
'''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"}),
                  ]     )








import enum
import inspect
import warnings
from functools import wraps
from typing import Callable, Optional

from .logging import get_logger


A_        =  set()
A_        =  get_logger(__name__)





def  __UpperCamelCase   (     a = None)			->str:

					def decorator(a):
										global _emitted_deprecation_warnings

										if inspect.isclass(a):
															lowerCamelCase__      =							deprecated_class_or_function.__init__
															lowerCamelCase__      =							deprecated_class_or_function.__name__
										else:
															lowerCamelCase__      =							deprecated_class_or_function
															lowerCamelCase__      =							deprecated_function.__name__
															# Support deprecating __init__ class method: class name instead
															lowerCamelCase__      =							name if name != "__init__" else deprecated_function.__qualname__.split(".")[-2]

										lowerCamelCase__      =							(
										    f"{name} is deprecated and will be removed in the next major version of datasets." + f" {help_message}"
										    if help_message
										    else ""
										)

										@wraps(a)
										def wrapper(*a,  **a):
															lowerCamelCase__      =							hash(a)
															if func_hash not in _emitted_deprecation_warnings:
																				warnings.warn(a,  category=a,  stacklevel=2)
																				_emitted_deprecation_warnings.add(a)
															return deprecated_function(*a,  **a)

										lowerCamelCase__      =							"deprecated"

										if inspect.isclass(a):
															lowerCamelCase__      =							wrapper
															return deprecated_class_or_function
										else:
															return wrapper

					return decorator

class SCREAMING_SNAKE_CASE_			(       enum.EnumMeta ):





					"""simple docstring"""


					def __getattribute__(			cls						,	_lowerCAmelCase						):
										lowerCamelCase__      =							super().__getattribute__(_lowerCAmelCase						)
										if isinstance(_lowerCAmelCase						,	enum.Enum						) and obj._on_access:
															obj._on_access()
										return obj





					def __getitem__(			cls						,	_lowerCAmelCase						):
										lowerCamelCase__      =							super().__getitem__(_lowerCAmelCase						)
										if member._on_access:
															member._on_access()
										return member






					def __call__(			cls						,	_lowerCAmelCase						,	_lowerCAmelCase=None						,	*, _lowerCAmelCase=None						,	_lowerCAmelCase=None						,	_lowerCAmelCase=None						,	_lowerCAmelCase=1						):
										lowerCamelCase__      =							super().__call__(_lowerCAmelCase						,	_lowerCAmelCase						,	module=_lowerCAmelCase						,	qualname=_lowerCAmelCase						,	type=_lowerCAmelCase						,	start=_lowerCAmelCase						)
										if isinstance(_lowerCAmelCase						,	enum.Enum						) and obj._on_access:
															obj._on_access()
										return obj

class SCREAMING_SNAKE_CASE_			(       enum.Enum				,							metaclass=lowercase_ ):





					"""simple docstring"""


					def __new__(			cls						,	_lowerCAmelCase						):
										lowerCamelCase__      =							object.__new__(cls						)
										lowerCamelCase__      =							value
										lowerCamelCase__      =							member.deprecate
										return member





					@property
					def        __magic_name__			(			self						):
										return ""






					def        __magic_name__			(			self						):
										lowerCamelCase__      =							F" {self.help_message}" if self.help_message else ""
										warnings.warn(
										    F"'{self.__objclass__.__name__}' is deprecated and will be removed in the next major version of datasets."
										    + help_message						,	_lowerCAmelCase						,	stacklevel=3						,	)

