





from typing import Mapping

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


__A							   =							logging.get_logger(__name__)

__A							   =							{
    "t5-small": "https://huggingface.co/t5-small/resolve/main/config.json",
    "t5-base": "https://huggingface.co/t5-base/resolve/main/config.json",
    "t5-large": "https://huggingface.co/t5-large/resolve/main/config.json",
    "t5-3b": "https://huggingface.co/t5-3b/resolve/main/config.json",
    "t5-11b": "https://huggingface.co/t5-11b/resolve/main/config.json",
}



class   _SCREAMING_SNAKE_CASE		(      __SCREAMING_SNAKE_CASE       ):







 '''simple docstring'''
 lowercase_						=     "t5"
 lowercase_						=     ["past_key_values"]
 lowercase_						=     {"hidden_size": "d_model", "num_attention_heads": "num_heads", "num_hidden_layers": "num_layers"}

 def __init__(self							:  List[str]			,					UpperCAmelCase_							:  int=32_128			,					UpperCAmelCase_							:  Dict=512			,					UpperCAmelCase_							:  List[Any]=64			,					UpperCAmelCase_							:  int=2_048			,					UpperCAmelCase_							:  Optional[Any]=6			,					UpperCAmelCase_							:  List[Any]=None			,					UpperCAmelCase_							:  Optional[int]=8			,					UpperCAmelCase_							:  Dict=32			,					UpperCAmelCase_							:  List[str]=128			,					UpperCAmelCase_							:  Dict=0.1			,					UpperCAmelCase_							:  int=1E-6			,					UpperCAmelCase_							:  Any=1.0			,					UpperCAmelCase_							:  Optional[Any]="relu"			,					UpperCAmelCase_							:  Tuple=True			,					UpperCAmelCase_							:  Optional[Any]=True			,					UpperCAmelCase_							:  Any=0			,					UpperCAmelCase_							:  str=1			,					**UpperCAmelCase_							:  str			,					)			->str:



   '''simple docstring'''



   lowerCamelCase__: int         =vocab_size
   lowerCamelCase__: Optional[int]         =d_model
   lowerCamelCase__: List[str]         =d_kv
   lowerCamelCase__: Optional[Any]         =d_ff
   lowerCamelCase__: Tuple         =num_layers
   lowerCamelCase__: str         =(
       num_decoder_layers if num_decoder_layers is not None else self.num_layers
   )  # default = symmetry
   lowerCamelCase__: Optional[int]         =num_heads
   lowerCamelCase__: Optional[Any]         =relative_attention_num_buckets
   lowerCamelCase__: Optional[int]         =relative_attention_max_distance
   lowerCamelCase__: Tuple         =dropout_rate
   lowerCamelCase__: Union[str, Any]         =layer_norm_epsilon
   lowerCamelCase__: str         =initializer_factor
   lowerCamelCase__: List[str]         =feed_forward_proj
   lowerCamelCase__: str         =use_cache

   lowerCamelCase__: Dict         =self.feed_forward_proj.split("-")
   lowerCamelCase__: Optional[int]         =act_info[-1]
   lowerCamelCase__: Optional[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":
     lowerCamelCase__: Union[str, Any]         ="gelu_new"

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



class   _SCREAMING_SNAKE_CASE		(      __SCREAMING_SNAKE_CASE       ):







 '''simple docstring'''

 @property
 def 				SCREAMING_SNAKE_CASE_   (self							:  Optional[int])			->Mapping[str, Mapping[int, str]]:



   '''simple docstring'''



   lowerCamelCase__: Dict         ={
       "input_ids": {0: "batch", 1: "encoder_sequence"},
       "attention_mask": {0: "batch", 1: "encoder_sequence"},
   }
   if self.use_past:
     lowerCamelCase__: Tuple         ="past_encoder_sequence + sequence"
     lowerCamelCase__: str         ={0: "batch"}
     lowerCamelCase__: Optional[Any]         ={0: "batch", 1: "past_decoder_sequence + sequence"}
   else:
     lowerCamelCase__: Optional[int]         ={0: "batch", 1: "decoder_sequence"}
     lowerCamelCase__: Optional[int]         ={0: "batch", 1: "decoder_sequence"}

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

   return common_inputs







 @property
 def 				SCREAMING_SNAKE_CASE_   (self							:  Optional[int])			->int:



   '''simple docstring'''



   return 13






'''simple docstring'''

from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
    MaskedBertForMultipleChoice,
    MaskedBertForQuestionAnswering,
    MaskedBertForSequenceClassification,
    MaskedBertForTokenClassification,
    MaskedBertModel,
)
from .modules import *




