




"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


A_						=				logging.get_logger(__name__)

A_						=				{
    '''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/config.json''',
    # See all BioGPT models at https://huggingface.co/models?filter=biogpt
}






class 					lowercase(     __a ):







 '''simple docstring'''





 lowercase__ 					=					"biogpt"


 def __init__(				self:		Dict,      a_:		List[Any]=42_384,      a_:		int=1_024,      a_:		Optional[int]=24,      a_:		List[str]=16,      a_:		Optional[Any]=4_096,      a_:		int="gelu",      a_:		int=0.1,      a_:		List[Any]=0.1,      a_:		Any=1_024,      a_:		Optional[Any]=0.02,      a_:		Dict=1E-12,      a_:		Tuple=True,      a_:		Any=True,      a_:		Tuple=0.0,      a_:		str=0.0,      a_:		int=1,      a_:		Any=0,      a_:		List[str]=2,      **a_:		Optional[int],      ):




   '''simple docstring'''



   _snake_case							:		Dict								=  vocab_size
   _snake_case							:		int								=  max_position_embeddings
   _snake_case							:		Optional[int]								=  hidden_size
   _snake_case							:		Any								=  num_hidden_layers
   _snake_case							:		List[str]								=  num_attention_heads
   _snake_case							:		Optional[int]								=  intermediate_size
   _snake_case							:		Dict								=  hidden_act
   _snake_case							:		Tuple								=  hidden_dropout_prob
   _snake_case							:		Tuple								=  attention_probs_dropout_prob
   _snake_case							:		Optional[Any]								=  initializer_range
   _snake_case							:		List[str]								=  layer_norm_eps
   _snake_case							:		List[str]								=  scale_embedding
   _snake_case							:		Dict								=  use_cache
   _snake_case							:		Optional[int]								=  layerdrop
   _snake_case							:		Any								=  activation_dropout
   super().__init__(pad_token_id=a_,      bos_token_id=a_,      eos_token_id=a_,      **a_		)





# 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 	snake_case_   (		__A					):







			'''simple docstring'''

			SCREAMING_SNAKE_CASE     :   Optional[Any]									=				"philschmid/bart-large-cnn-samsum"
			SCREAMING_SNAKE_CASE     :   Tuple									=				(
			    "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."
			)
			SCREAMING_SNAKE_CASE     :   str									=				"summarizer"
			SCREAMING_SNAKE_CASE     :   str									=				AutoTokenizer
			SCREAMING_SNAKE_CASE     :   str									=				AutoModelForSeqaSeqLM

			SCREAMING_SNAKE_CASE     :   Optional[int]									=				["text"]
			SCREAMING_SNAKE_CASE     :   Optional[int]									=				["text"]







			def 				snake_case__(     self :				str							,   _UpperCamelCase :				int							)      ->Optional[int]:
									return self.pre_processor(_UpperCamelCase							,   return_tensors='''pt'''							,   truncation=_UpperCamelCase							)







			def 				snake_case__(     self :				Tuple							,   _UpperCamelCase :				Optional[int]							)      ->Tuple:
									return self.model.generate(**_UpperCamelCase							)[0]







			def 				snake_case__(     self :				Optional[Any]							,   _UpperCamelCase :				Optional[int]							)      ->Any:
									return self.pre_processor.decode(_UpperCamelCase							,   skip_special_tokens=_UpperCamelCase							,   clean_up_tokenization_spaces=_UpperCamelCase							)