
"""simple docstring"""




from typing import Mapping

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


A__   :						str 							=     logging.get_logger(__name__)

A__   :						Tuple 							=     {
    """google/long-t5-local-base""": """https://huggingface.co/google/long-t5-local-base/blob/main/config.json""",
    """google/long-t5-local-large""": """https://huggingface.co/google/long-t5-local-large/blob/main/config.json""",
    """google/long-t5-tglobal-base""": """https://huggingface.co/google/long-t5-tglobal-base/blob/main/config.json""",
    """google/long-t5-tglobal-large""": """https://huggingface.co/google/long-t5-tglobal-large/blob/main/config.json""",
}







class 	_lowercase    (							lowerCAmelCase_					):


     '''simple docstring'''





     _A		    =				'longt5'
     _A		    =				['past_key_values']
     _A		    =				{'hidden_size': 'd_model', 'num_attention_heads': 'num_heads', 'num_hidden_layers': 'num_layers'}



     def __init__(   self			,      __UpperCamelCase=3_21_28			,      __UpperCamelCase=5_12			,      __UpperCamelCase=64			,      __UpperCamelCase=20_48			,      __UpperCamelCase=6			,      __UpperCamelCase=None			,      __UpperCamelCase=8			,      __UpperCamelCase=1_27			,      __UpperCamelCase=16			,      __UpperCamelCase=32			,      __UpperCamelCase=1_28			,      __UpperCamelCase=0.1			,      __UpperCamelCase=1E-6			,      __UpperCamelCase=1.0			,      __UpperCamelCase="relu"			,      __UpperCamelCase=True			,      __UpperCamelCase="local"			,      __UpperCamelCase=True			,      __UpperCamelCase=0			,      __UpperCamelCase=1			,      **__UpperCamelCase			,      )->       Tuple:
          UpperCAmelCase__				:			int							=    vocab_size
          UpperCAmelCase__				:			int							=    d_model
          UpperCAmelCase__				:			int							=    d_kv
          UpperCAmelCase__				:			Union[str, Any]							=    d_ff
          UpperCAmelCase__				:			Any							=    num_layers
          # default = symmetry
          UpperCAmelCase__				:			Dict							=    num_decoder_layers if num_decoder_layers is not None else self.num_layers
          UpperCAmelCase__				:			Optional[Any]							=    num_heads
          UpperCAmelCase__				:			List[Any]							=    local_radius
          UpperCAmelCase__				:			Optional[Any]							=    global_block_size
          UpperCAmelCase__				:			Any							=    relative_attention_num_buckets
          UpperCAmelCase__				:			List[str]							=    relative_attention_max_distance
          UpperCAmelCase__				:			Optional[int]							=    dropout_rate
          UpperCAmelCase__				:			Union[str, Any]							=    layer_norm_epsilon
          UpperCAmelCase__				:			Optional[int]							=    initializer_factor
          UpperCAmelCase__				:			int							=    feed_forward_proj
          UpperCAmelCase__				:			List[Any]							=    encoder_attention_type
          UpperCAmelCase__				:			Any							=    use_cache

          UpperCAmelCase__				:			Optional[Any]							=    self.feed_forward_proj.split("-"	)
          UpperCAmelCase__				:			List[str]							=    act_info[-1]
          UpperCAmelCase__				:			Any							=    act_info[0] == "gated"

          if len(__UpperCamelCase	) > 1 and act_info[0] != "gated" or len(__UpperCamelCase	) > 2:
               raise ValueError(
                   F"`feed_forward_proj`: {feed_forward_proj} is not a valid activation function of the dense layer."
                   "Please make sure `feed_forward_proj` is of the format `gated-{ACT_FN}` or `{ACT_FN}`, e.g. "
                   "'gated-gelu' or 'relu'"	)

          # for backwards compatibility
          if feed_forward_proj == "gated-gelu":
               UpperCAmelCase__				:			int							=    "gelu_new"

          super().__init__(
              pad_token_id=__UpperCamelCase			,      eos_token_id=__UpperCamelCase			,      is_encoder_decoder=__UpperCamelCase			,      **__UpperCamelCase			,      )







class 	_lowercase    (							lowerCAmelCase_					):


     '''simple docstring'''





