


from typing import Mapping

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


SCREAMING_SNAKE_CASE       :		Dict         =				logging.get_logger(__name__)

SCREAMING_SNAKE_CASE       :		List[Any]         =				{
    "google/umt5-small": "https://huggingface.co/google/umt5-small/resolve/main/config.json",
    # See all umt5 models at https://huggingface.co/models?filter=umt5
}






class 							UpperCamelCase					(		__A     ):


   '''simple docstring'''







   lowercase					:	List[str]									="""umt5"""
   lowercase					:	Dict									=["""past_key_values"""]
   def __init__(     self   ,							UpperCamelCase_=25_0112   ,							UpperCamelCase_=512   ,							UpperCamelCase_=64   ,							UpperCamelCase_=1024   ,							UpperCamelCase_=8   ,							UpperCamelCase_=None   ,							UpperCamelCase_=6   ,							UpperCamelCase_=32   ,							UpperCamelCase_=128   ,							UpperCamelCase_=0.1   ,							UpperCamelCase_=1E-6   ,							UpperCamelCase_=1.0   ,							UpperCamelCase_="gated-gelu"   ,							UpperCamelCase_=True   ,							UpperCamelCase_=True   ,							UpperCamelCase_="T5Tokenizer"   ,							UpperCamelCase_=True   ,							UpperCamelCase_=0   ,							UpperCamelCase_=1   ,							UpperCamelCase_=0   ,							**UpperCamelCase_   ,							):
        super().__init__(
            is_encoder_decoder=UpperCamelCase_   ,							tokenizer_class=UpperCamelCase_   ,							tie_word_embeddings=UpperCamelCase_   ,							pad_token_id=UpperCamelCase_   ,							eos_token_id=UpperCamelCase_   ,							decoder_start_token_id=UpperCamelCase_   ,							**UpperCamelCase_   ,							)
        lowercase_       :Optional[Any]     =       vocab_size
        lowercase_       :List[Any]     =       d_model
        lowercase_       :Optional[Any]     =       d_kv
        lowercase_       :Any     =       d_ff
        lowercase_       :Union[str, Any]     =       num_layers
        lowercase_       :Optional[int]     =       (
            num_decoder_layers if num_decoder_layers is not None else self.num_layers
        )  # default = symmetry
        lowercase_       :int     =       num_heads
        lowercase_       :Tuple     =       relative_attention_num_buckets
        lowercase_       :int     =       relative_attention_max_distance
        lowercase_       :Tuple     =       dropout_rate
        lowercase_       :List[str]     =       layer_norm_epsilon
        lowercase_       :Union[str, Any]     =       initializer_factor
        lowercase_       :int     =       feed_forward_proj
        lowercase_       :List[Any]     =       use_cache

        lowercase_       :List[Any]     =       self.feed_forward_proj.split('''-'''		)
        lowercase_       :Dict     =       act_info[-1]
        lowercase_       :Tuple     =       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\''''		)

        if feed_forward_proj == "gated-gelu":
             lowercase_       :List[Any]     =       '''gelu_new'''
   @property
   def 		UpperCamelCase  (     self		):
        return self.d_model
   @property
   def 		UpperCamelCase  (     self		):
        return self.num_heads




   @property
   def 		UpperCamelCase  (     self		):
        return self.num_layers






class 							UpperCamelCase					(		__A     ):


   '''simple docstring'''







   @property
   # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.inputs
   def 		UpperCamelCase  (     self		):
        lowercase_       :List[str]     =       {
            '''input_ids''': {0: '''batch''', 1: '''encoder_sequence'''},
            '''attention_mask''': {0: '''batch''', 1: '''encoder_sequence'''},
        }
        if self.use_past:
             lowercase_       :Union[str, Any]     =       '''past_encoder_sequence + sequence'''
             lowercase_       :Tuple     =       {0: '''batch'''}
             lowercase_       :Any     =       {0: '''batch''', 1: '''past_decoder_sequence + sequence'''}
        else:
             lowercase_       :Dict     =       {0: '''batch''', 1: '''decoder_sequence'''}
             lowercase_       :List[str]     =       {0: '''batch''', 1: '''decoder_sequence'''}

        if self.use_past:
             self.fill_with_past_key_values_(UpperCamelCase_   ,							direction='''inputs'''		)

        return common_inputs
   @property
   # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.default_onnx_opset
   def 		UpperCamelCase  (     self		):
        return 13




   @property
   def 		UpperCamelCase  (     self		):
        return 5E-4





from torch import nn




def     UpperCamelCase    (      _a		)					->							str:
     '''simple docstring'''





     if act_fn in ["swish", "silu"]:
          return nn.SiLU()
     elif act_fn == "mish":
          return nn.Mish()
     elif act_fn == "gelu":
          return nn.GELU()
     else:
          raise ValueError(f"Unsupported activation function: {act_fn}"		)

