import json
import os
import shutil
import tempfile
from unittest import TestCase

from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.configuration_dpr import DPRConfig
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
from transformers.utils import is_datasets_available, is_faiss_available, is_torch_available


if is_torch_available() and is_datasets_available() and is_faiss_available():
      from transformers.models.rag.configuration_rag import RagConfig
      from transformers.models.rag.tokenization_rag import RagTokenizer





@require_faiss
@require_torch
class 					A							(    UpperCAmelCase_					):


   def       lowercase_				(self					:						Optional[Any]		)						->    Tuple:
         """simple docstring"""



         UpperCAmelCase__								=  tempfile.mkdtemp()
         UpperCAmelCase__								=  8

         # DPR tok
         UpperCAmelCase__								=  [
             "[UNK]",
             "[CLS]",
             "[SEP]",
             "[PAD]",
             "[MASK]",
             "want",
             "##want",
             "##ed",
             "wa",
             "un",
             "runn",
             "##ing",
             ",",
             "low",
             "lowest",
         ]
         UpperCAmelCase__								=  os.path.join(self.tmpdirname	,  "dpr_tokenizer"		)
         os.makedirs(__UpperCAmelCase	,  exist_ok=__UpperCAmelCase		)
         UpperCAmelCase__								=  os.path.join(__UpperCAmelCase	,  DPR_VOCAB_FILES_NAMES["vocab_file"]		)
         with open(self.vocab_file	,  "w"	,  encoding="utf-8"		) as vocab_writer:
               vocab_writer.write("".join([x + "\n" for x in vocab_tokens]		)		)

         # BART tok
         UpperCAmelCase__								=  [
             "l",
             "o",
             "w",
             "e",
             "r",
             "s",
             "t",
             "i",
             "d",
             "n",
             "\u0120",
             "\u0120l",
             "\u0120n",
             "\u0120lo",
             "\u0120low",
             "er",
             "\u0120lowest",
             "\u0120newer",
             "\u0120wider",
             "<unk>",
         ]
         UpperCAmelCase__								=  dict(zip(__UpperCAmelCase	,  range(len(__UpperCAmelCase		)		)		)		)
         UpperCAmelCase__								=  ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
         UpperCAmelCase__								=  {"unk_token": "<unk>"}

         UpperCAmelCase__								=  os.path.join(self.tmpdirname	,  "bart_tokenizer"		)
         os.makedirs(__UpperCAmelCase	,  exist_ok=__UpperCAmelCase		)
         UpperCAmelCase__								=  os.path.join(__UpperCAmelCase	,  BART_VOCAB_FILES_NAMES["vocab_file"]		)
         UpperCAmelCase__								=  os.path.join(__UpperCAmelCase	,  BART_VOCAB_FILES_NAMES["merges_file"]		)
         with open(self.vocab_file	,  "w"	,  encoding="utf-8"		) as fp:
               fp.write(json.dumps(__UpperCAmelCase		) + "\n"		)
         with open(self.merges_file	,  "w"	,  encoding="utf-8"		) as fp:
               fp.write("\n".join(__UpperCAmelCase		)		)


   def       lowercase_				(self					:						Dict		)						->    DPRQuestionEncoderTokenizer:
         """simple docstring"""



         return DPRQuestionEncoderTokenizer.from_pretrained(os.path.join(self.tmpdirname	,  "dpr_tokenizer"		)		)


   def       lowercase_				(self					:						Any		)						->    BartTokenizer:
         """simple docstring"""



         return BartTokenizer.from_pretrained(os.path.join(self.tmpdirname	,  "bart_tokenizer"		)		)


   def       lowercase_				(self					:						Any		)						->    str:
         """simple docstring"""



         shutil.rmtree(self.tmpdirname		)


   @require_tokenizers
   def       lowercase_				(self					:						Dict		)						->    List[str]:
         """simple docstring"""



