

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_      =     {
    'configuration_clipseg': [
        'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'CLIPSegConfig',
        'CLIPSegTextConfig',
        'CLIPSegVisionConfig',
    ],
    'processing_clipseg': ['CLIPSegProcessor'],
}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_      =     [
			    'CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'CLIPSegModel',
			    'CLIPSegPreTrainedModel',
			    'CLIPSegTextModel',
			    'CLIPSegVisionModel',
			    'CLIPSegForImageSegmentation',
			]

if TYPE_CHECKING:
			from .configuration_clipseg import (
			    CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP,
			    CLIPSegConfig,
			    CLIPSegTextConfig,
			    CLIPSegVisionConfig,
			)
			from .processing_clipseg import CLIPSegProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_clipseg import (
						    CLIPSEG_PRETRAINED_MODEL_ARCHIVE_LIST,
						    CLIPSegForImageSegmentation,
						    CLIPSegModel,
						    CLIPSegPreTrainedModel,
						    CLIPSegTextModel,
						    CLIPSegVisionModel,
						)

else:
			import sys

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



"""simple docstring"""



# 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							( snake_case_      ):
   __UpperCAmelCase					:			List[str]				    =    '''openai/whisper-base'''
   __UpperCAmelCase					:			Any				    =    (
       '''This is a tool that transcribes an audio into text. It takes an input named `audio` and returns the '''
       '''transcribed text.'''
   )
   __UpperCAmelCase					:			Tuple				    =    '''transcriber'''
   __UpperCAmelCase					:			Union[str, Any]				    =    WhisperProcessor
   __UpperCAmelCase					:			str				    =    WhisperForConditionalGeneration

   __UpperCAmelCase					:			int				    =    ['''audio''']
   __UpperCAmelCase					:			Optional[int]				    =    ['''text''']







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		)      ->						Tuple:

       '''simple docstring'''




       return self.pre_processor(UpperCamelCase__		,      return_tensors="pt"		).input_features







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		)      ->						int:

       '''simple docstring'''




       return self.model.generate(inputs=UpperCamelCase__		)







   def 					lowerCamelCase						(      self		,      UpperCamelCase__		)      ->						Optional[Any]:

       '''simple docstring'''




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





