


"""simple docstring"""

from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool





class    lowerCamelCase__						(		_a    ):
      a :     str											=		"openai/whisper-base"
      a :     List[str]											=		(
          "This is a tool that transcribes an audio into text. It takes an input named `audio` and returns the "
          "transcribed text."
      )
      a :     str											=		"transcriber"
      a :     Optional[Any]											=		WhisperProcessor
      a :     str											=		WhisperForConditionalGeneration

      a :     Optional[int]											=		["audio"]
      a :     List[Any]											=		["text"]
      def SCREAMING_SNAKE_CASE_	(		self	:	str      ,       A_	:	List[str]							):






       '''simple docstring'''


       return self.pre_processor(UpperCamelCase__      ,       return_tensors="""pt"""							).input_features
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[int]      ,       A_	:	List[Any]							):






       '''simple docstring'''


       return self.model.generate(inputs=UpperCamelCase__							)






      def SCREAMING_SNAKE_CASE_	(		self	:	Union[str, Any]      ,       A_	:	Tuple							):






       '''simple docstring'''


       return self.pre_processor.batch_decode(UpperCamelCase__      ,       skip_special_tokens=UpperCamelCase__							)[0]




"""simple docstring"""

import argparse
import logging
import pickle
from collections import Counter


logging.basicConfig(
    format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=logging.INFO
)
UpperCAmelCase__  							=logging.getLogger(__name__)

if __name__ == "__main__":
       UpperCAmelCase__  							=argparse.ArgumentParser(
           description="Token Counts for smoothing the masking probabilities in MLM (cf XLM/word2vec)"
       )
       parser.add_argument(
           "--data_file", type=str, default="data/dump.bert-base-uncased.pickle", help="The binarized dataset."
       )
       parser.add_argument(
           "--token_counts_dump", type=str, default="data/token_counts.bert-base-uncased.pickle", help="The dump file."
       )
       parser.add_argument("--vocab_size", default=3_0522, type=int)
       UpperCAmelCase__  							=parser.parse_args()

       logger.info(f"""Loading data from {args.data_file}""")
       with open(args.data_file, "rb") as fp:
              UpperCAmelCase__  							=pickle.load(fp)

       logger.info("Counting occurrences for MLM.")
       UpperCAmelCase__  							=Counter()
       for tk_ids in data:
              counter.update(tk_ids)
       UpperCAmelCase__  							=[0] * args.vocab_size
       for k, v in counter.items():
              UpperCAmelCase__  							=v

       logger.info(f"""Dump to {args.token_counts_dump}""")
       with open(args.token_counts_dump, "wb") as handle:
              pickle.dump(counts, handle, protocol=pickle.HIGHEST_PROTOCOL)
