



import os
from typing import List, Optional, Union

from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging


__A   :							Optional[int]										=   logging.get_logger(__name__)

__A   :							Union[str, Any]										=   {'vocab_file': 'vocab.txt'}

__A   :							int										=   {
    'vocab_file': {
        'facebook/esm2_t6_8M_UR50D': 'https://huggingface.co/facebook/esm2_t6_8M_UR50D/resolve/main/vocab.txt',
        'facebook/esm2_t12_35M_UR50D': 'https://huggingface.co/facebook/esm2_t12_35M_UR50D/resolve/main/vocab.txt',
    },
}

__A   :							Optional[Any]										=   {
    'facebook/esm2_t6_8M_UR50D': 1024,
    'facebook/esm2_t12_35M_UR50D': 1024,
}







def  lowercase	(      _SCREAMING_SNAKE_CASE   :						Tuple				):






				'''simple docstring'''



				with open(lowerCamelCase_					,     '''r'''				) as f:
								_UpperCAmelCase					=    f.read().splitlines()
								return [l.strip() for l in lines]
class 			_a (					lowerCamelCase__):
			"""simple docstring"""
			UpperCamelCase__			      =	VOCAB_FILES_NAMES
			UpperCamelCase__			      =	PRETRAINED_VOCAB_FILES_MAP
			UpperCamelCase__			      =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			UpperCamelCase__			      =	["""input_ids""", """attention_mask"""]



			def __init__(		self     :    List[Any]				,   __UpperCamelCase     :    List[str]				,   __UpperCamelCase     :    str="<unk>"				,   __UpperCamelCase     :    str="<cls>"				,   __UpperCamelCase     :    List[str]="<pad>"				,   __UpperCamelCase     :    List[str]="<mask>"				,   __UpperCamelCase     :    List[Any]="<eos>"				,   **__UpperCamelCase     :    List[str]				,   )->Dict:
							super().__init__(**__lowerCamelCase   )
							_UpperCAmelCase					=    load_vocab_file(__lowerCamelCase   )
							_UpperCAmelCase					=    dict(enumerate(self.all_tokens   )   )
							_UpperCAmelCase					=    {tok: ind for ind, tok in enumerate(self.all_tokens   )}
							_UpperCAmelCase					=    unk_token
							_UpperCAmelCase					=    cls_token
							_UpperCAmelCase					=    pad_token
							_UpperCAmelCase					=    mask_token
							_UpperCAmelCase					=    eos_token
							_UpperCAmelCase					=    self.all_tokens
							self._create_trie(self.unique_no_split_tokens   )



			def  lowercase__						(		self     :    Any				,   __UpperCamelCase     :    Optional[int]   )->str:
							return self._id_to_token.get(__lowerCamelCase				,   self.unk_token   )



			def  lowercase__						(		self     :    List[Any]				,   __UpperCamelCase     :    int   )->int:
							return self._token_to_id.get(__lowerCamelCase				,   self._token_to_id.get(self.unk_token   )   )



			def  lowercase__						(		self     :    int				,   __UpperCamelCase     :    Union[str, Any]				,   **__UpperCamelCase     :    Tuple   )->Union[str, Any]:
							return text.split()



			def  lowercase__						(		self     :    Union[str, Any]				,   __UpperCamelCase     :    Any=False   )->Optional[int]:
							return len(self._id_to_token   )



			def  lowercase__						(		self     :    List[Any]   )->str:
							return {token: i for i, token in enumerate(self.all_tokens   )}



			def  lowercase__						(		self     :    Optional[int]				,   __UpperCamelCase     :    str   )->int:
							return self._token_to_id.get(__lowerCamelCase				,   self._token_to_id.get(self.unk_token   )   )



			def  lowercase__						(		self     :    str				,   __UpperCamelCase     :    Tuple   )->str:
							return self._id_to_token.get(__lowerCamelCase				,   self.unk_token   )



			def  lowercase__						(		self     :    str				,   __UpperCamelCase     :    Dict				,   __UpperCamelCase     :    Tuple = None   )->List[int]:
							_UpperCAmelCase					=    [self.cls_token_id]
							_UpperCAmelCase					=    [self.eos_token_id]  # No sep token in ESM vocabulary
							if token_ids_a is None:
											if self.eos_token_id is None:
															return cls + token_ids_a
											else:
															return cls + token_ids_a + sep
							elif self.eos_token_id is None:
											raise ValueError('''Cannot tokenize multiple sequences when EOS token is not set!'''   )
							return cls + token_ids_a + sep + token_ids_a + sep  # Multiple inputs always have an EOS token



			def  lowercase__						(		self     :    Tuple				,   __UpperCamelCase     :    Tuple				,   __UpperCamelCase     :    Dict = None				,   __UpperCamelCase     :    Tuple = False   )->List[int]:






							if already_has_special_tokens:
											if token_ids_a is not None:
															raise ValueError(
															    '''You should not supply a second sequence if the provided sequence of '''
															    '''ids is already formatted with special tokens for the model.'''   )

