


"""simple docstring"""







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#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#     http://www.apache.org/licenses/LICENSE-2.0
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from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool




class 			UpperCamelCase_     (			UpperCamelCase):

	"""simple docstring"""





	snake_case__    :  Dict    =      "philschmid/bart-large-cnn-samsum"
	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."
	)
	snake_case__    :  Any    =      "summarizer"
	snake_case__    :  Optional[int]    =      AutoTokenizer
	snake_case__    :  str    =      AutoModelForSeqaSeqLM

	snake_case__    :  int    =      ["text"]
	snake_case__    :  Tuple    =      ["text"]




	def   UpperCAmelCase_				(			self      :    List[Any]      ,      UpperCAmelCase__      :    Union[str, Any]       )	->     List[str]:
						return self.pre_processor(UpperCAmelCase__      ,      return_tensors="pt"      ,      truncation=UpperCAmelCase__       )




	def   UpperCAmelCase_				(			self      :    Tuple      ,      UpperCAmelCase__      :    Dict       )	->     Union[str, Any]:
						return self.model.generate(**UpperCAmelCase__       )[0]




	def   UpperCAmelCase_				(			self      :    Union[str, Any]      ,      UpperCAmelCase__      :    Optional[Any]       )	->     int:
						return self.pre_processor.decode(UpperCAmelCase__      ,      skip_special_tokens=UpperCAmelCase__      ,      clean_up_tokenization_spaces=UpperCAmelCase__       )




"""simple docstring"""







from typing import List

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


a__    :							Tuple            =					logging.get_logger(__name__)

a__    :							List[Any]            =					{
    '''snap-research/efficientformer-l1-300''': (
        '''https://huggingface.co/snap-research/efficientformer-l1-300/resolve/main/config.json'''
    ),
}




class 			UpperCamelCase_     (			UpperCamelCase):

	"""simple docstring"""





	snake_case__    :  Any    =      "efficientformer"




	def __init__(			self      :    Any      ,      UpperCAmelCase__      :    List[int] = [3, 2, 6, 4]      ,      UpperCAmelCase__      :    List[int] = [4_8, 9_6, 2_2_4, 4_4_8]      ,      UpperCAmelCase__      :    List[bool] = [True, True, True, True]      ,      UpperCAmelCase__      :    int = 4_4_8      ,      UpperCAmelCase__      :    int = 3_2      ,      UpperCAmelCase__      :    int = 4      ,      UpperCAmelCase__      :    int = 7      ,      UpperCAmelCase__      :    int = 5      ,      UpperCAmelCase__      :    int = 8      ,      UpperCAmelCase__      :    int = 4      ,      UpperCAmelCase__      :    float = 0.0      ,      UpperCAmelCase__      :    int = 1_6      ,      UpperCAmelCase__      :    int = 3      ,      UpperCAmelCase__      :    int = 3      ,      UpperCAmelCase__      :    int = 3      ,      UpperCAmelCase__      :    int = 2      ,      UpperCAmelCase__      :    int = 1      ,      UpperCAmelCase__      :    float = 0.0      ,      UpperCAmelCase__      :    int = 1      ,      UpperCAmelCase__      :    bool = True      ,      UpperCAmelCase__      :    bool = True      ,      UpperCAmelCase__      :    float = 1E-5      ,      UpperCAmelCase__      :    str = "gelu"      ,      UpperCAmelCase__      :    float = 0.02      ,      UpperCAmelCase__      :    float = 1E-12      ,      UpperCAmelCase__      :    int = 2_2_4      ,      UpperCAmelCase__      :    float = 1E-05      ,      **UpperCAmelCase__      :    Tuple      ,      )	->     None:
						super().__init__(**UpperCAmelCase__       )

						__SCREAMING_SNAKE_CASE						       =    hidden_act
						__SCREAMING_SNAKE_CASE						       =    hidden_dropout_prob
						__SCREAMING_SNAKE_CASE						       =    hidden_sizes
						__SCREAMING_SNAKE_CASE						       =    num_hidden_layers
						__SCREAMING_SNAKE_CASE						       =    num_attention_heads
						__SCREAMING_SNAKE_CASE						       =    initializer_range
						__SCREAMING_SNAKE_CASE						       =    layer_norm_eps
						__SCREAMING_SNAKE_CASE						       =    patch_size
						__SCREAMING_SNAKE_CASE						       =    num_channels
						__SCREAMING_SNAKE_CASE						       =    depths
						__SCREAMING_SNAKE_CASE						       =    mlp_expansion_ratio
						__SCREAMING_SNAKE_CASE						       =    downsamples
						__SCREAMING_SNAKE_CASE						       =    dim
						__SCREAMING_SNAKE_CASE						       =    key_dim
						__SCREAMING_SNAKE_CASE						       =    attention_ratio
						__SCREAMING_SNAKE_CASE						       =    resolution
						__SCREAMING_SNAKE_CASE						       =    pool_size
						__SCREAMING_SNAKE_CASE						       =    downsample_patch_size
						__SCREAMING_SNAKE_CASE						       =    downsample_stride
						__SCREAMING_SNAKE_CASE						       =    downsample_pad
						__SCREAMING_SNAKE_CASE						       =    drop_path_rate
						__SCREAMING_SNAKE_CASE						       =    num_metaad_blocks
						__SCREAMING_SNAKE_CASE						       =    distillation
						__SCREAMING_SNAKE_CASE						       =    use_layer_scale
						__SCREAMING_SNAKE_CASE						       =    layer_scale_init_value
						__SCREAMING_SNAKE_CASE						       =    image_size
						__SCREAMING_SNAKE_CASE						       =    batch_norm_eps
