"""simple docstring"""



from typing import Mapping

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


SCREAMING_SNAKE_CASE__:List[Any]			=	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE__:Optional[Any]			=	{
    '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 				snake_case__     (   lowerCamelCase__   ):
 _snake_case   :			Union[str, Any]           =		"""t5"""
 _snake_case   :			Dict           =		["""past_key_values"""]
 _snake_case   :			List[Any]           =		{"""hidden_size""": """d_model""", """num_attention_heads""": """num_heads""", """num_hidden_layers""": """num_layers"""}


 def __init__(				self  ,						lowerCamelCase=32128  ,						lowerCamelCase=512  ,						lowerCamelCase=64  ,						lowerCamelCase=2048  ,						lowerCamelCase=6  ,						lowerCamelCase=None  ,						lowerCamelCase=8  ,						lowerCamelCase=32  ,						lowerCamelCase=128  ,						lowerCamelCase=0.1  ,						lowerCamelCase=1E-6  ,						lowerCamelCase=1.0  ,						lowerCamelCase="relu"  ,						lowerCamelCase=True  ,						lowerCamelCase=True  ,						lowerCamelCase=0  ,						lowerCamelCase=1  ,						**lowerCamelCase  ,						):
        __a     				=  vocab_size
        __a     				=  d_model
        __a     				=  d_kv
        __a     				=  d_ff
        __a     				=  num_layers
        __a     				=  (
            num_decoder_layers if num_decoder_layers is not None else self.num_layers
        )  # default = symmetry
        __a     				=  num_heads
        __a     				=  relative_attention_num_buckets
        __a     				=  relative_attention_max_distance
        __a     				=  dropout_rate
        __a     				=  layer_norm_epsilon
        __a     				=  initializer_factor
        __a     				=  feed_forward_proj
        __a     				=  use_cache

        __a     				=  self.feed_forward_proj.split("-"		)
        __a     				=  act_info[-1]
        __a     				=  act_info[0] == 'gated'

        if len(__snake_case		) > 1 and act_info[0] != "gated" or len(__snake_case		) > 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":
               __a     				=  'gelu_new'

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






class 				snake_case__     (   lowerCamelCase__   ):


 @property
 def 		a__ (				self		):
        __a     				=  {
            'input_ids': {0: 'batch', 1: 'encoder_sequence'},
            'attention_mask': {0: 'batch', 1: 'encoder_sequence'},
        }
        if self.use_past:
               __a     				=  'past_encoder_sequence + sequence'
               __a     				=  {0: 'batch'}
               __a     				=  {0: 'batch', 1: 'past_decoder_sequence + sequence'}
        else:
               __a     				=  {0: 'batch', 1: 'decoder_sequence'}
               __a     				=  {0: 'batch', 1: 'decoder_sequence'}

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

        return common_inputs






 @property
 def 		a__ (				self		):
        return 13

"""simple docstring"""



from ..utils import DummyObject, requires_backends






class 				snake_case__     (   metaclass=snake_case_   ):
 _snake_case   :			Union[str, Any]           =		["""onnx"""]


 def __init__(				self  ,						*lowerCamelCase  ,						**lowerCamelCase		):
        requires_backends(self  ,						["onnx"]		)


 @classmethod
 def 		a__ (				cls  ,						*lowerCamelCase  ,						**lowerCamelCase		):
        requires_backends(cls  ,						["onnx"]		)






 @classmethod
 def 		a__ (				cls  ,						*lowerCamelCase  ,						**lowerCamelCase		):
        requires_backends(cls  ,						["onnx"]		)