											return [1 if token in self.all_special_ids else 0 for token in token_ids_a]
							_UpperCAmelCase					=    [1] + ([0] * len(__lowerCamelCase   )) + [1]
							if token_ids_a is not None:
											mask += [0] * len(__lowerCamelCase   ) + [1]
							return mask



			def  lowercase__						(		self     :    Optional[Any]				,   __UpperCamelCase     :    List[str]				,   __UpperCamelCase     :    Tuple   )->Tuple:
							_UpperCAmelCase					=    os.path.join(__lowerCamelCase				,   (filename_prefix + '''-''' if filename_prefix else '''''') + '''vocab.txt'''   )
							with open(__lowerCamelCase				,   '''w'''   ) as f:
											f.write('''\n'''.join(self.all_tokens   )   )
							return (vocab_file,)



			@property
			def  lowercase__						(		self     :    Union[str, Any]   )->int:
							return self.get_vocab_size(with_added_tokens=__lowerCamelCase   )



			def  lowercase__						(		self     :    int				,   __UpperCamelCase     :    int				,   __UpperCamelCase     :    str = False   )->int:
							return super()._add_tokens(__lowerCamelCase				,   special_tokens=__lowerCamelCase   )








"""simple docstring"""


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

import yaml
class 			_a (					yaml.SafeLoader):
			"""simple docstring"""



			def  lowercase__						(		self     :    List[str]				,   __UpperCamelCase     :    Any   )->List[Any]:
							_UpperCAmelCase					=    [self.constructed_objects[key_node] for key_node, _ in node.value]
							_UpperCAmelCase					=    [tuple(__UpperCamelCase   ) if isinstance(__UpperCamelCase				,   __UpperCamelCase   ) else key for key in keys]
							_UpperCAmelCase					=    Counter(__UpperCamelCase   )
							_UpperCAmelCase					=    [key for key in counter if counter[key] > 1]
							if duplicate_keys:
											raise TypeError(F'Got duplicate yaml keys: {duplicate_keys}'   )



			def  lowercase__						(		self     :    List[str]				,   __UpperCamelCase     :    Optional[Any]				,   __UpperCamelCase     :    str=False   )->Dict:
							_UpperCAmelCase					=    super().construct_mapping(__UpperCamelCase				,   deep=__UpperCamelCase   )
							self._check_no_duplicates_on_constructed_node(__UpperCamelCase   )
							return mapping







def  lowercase	(      _SCREAMING_SNAKE_CASE   :						str				):






				'''simple docstring'''



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

				return None, "\n".join(_SCREAMING_SNAKE_CASE				)
class 			_a (					lowerCAmelCase):
			"""simple docstring"""
			# class attributes
			UpperCamelCase__			      =	{"""train_eval_index"""}  # train-eval-index in the YAML metadata



			@classmethod
			def  lowercase__						(		cls     :    List[Any]				,   __UpperCamelCase     :    Path   )->"DatasetMetadata":
							with open(__UpperCamelCase				,   encoding='''utf-8'''   ) as readme_file:
											_UpperCAmelCase		,						_UpperCAmelCase					=    _split_yaml_from_readme(readme_file.read()   )
							if yaml_string is not None:
											return cls.from_yaml_string(__UpperCamelCase   )
							else:
											return cls()



			def  lowercase__						(		self     :    Tuple				,   __UpperCamelCase     :    Path   )->List[Any]:
							if path.exists():
											with open(__UpperCamelCase				,   encoding='''utf-8'''   ) as readme_file:
															_UpperCAmelCase					=    readme_file.read()
							else:
											_UpperCAmelCase					=    None
							_UpperCAmelCase					=    self._to_readme(__UpperCamelCase   )
							with open(__UpperCamelCase				,   '''w'''				,   encoding='''utf-8'''   ) as readme_file:
											readme_file.write(__UpperCamelCase   )



			def  lowercase__						(		self     :    List[str]				,   __UpperCamelCase     :    Optional[str] = None   )->str:
							if readme_content is not None:
											_UpperCAmelCase		,						_UpperCAmelCase					=    _split_yaml_from_readme(__UpperCamelCase   )
											_UpperCAmelCase					=    '''---\n''' + self.to_yaml_string() + '''---\n''' + content
							else:
											_UpperCAmelCase					=    '''---\n''' + self.to_yaml_string() + '''---\n'''
							return full_content



			@classmethod
			def  lowercase__						(		cls     :    str				,   __UpperCamelCase     :    str   )->"DatasetMetadata":
							_UpperCAmelCase					=    yaml.load(__UpperCamelCase				,   Loader=_NoDuplicateSafeLoader   ) or {}

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



			def  lowercase__						(		self     :    str   )->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'''   )



__A   :							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

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

					__A   :							Dict										=   Path(args.readme_filepath)
					__A   :							Tuple										=   DatasetMetadata.from_readme(readme_filepath)
					print(dataset_metadata)
					dataset_metadata.to_readme(readme_filepath)



