

# 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	(   SCREAMING_SNAKE_CASE				):
  _a		     =    """openai/whisper-base"""
  _a		     =    (
      """This is a tool that transcribes an audio into text. It takes an input named `audio` and returns the """
      """transcribed text."""
  )
  _a		     =    """transcriber"""
  _a		     =    WhisperProcessor
  _a		     =    WhisperForConditionalGeneration

  _a		     =    ["""audio"""]
  _a		     =    ["""text"""]




  def     A__	(							self				,  lowerCAmelCase   )    ->					Union[str, Any]:
        '''simple docstring'''






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




  def     A__	(							self				,  lowerCAmelCase   )    ->					Any:
        '''simple docstring'''






        return self.model.generate(inputs=lowerCAmelCase   )




  def     A__	(							self				,  lowerCAmelCase   )    ->					Dict:
        '''simple docstring'''






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





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase_   							=  {
    'configuration_timesformer': ['TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TimesformerConfig'],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  lowercase_   							=  [
      'TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
      'TimesformerModel',
      'TimesformerForVideoClassification',
      'TimesformerPreTrainedModel',
  ]

if TYPE_CHECKING:
  from .configuration_timesformer import TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, TimesformerConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_timesformer import (
        TIMESFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        TimesformerForVideoClassification,
        TimesformerModel,
        TimesformerPreTrainedModel,
    )

else:
  import sys

  lowercase_   							=  _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


