
         '''safety_checker/pytorch_model.bin''',
         '''safety_checker/model.safetensors''',
         '''vae/diffusion_pytorch_model.bin''',
         '''vae/diffusion_pytorch_model.safetensors''',
         '''text_encoder/pytorch_model.bin''',
         '''text_encoder/model.safetensors''',
         '''unet/diffusion_pytorch_model.bin''',
         # Removed: 'unet/diffusion_pytorch_model.safetensors',
     ]
     self.assertFalse(is_safetensors_compatible(lowerCAmelCase   )   )
    def 						UpperCamelCase_				(  self   )       ->					Dict:
     SCREAMING_SNAKE_CASE__:   str=      [
         '''text_encoder/pytorch_model.bin''',
         '''text_encoder/model.safetensors''',
     ]
     self.assertTrue(is_safetensors_compatible(lowerCAmelCase   )   )
    def 						UpperCamelCase_				(  self   )       ->					str:
     SCREAMING_SNAKE_CASE__:   List[str]=      [
         '''safety_checker/pytorch_model.bin''',
         '''safety_checker/model.safetensors''',
         '''vae/diffusion_pytorch_model.bin''',
         '''vae/diffusion_pytorch_model.safetensors''',
         '''text_encoder/pytorch_model.bin''',
         # Removed: 'text_encoder/model.safetensors',
         '''unet/diffusion_pytorch_model.bin''',
         '''unet/diffusion_pytorch_model.safetensors''',
     ]
     self.assertFalse(is_safetensors_compatible(lowerCAmelCase   )   )
    def 						UpperCamelCase_				(  self   )       ->					List[str]:
     SCREAMING_SNAKE_CASE__:   Optional[int]=      [
         '''safety_checker/pytorch_model.fp16.bin''',
         '''safety_checker/model.fp16.safetensors''',
         '''vae/diffusion_pytorch_model.fp16.bin''',
         '''vae/diffusion_pytorch_model.fp16.safetensors''',
         '''text_encoder/pytorch_model.fp16.bin''',
         '''text_encoder/model.fp16.safetensors''',
         '''unet/diffusion_pytorch_model.fp16.bin''',
         '''unet/diffusion_pytorch_model.fp16.safetensors''',
     ]
     SCREAMING_SNAKE_CASE__:   Any=      '''fp16'''
     self.assertTrue(is_safetensors_compatible(lowerCAmelCase , variant=lowerCAmelCase   )   )
    def 						UpperCamelCase_				(  self   )       ->					Any:
     SCREAMING_SNAKE_CASE__:   List[str]=      [
         '''unet/diffusion_pytorch_model.fp16.bin''',
         '''unet/diffusion_pytorch_model.fp16.safetensors''',
     ]
     SCREAMING_SNAKE_CASE__:   Dict=      '''fp16'''
     self.assertTrue(is_safetensors_compatible(lowerCAmelCase , variant=lowerCAmelCase   )   )
    def 						UpperCamelCase_				(  self   )       ->					Dict:
     # pass variant but use the non-variant filenames
     SCREAMING_SNAKE_CASE__:   List[str]=      [
         '''unet/diffusion_pytorch_model.bin''',
         '''unet/diffusion_pytorch_model.safetensors''',
     ]
     SCREAMING_SNAKE_CASE__:   Union[str, Any]=      '''fp16'''
     self.assertTrue(is_safetensors_compatible(lowerCAmelCase , variant=lowerCAmelCase   )   )
    def 						UpperCamelCase_				(  self   )       ->					List[Any]:
     SCREAMING_SNAKE_CASE__:   Dict=      [
         '''safety_checker/pytorch_model.fp16.bin''',
         '''safety_checker/model.fp16.safetensors''',
         '''vae/diffusion_pytorch_model.fp16.bin''',
         '''vae/diffusion_pytorch_model.fp16.safetensors''',
         '''text_encoder/pytorch_model.fp16.bin''',
         '''text_encoder/model.fp16.safetensors''',
         '''unet/diffusion_pytorch_model.fp16.bin''',
         # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors',
     ]
     SCREAMING_SNAKE_CASE__:   List[Any]=      '''fp16'''
     self.assertFalse(is_safetensors_compatible(lowerCAmelCase , variant=lowerCAmelCase   )   )
    def 						UpperCamelCase_				(  self   )       ->					List[str]:
     SCREAMING_SNAKE_CASE__:   int=      [
         '''text_encoder/pytorch_model.fp16.bin''',
         '''text_encoder/model.fp16.safetensors''',
     ]
     SCREAMING_SNAKE_CASE__:   Any=      '''fp16'''
     self.assertTrue(is_safetensors_compatible(lowerCAmelCase , variant=lowerCAmelCase   )   )
    def 						UpperCamelCase_				(  self   )       ->					Optional[Any]:
     # pass variant but use the non-variant filenames
     SCREAMING_SNAKE_CASE__:   Optional[int]=      [
         '''text_encoder/pytorch_model.bin''',
         '''text_encoder/model.safetensors''',
     ]
     SCREAMING_SNAKE_CASE__:   str=      '''fp16'''
     self.assertTrue(is_safetensors_compatible(lowerCAmelCase , variant=lowerCAmelCase   )   )



    def 						UpperCamelCase_				(  self   )       ->					Union[str, Any]:
     SCREAMING_SNAKE_CASE__:   Tuple=      [
         '''safety_checker/pytorch_model.fp16.bin''',
         '''safety_checker/model.fp16.safetensors''',
         '''vae/diffusion_pytorch_model.fp16.bin''',
         '''vae/diffusion_pytorch_model.fp16.safetensors''',
         '''text_encoder/pytorch_model.fp16.bin''',
         # 'text_encoder/model.fp16.safetensors',
         '''unet/diffusion_pytorch_model.fp16.bin''',
         '''unet/diffusion_pytorch_model.fp16.safetensors''',
     ]
     SCREAMING_SNAKE_CASE__:   str=      '''fp16'''
     self.assertFalse(is_safetensors_compatible(lowerCAmelCase , variant=lowerCAmelCase   )   )

