
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm

from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save

def  __lowerCamelCase					( _lowercase						,     _lowercase						,     _lowercase=1024						,     _lowercase=1024						,     _lowercase=False						,     **_lowercase			)       ->      Tuple:
     UpperCamelCase						    =					AutoTokenizer.from_pretrained(_lowercase			)
     UpperCamelCase						    =					SeqaSeqDataset(_lowercase						,     _lowercase						,     _lowercase						,     _lowercase						,     type_path='train'						,     **_lowercase			)
     UpperCamelCase						    =					tok.pad_token_id

     def get_lens(_lowercase			):
          UpperCamelCase						    =					tqdm(
              DataLoader(_lowercase						,     batch_size=512						,     num_workers=8						,     shuffle=_lowercase						,     collate_fn=ds.collate_fn			)						,     desc=str(ds.len_file			)						,     )
          UpperCamelCase						    =					[]
          for batch in dl:
               UpperCamelCase						    =					batch['input_ids'].ne(_lowercase			).sum(1			).tolist()
               UpperCamelCase						    =					batch['labels'].ne(_lowercase			).sum(1			).tolist()
               if consider_target:
                    for src, tgt in zip(_lowercase						,     _lowercase			):
                         max_lens.append(max(_lowercase						,     _lowercase			)			)
               else:
                    max_lens.extend(_lowercase			)
          return max_lens

     UpperCamelCase						    =					get_lens(_lowercase			)
     UpperCamelCase						    =					SeqaSeqDataset(_lowercase						,     _lowercase						,     _lowercase						,     _lowercase						,     type_path='val'						,     **_lowercase			)
     UpperCamelCase						    =					get_lens(_lowercase			)
     pickle_save(_lowercase						,     train_ds.len_file			)
     pickle_save(_lowercase						,     val_ds.len_file			)


if __name__ == "__main__":
 fire.Fire(save_len_file)




# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from ..models.whisper import WhisperForConditionalGeneration, WhisperProcessor
from .base import PipelineTool
class       _lowerCAmelCase  (		__magic_name__							):

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

 SCREAMING_SNAKE_CASE_				:					Union[str, Any]       						=["audio"]
 SCREAMING_SNAKE_CASE_				:					Any       						=["text"]

 def      __lowerCAmelCase  (						self			:			List[Any]					, SCREAMING_SNAKE_CASE__			:			List[Any]   ):






      """simple docstring"""



      return self.pre_processor(SCREAMING_SNAKE_CASE__					, return_tensors='pt'   ).input_features

 def      __lowerCAmelCase  (						self			:			Tuple					, SCREAMING_SNAKE_CASE__			:			Union[str, Any]   ):






      """simple docstring"""



      return self.model.generate(inputs=SCREAMING_SNAKE_CASE__   )






 def      __lowerCAmelCase  (						self			:			List[str]					, SCREAMING_SNAKE_CASE__			:			List[str]   ):






      """simple docstring"""



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


