





"""simple docstring"""





# Copyright 2023 The HuggingFace 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 typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_lowerCamelCase    	=      {
    '''configuration_vivit''': ['''VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VivitConfig'''],
}
try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _lowerCamelCase    	=      ['''VivitImageProcessor''']


try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _lowerCamelCase    	=      [
        '''VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''VivitModel''',
        '''VivitPreTrainedModel''',
        '''VivitForVideoClassification''',
    ]


if TYPE_CHECKING:
    from .configuration_vivit import VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, VivitConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .image_processing_vivit import VivitImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_vivit import (
            VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
            VivitForVideoClassification,
            VivitModel,
            VivitPreTrainedModel,
        )


else:
    import sys

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



# 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]


