





# 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			(     _a	):
			lowerCamelCase_	:	Any			     = '''philschmid/bart-large-cnn-samsum'''
			lowerCamelCase_	:	Optional[Any]			     = (
			    '''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.'''
			)
			lowerCamelCase_	:	str			     = '''summarizer'''
			lowerCamelCase_	:	Optional[int]			     = AutoTokenizer
			lowerCamelCase_	:	Optional[Any]			     = AutoModelForSeqaSeqLM

			lowerCamelCase_	:	Dict			     = ['''text''']
			lowerCamelCase_	:	Any			     = ['''text''']






			def      lowerCamelCase    (self   ,				__magic_name__       )	->  str:


							'''simple docstring'''



							return self.pre_processor(__magic_name__   ,				return_tensors='''pt'''   ,				truncation=__magic_name__       )






			def      lowerCamelCase    (self   ,				__magic_name__       )	->  int:


							'''simple docstring'''



							return self.model.generate(**__magic_name__       )[0]






			def      lowerCamelCase    (self   ,				__magic_name__       )	->  List[str]:


							'''simple docstring'''



							return self.pre_processor.decode(__magic_name__   ,				skip_special_tokens=__magic_name__   ,				clean_up_tokenization_spaces=__magic_name__       )








__a:     List[Any]   					=					{
    '''Pillow''': '''Pillow''',
    '''accelerate''': '''accelerate>=0.11.0''',
    '''compel''': '''compel==0.1.8''',
    '''black''': '''black~=23.1''',
    '''datasets''': '''datasets''',
    '''filelock''': '''filelock''',
    '''flax''': '''flax>=0.4.1''',
    '''hf-doc-builder''': '''hf-doc-builder>=0.3.0''',
    '''huggingface-hub''': '''huggingface-hub>=0.13.2''',
    '''requests-mock''': '''requests-mock==1.10.0''',
    '''importlib_metadata''': '''importlib_metadata''',
    '''invisible-watermark''': '''invisible-watermark''',
    '''isort''': '''isort>=5.5.4''',
    '''jax''': '''jax>=0.2.8,!=0.3.2''',
    '''jaxlib''': '''jaxlib>=0.1.65''',
    '''Jinja2''': '''Jinja2''',
    '''k-diffusion''': '''k-diffusion>=0.0.12''',
    '''torchsde''': '''torchsde''',
    '''note_seq''': '''note_seq''',
    '''librosa''': '''librosa''',
    '''numpy''': '''numpy''',
    '''omegaconf''': '''omegaconf''',
    '''parameterized''': '''parameterized''',
    '''protobuf''': '''protobuf>=3.20.3,<4''',
    '''pytest''': '''pytest''',
    '''pytest-timeout''': '''pytest-timeout''',
    '''pytest-xdist''': '''pytest-xdist''',
    '''ruff''': '''ruff>=0.0.241''',
    '''safetensors''': '''safetensors''',
    '''sentencepiece''': '''sentencepiece>=0.1.91,!=0.1.92''',
    '''scipy''': '''scipy''',
    '''onnx''': '''onnx''',
    '''regex''': '''regex!=2019.12.17''',
    '''requests''': '''requests''',
    '''tensorboard''': '''tensorboard''',
    '''torch''': '''torch>=1.4''',
    '''torchvision''': '''torchvision''',
    '''transformers''': '''transformers>=4.25.1''',
    '''urllib3''': '''urllib3<=2.0.0''',
}