

'''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.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool



class lowerCamelCase			(  lowercase_						):



			'''simple docstring'''






			__snake_case        =	'philschmid/bart-large-cnn-samsum'
			__snake_case        =	(
			    'This is a tool that summarizes an English text. It takes an input `text` containing the text to summarize, '
			    'and returns a summary of the text.'
			)
			__snake_case        =	'summarizer'
			__snake_case        =	AutoTokenizer
			__snake_case        =	AutoModelForSeqaSeqLM

			__snake_case        =	['text']
			__snake_case        =	['text']


			def lowercase__						(				self	:						Tuple		,      lowerCAmelCase_	:						List[str]			)      ->		Optional[int]:





									'''simple docstring'''
									return self.pre_processor(lowerCAmelCase_		,      return_tensors="""pt"""		,      truncation=lowerCAmelCase_			)


			def lowercase__						(				self	:						Tuple		,      lowerCAmelCase_	:						Optional[int]			)      ->		Optional[Any]:





									'''simple docstring'''
									return self.model.generate(**lowerCAmelCase_			)[0]



			def lowercase__						(				self	:						Union[str, Any]		,      lowerCAmelCase_	:						List[str]			)      ->		List[Any]:





									'''simple docstring'''
									return self.pre_processor.decode(lowerCAmelCase_		,      skip_special_tokens=lowerCAmelCase_		,      clean_up_tokenization_spaces=lowerCAmelCase_			)




'''simple docstring'''



from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available


__snake_case			:     Any										=      {
    'configuration_audio_spectrogram_transformer': [
        'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'ASTConfig',
    ]
}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case			:     Optional[int]										=      [
		    'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'ASTForAudioClassification',
		    'ASTModel',
		    'ASTPreTrainedModel',
		]

try:
		if not is_speech_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__snake_case			:     List[Any]										=      ['ASTFeatureExtractor']

if TYPE_CHECKING:
		from .configuration_audio_spectrogram_transformer import (
		    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
		    ASTConfig,
		)

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_audio_spectrogram_transformer import (
				    AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ASTForAudioClassification,
				    ASTModel,
				    ASTPreTrainedModel,
				)

		try:
				if not is_speech_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .feature_extraction_audio_spectrogram_transformer import ASTFeatureExtractor


else:
		import sys

		__snake_case			:     Optional[Any]										=      _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)