         UpperCAmelCase__								=  os.path.join(self.tmpdirname	,  "rag_tokenizer"		)
         UpperCAmelCase__								=  RagConfig(question_encoder=DPRConfig().to_dict()	,  generator=BartConfig().to_dict()		)
         UpperCAmelCase__								=  RagTokenizer(question_encoder=self.get_dpr_tokenizer()	,  generator=self.get_bart_tokenizer()		)
         rag_config.save_pretrained(__UpperCAmelCase		)
         rag_tokenizer.save_pretrained(__UpperCAmelCase		)
         UpperCAmelCase__								=  RagTokenizer.from_pretrained(__UpperCAmelCase	,  config=__UpperCAmelCase		)
         self.assertIsInstance(new_rag_tokenizer.question_encoder	,  __UpperCAmelCase		)
         self.assertEqual(new_rag_tokenizer.question_encoder.get_vocab()	,  rag_tokenizer.question_encoder.get_vocab()		)
         self.assertIsInstance(new_rag_tokenizer.generator	,  __UpperCAmelCase		)
         self.assertEqual(new_rag_tokenizer.generator.get_vocab()	,  rag_tokenizer.generator.get_vocab()		)


   @slow
   def       lowercase_				(self					:						Optional[int]		)						->    str:
         """simple docstring"""



         UpperCAmelCase__								=  RagTokenizer.from_pretrained("facebook/rag-token-nq"		)
         UpperCAmelCase__								=  [
             "who got the first nobel prize in physics",
             "when is the next deadpool movie being released",
             "which mode is used for short wave broadcast service",
             "who is the owner of reading football club",
             "when is the next scandal episode coming out",
             "when is the last time the philadelphia won the superbowl",
             "what is the most current adobe flash player version",
             "how many episodes are there in dragon ball z",
             "what is the first step in the evolution of the eye",
             "where is gall bladder situated in human body",
             "what is the main mineral in lithium batteries",
             "who is the president of usa right now",
             "where do the greasers live in the outsiders",
             "panda is a national animal of which country",
             "what is the name of manchester united stadium",
         ]
         UpperCAmelCase__								=  tokenizer(__UpperCAmelCase		)
         self.assertIsNotNone(__UpperCAmelCase		)





   @slow
   def       lowercase_				(self					:						Tuple		)						->    List[Any]:
         """simple docstring"""



         UpperCAmelCase__								=  RagTokenizer.from_pretrained("facebook/rag-sequence-nq"		)
         UpperCAmelCase__								=  [
             "who got the first nobel prize in physics",
             "when is the next deadpool movie being released",
             "which mode is used for short wave broadcast service",
             "who is the owner of reading football club",
             "when is the next scandal episode coming out",
             "when is the last time the philadelphia won the superbowl",
             "what is the most current adobe flash player version",
             "how many episodes are there in dragon ball z",
             "what is the first step in the evolution of the eye",
             "where is gall bladder situated in human body",
             "what is the main mineral in lithium batteries",
             "who is the president of usa right now",
             "where do the greasers live in the outsiders",
             "panda is a national animal of which country",
             "what is the name of manchester united stadium",
         ]
         UpperCAmelCase__								=  tokenizer(__UpperCAmelCase		)
         self.assertIsNotNone(__UpperCAmelCase		)




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

import yaml





class 					A							(    yaml.SafeLoader					):


   def       lowercase_				(self					:						Tuple	,  __UpperCAmelCase					:						str		)						->    Tuple:
         """simple docstring"""



         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					:						Dict	,  __UpperCAmelCase					:						Dict	,  __UpperCAmelCase					:						Any=False		)						->    Union[str, Any]:
         """simple docstring"""



         UpperCAmelCase__								=  super().construct_mapping(__UpperCAmelCase	,  deep=__UpperCAmelCase		)
         self._check_no_duplicates_on_constructed_node(__UpperCAmelCase		)
         return mapping




def        lowerCAmelCase_			(					__A							)					->    Tuple[Optional[str], 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(__A							)





class 					A							(    UpperCAmelCase_					):
   # class attributes
   __UpperCAmelCase			:			Optional[Any]              =      {'train_eval_index'}  # train-eval-index in the YAML metadata


   @classmethod
   def       lowercase_				(cls					:						List[str]	,  __UpperCAmelCase					:						Path		)						->    "DatasetMetadata":
         """simple docstring"""



         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					:						int	,  __UpperCAmelCase					:						Path		)						->    str:
         """simple docstring"""



         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					:						str	,  __UpperCAmelCase					:						Optional[str] = None		)						->    str:
         """simple docstring"""



         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					:						Optional[int]	,  __UpperCAmelCase					:						str		)						->    "DatasetMetadata":
         """simple docstring"""



         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					:						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=__UpperCAmelCase	,  allow_unicode=__UpperCAmelCase	,  encoding="utf-8"	,  ).decode("utf-8"		)




UpperCamelCase__    							= {
    '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

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

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



