


'''simple docstring'''







from typing import Mapping

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


a__    :   Tuple								=			logging.get_logger(__name__)
class    lowercase_	(       a__  ):
    __UpperCAmelCase       =      'mt5'
    __UpperCAmelCase       =      ['past_key_values']


    def __init__(	self    ,   a=25_01_12    ,   a=5_12    ,   a=64    ,   a=10_24    ,   a=8    ,   a=None    ,   a=6    ,   a=32    ,   a=1_28    ,   a=0.1    ,   a=1e-6    ,   a=1.0    ,   a="gated-gelu"    ,   a=True    ,   a=True    ,   a="T5Tokenizer"    ,   a=False    ,   a=0    ,   a=1    ,   a=0    ,   **a    ,   ):
          super().__init__(
              is_encoder_decoder=a    ,   tokenizer_class=a    ,   tie_word_embeddings=a    ,   pad_token_id=a    ,   eos_token_id=a    ,   decoder_start_token_id=a    ,   **a    ,   )
          UpperCamelCase__      =							vocab_size
          UpperCamelCase__      =							d_model
          UpperCamelCase__      =							d_kv
          UpperCamelCase__      =							d_ff
          UpperCamelCase__      =							num_layers
          UpperCamelCase__      =							(
              num_decoder_layers if num_decoder_layers is not None else self.num_layers
          )  # default = symmetry
          UpperCamelCase__      =							num_heads
          UpperCamelCase__      =							relative_attention_num_buckets
          UpperCamelCase__      =							relative_attention_max_distance
          UpperCamelCase__      =							dropout_rate
          UpperCamelCase__      =							layer_norm_epsilon
          UpperCamelCase__      =							initializer_factor
          UpperCamelCase__      =							feed_forward_proj
          UpperCamelCase__      =							use_cache

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

          if len(a       ) > 1 and act_info[0] != "gated" or len(a       ) > 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__      =							"gelu_new"


    @property
    def   __a				(	self       ):
          return self.d_model


    @property
    def   __a				(	self       ):
          return self.num_heads


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

class    lowercase_	(       a__  ):


    @property
    # Copied from transformers.models.t5.configuration_t5.T5OnnxConfig.inputs
    def   __a				(	self       ):
          UpperCamelCase__      =							{
              "input_ids": {0: "batch", 1: "encoder_sequence"},
              "attention_mask": {0: "batch", 1: "encoder_sequence"},
          }
          if self.use_past:
                UpperCamelCase__      =							"past_encoder_sequence + sequence"
                UpperCamelCase__      =							{0: "batch"}
                UpperCamelCase__      =							{0: "batch", 1: "past_decoder_sequence + sequence"}
          else:
                UpperCamelCase__      =							{0: "batch", 1: "decoder_sequence"}
                UpperCamelCase__      =							{0: "batch", 1: "decoder_sequence"}

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

          return common_inputs


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


    @property
    def   __a				(	self       ):
          return 5e-4









'''simple docstring'''







from __future__ import annotations

from enum import Enum, unique
from typing import TypeVar

# Create a generic variable that can be 'Enum', or any subclass.
a__    :   Optional[Any]								=			TypeVar('T', bound='Enum')
@unique
class    lowercase_	(       a__  ):
    __UpperCAmelCase       =      80
    __UpperCAmelCase       =      70
    __UpperCAmelCase       =      60
    __UpperCAmelCase       =      50
    __UpperCAmelCase       =      40
    __UpperCAmelCase       =      30
    __UpperCAmelCase       =      20
    __UpperCAmelCase       =      10

@unique
class    lowercase_	(       a__  ):
    __UpperCAmelCase       =      24
    __UpperCAmelCase       =      21
    __UpperCAmelCase       =      18
    __UpperCAmelCase       =      15
    __UpperCAmelCase       =      12
    __UpperCAmelCase       =      9
    __UpperCAmelCase       =      6
    __UpperCAmelCase       =      3
    __UpperCAmelCase       =      2
    __UpperCAmelCase       =      1
    __UpperCAmelCase       =      -1
    __UpperCAmelCase       =      -2
    __UpperCAmelCase       =      -3
    __UpperCAmelCase       =      -6
    __UpperCAmelCase       =      -9
    __UpperCAmelCase       =      -12
    __UpperCAmelCase       =      -15
    __UpperCAmelCase       =      -18
    __UpperCAmelCase       =      -21
    __UpperCAmelCase       =      -24


    @classmethod
    def   __a				(	cls       ):
          return {unit.name: unit.value for unit in cls if unit.value > 0}


    @classmethod
    def   __a				(	cls       ):
          return {unit.name: unit.value for unit in cls if unit.value < 0}







def _UpperCamelCase			(	__A       )				->						str:


      '''simple docstring'''



      UpperCamelCase__      =							SIUnit.get_positive() if value > 0 else SIUnit.get_negative()
      for name_prefix, value_prefix in prefixes.items():
            UpperCamelCase__      =							value / (10**value_prefix)
            if numerical_part > 1:
                  return F'''{numerical_part!s} {name_prefix}'''
      return str(__A       )







def _UpperCamelCase			(	__A       )				->						str:


      '''simple docstring'''



      for prefix in BinaryUnit:
            UpperCamelCase__      =							value / (2**prefix.value)
            if numerical_part > 1:
                  return F'''{numerical_part!s} {prefix.name}'''
      return str(__A       )


if __name__ == "__main__":
  import doctest

  doctest.testmod()





