
'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging


A							     = logging.get_logger(__name__)

A							     = {
    "uclanlp/plbart-base": "https://huggingface.co/uclanlp/plbart-base/resolve/main/config.json",
    # See all PLBART models at https://huggingface.co/models?filter=plbart
}



class 			lowerCAmelCase__ (							UpperCamelCase							):



  '''simple docstring'''






  _UpperCamelCase							=			'plbart'
  _UpperCamelCase							=			['past_key_values']
  _UpperCamelCase							=			{'num_attention_heads': 'encoder_attention_heads', 'hidden_size': 'd_model'}

  def __init__(self	:			List[str]						,			lowerCAmelCase_	:			str=5_00_05						,			lowerCAmelCase_	:			Any=10_24						,			lowerCAmelCase_	:			Dict=6						,			lowerCAmelCase_	:			int=30_72						,			lowerCAmelCase_	:			Union[str, Any]=12						,			lowerCAmelCase_	:			Union[str, Any]=6						,			lowerCAmelCase_	:			Any=30_72						,			lowerCAmelCase_	:			List[Any]=12						,			lowerCAmelCase_	:			str=0.0						,			lowerCAmelCase_	:			Any=0.0						,			lowerCAmelCase_	:			Optional[int]=True						,			lowerCAmelCase_	:			Optional[Any]=True						,			lowerCAmelCase_	:			Optional[int]="gelu"						,			lowerCAmelCase_	:			Tuple=7_68						,			lowerCAmelCase_	:			str=0.1						,			lowerCAmelCase_	:			Union[str, Any]=0.1						,			lowerCAmelCase_	:			str=0.0						,			lowerCAmelCase_	:			int=0.02						,			lowerCAmelCase_	:			List[Any]=0.0						,			lowerCAmelCase_	:			Optional[Any]=True						,			lowerCAmelCase_	:			List[str]=1						,			lowerCAmelCase_	:			Union[str, Any]=0						,			lowerCAmelCase_	:			List[str]=2						,			lowerCAmelCase_	:			Union[str, Any]=2						,			**lowerCAmelCase_	:			List[str]						,			) ->							Dict:
        snake_case_    							=				vocab_size
        snake_case_    							=				max_position_embeddings
        snake_case_    							=				d_model
        snake_case_    							=				encoder_ffn_dim
        snake_case_    							=				encoder_layers
        snake_case_    							=				encoder_attention_heads
        snake_case_    							=				decoder_ffn_dim
        snake_case_    							=				decoder_layers
        snake_case_    							=				decoder_attention_heads
        snake_case_    							=				dropout
        snake_case_    							=				attention_dropout
        snake_case_    							=				activation_dropout
        snake_case_    							=				activation_function
        snake_case_    							=				init_std
        snake_case_    							=				encoder_layerdrop
        snake_case_    							=				decoder_layerdrop
        snake_case_    							=				classifier_dropout
        snake_case_    							=				use_cache
        snake_case_    							=				encoder_layers
        snake_case_    							=				scale_embedding  # scale factor will be sqrt(d_model) if True
        super().__init__(
            pad_token_id=lowerCAmelCase_						,			bos_token_id=lowerCAmelCase_						,			eos_token_id=lowerCAmelCase_						,			is_encoder_decoder=lowerCAmelCase_						,			forced_eos_token_id=lowerCAmelCase_						,			**lowerCAmelCase_						,			)



class 			lowerCAmelCase__ (							UpperCamelCase							):



  '''simple docstring'''






  @property
  def 		_lowerCamelCase						(self	:			Any     ) ->							Mapping[str, Mapping[int, str]]:
        return OrderedDict(
            [
                ("input_ids", {0: "batch", 1: "sequence"}),
                ("attention_mask", {0: "batch", 1: "sequence"}),
            ]     )


  @property
  def 		_lowerCamelCase						(self	:			Dict     ) ->							Mapping[str, Mapping[int, str]]:
        if self.use_past:
              return OrderedDict(
                  [
                      ("last_hidden_state", {0: "batch", 1: "sequence"}),
                      ("past_keys", {0: "batch", 2: "sequence"}),
                      ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
                  ]     )
        else:
              return OrderedDict(
                  [
                      ("last_hidden_state", {0: "batch", 1: "sequence"}),
                      ("encoder_last_hidden_state", {0: "batch", 1: "sequence"}),
                  ]     )








"""simple docstring"""




def 		UpperCAmelCase__						(	_UpperCAmelCase					,   _UpperCAmelCase   ):






  """simple docstring"""





  A_    :			List[str]									=    (boundary[1] - boundary[0]) / steps
  A_    :			Optional[int]									=    boundary[0]
  A_    :			Optional[int]									=    boundary[1]
  A_    :			Any									=    make_points(_UpperCAmelCase					,   _UpperCAmelCase					,   _UpperCAmelCase   )
  A_    :			Dict									=    0.0
  y += (h / 3.0) * f(_UpperCAmelCase   )
  A_    :			Optional[int]									=    2
  for i in x_i:
    y += (h / 3) * (4 - 2 * (cnt % 2)) * f(_UpperCAmelCase   )
    cnt += 1
  y += (h / 3.0) * f(_UpperCAmelCase   )
  return y





def 		UpperCAmelCase__						(	_UpperCAmelCase					,   _UpperCAmelCase					,   _UpperCAmelCase   ):






  """simple docstring"""





  A_    :			Optional[Any]									=    a + h
  while x < (b - h):
    yield x
    A_    :			Dict									=    x + h





def 		UpperCAmelCase__						(	_UpperCAmelCase   ):  # enter your function here






  """simple docstring"""





  A_    :			List[Any]									=    (x - 0) * (x - 0)
  return y





def 		UpperCAmelCase__						(	):






  """simple docstring"""





  A_    :			int									=    0.0  # Lower bound of integration
  A_    :			int									=    1.0  # Upper bound of integration
  A_    :			Tuple									=    10.0  # define number of steps or resolution
  A_    :			List[str]									=    [a, b]  # define boundary of integration
  A_    :			Optional[Any]									=    method_a(_UpperCAmelCase					,   _UpperCAmelCase   )
  print(f"""y = {y}"""   )


if __name__ == "__main__":
   main()