     @property
     def 			lowerCAmelCase__							(   self	)->       Mapping[str, Mapping[int, str]]:
          UpperCAmelCase__				:			Optional[int]							=    {
              "input_ids": {0: "batch", 1: "encoder_sequence"},
              "attention_mask": {0: "batch", 1: "encoder_sequence"},
          }
          if self.use_past:
               UpperCAmelCase__				:			Union[str, Any]							=    "past_encoder_sequence + sequence"
               UpperCAmelCase__				:			List[Any]							=    {0: "batch"}
               UpperCAmelCase__				:			Dict							=    {0: "batch", 1: "past_decoder_sequence + sequence"}
          else:
               UpperCAmelCase__				:			int							=    {0: "batch", 1: "decoder_sequence"}
               UpperCAmelCase__				:			List[str]							=    {0: "batch", 1: "decoder_sequence"}

          if self.use_past:
               self.fill_with_past_key_values_(__UpperCamelCase			,      direction="inputs"	)

          return common_inputs



     @property
     def 			lowerCAmelCase__							(   self	)->       int:
          return 13





"""simple docstring"""




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

from .logging import get_logger


A__   :						Optional[Any] 							=     set()
A__   :						List[str] 							=     get_logger(__name__)



def 				a__			(					lowerCAmelCase						:							Optional[str] = None		):






     '''simple docstring'''

     def decorator(lowerCAmelCase						:							Callable		):
          global _emitted_deprecation_warnings

          if inspect.isclass(lowerCAmelCase		):
               UpperCAmelCase__				:			Any							=    deprecated_class_or_function.__init__
               UpperCAmelCase__				:			Optional[int]							=    deprecated_class_or_function.__name__
          else:
               UpperCAmelCase__				:			str							=    deprecated_class_or_function
               UpperCAmelCase__				:			List[Any]							=    deprecated_function.__name__
               # Support deprecating __init__ class method: class name instead
               UpperCAmelCase__				:			List[str]							=    name if name != "__init__" else deprecated_function.__qualname__.split("."		)[-2]

          UpperCAmelCase__				:			Optional[Any]							=    (
              F"{name} is deprecated and will be removed in the next major version of datasets." + F" {help_message}"
              if help_message
              else ""
          )

          @wraps(lowerCAmelCase		)
          def wrapper(*lowerCAmelCase						:							int							,     **lowerCAmelCase						:							str		):
               UpperCAmelCase__				:			List[str]							=    hash(lowerCAmelCase		)
               if func_hash not in _emitted_deprecation_warnings:
                    warnings.warn(lowerCAmelCase							,     category=lowerCAmelCase							,     stacklevel=2		)
                    _emitted_deprecation_warnings.add(lowerCAmelCase		)
               return deprecated_function(*lowerCAmelCase							,     **lowerCAmelCase		)

          UpperCAmelCase__				:			List[str]							=    "deprecated"

          if inspect.isclass(lowerCAmelCase		):
               UpperCAmelCase__				:			List[str]							=    wrapper
               return deprecated_class_or_function
          else:
               return wrapper

     return decorator







class 	_lowercase    (							enum.EnumMeta					):


     '''simple docstring'''





     def __getattribute__(   cls			,      __UpperCamelCase	)->       Optional[Any]:
          UpperCAmelCase__				:			Optional[int]							=    super().__getattribute__(__UpperCamelCase	)
          if isinstance(__UpperCamelCase			,      enum.Enum	) and obj._on_access:
               obj._on_access()
          return obj



     def __getitem__(   cls			,      __UpperCamelCase	)->       Optional[int]:
          UpperCAmelCase__				:			Union[str, Any]							=    super().__getitem__(__UpperCamelCase	)
          if member._on_access:
               member._on_access()
          return member



     def __call__(   cls			,      __UpperCamelCase			,      __UpperCamelCase=None			,      *, __UpperCamelCase=None			,      __UpperCamelCase=None			,      __UpperCamelCase=None			,      __UpperCamelCase=1	)->       Dict:
          UpperCAmelCase__				:			Optional[int]							=    super().__call__(__UpperCamelCase			,      __UpperCamelCase			,      module=__UpperCamelCase			,      qualname=__UpperCamelCase			,      type=__UpperCamelCase			,      start=__UpperCamelCase	)
          if isinstance(__UpperCamelCase			,      enum.Enum	) and obj._on_access:
               obj._on_access()
          return obj







class 	_lowercase    (							enum.Enum						, metaclass=lowerCAmelCase_					):


     '''simple docstring'''





     def __new__(   cls			,      __UpperCamelCase	)->       Union[str, Any]:
          UpperCAmelCase__				:			int							=    object.__new__(cls	)
          UpperCAmelCase__				:			int							=    value
          UpperCAmelCase__				:			Optional[int]							=    member.deprecate
          return member



     @property
     def 			lowerCAmelCase__							(   self	)->       Union[str, Any]:
          return ""



     def 			lowerCAmelCase__							(   self	)->       int:
          UpperCAmelCase__				:			Tuple							=    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			,      __UpperCamelCase			,      stacklevel=3			,      )



