





'''simple docstring'''






from ...configuration_utils import PretrainedConfig
from ...utils import logging


A_		:  Optional[Any]		 =						logging.get_logger(__name__)

A_		:  int		 =						{
    "uw-madison/mra-base-512-4": "https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json",
}
class 					__snake_case  (					__SCREAMING_SNAKE_CASE							):






   '''simple docstring'''





   lowerCamelCase__    							=      '''mra'''

   def __init__(							self	,		__SCREAMING_SNAKE_CASE=5_0_2_6_5	,		__SCREAMING_SNAKE_CASE=7_6_8	,		__SCREAMING_SNAKE_CASE=1_2	,		__SCREAMING_SNAKE_CASE=1_2	,		__SCREAMING_SNAKE_CASE=3_0_7_2	,		__SCREAMING_SNAKE_CASE="gelu"	,		__SCREAMING_SNAKE_CASE=0.1	,		__SCREAMING_SNAKE_CASE=0.1	,		__SCREAMING_SNAKE_CASE=5_1_2	,		__SCREAMING_SNAKE_CASE=1	,		__SCREAMING_SNAKE_CASE=0.02	,		__SCREAMING_SNAKE_CASE=1e-5	,		__SCREAMING_SNAKE_CASE="absolute"	,		__SCREAMING_SNAKE_CASE=4	,		__SCREAMING_SNAKE_CASE="full"	,		__SCREAMING_SNAKE_CASE=0	,		__SCREAMING_SNAKE_CASE=0	,		__SCREAMING_SNAKE_CASE=1	,		__SCREAMING_SNAKE_CASE=0	,		__SCREAMING_SNAKE_CASE=2	,		**__SCREAMING_SNAKE_CASE	,		):
    super().__init__(pad_token_id=__SCREAMING_SNAKE_CASE	,		bos_token_id=__SCREAMING_SNAKE_CASE	,		eos_token_id=__SCREAMING_SNAKE_CASE	,		**__SCREAMING_SNAKE_CASE       )

    snake_case__     :					List[Any]    =  vocab_size
    snake_case__     :					Optional[int]    =  max_position_embeddings
    snake_case__     :					List[Any]    =  hidden_size
    snake_case__     :					Tuple    =  num_hidden_layers
    snake_case__     :					List[Any]    =  num_attention_heads
    snake_case__     :					Dict    =  intermediate_size
    snake_case__     :					str    =  hidden_act
    snake_case__     :					Optional[Any]    =  hidden_dropout_prob
    snake_case__     :					Tuple    =  attention_probs_dropout_prob
    snake_case__     :					Dict    =  initializer_range
    snake_case__     :					List[str]    =  type_vocab_size
    snake_case__     :					str    =  layer_norm_eps
    snake_case__     :					Dict    =  position_embedding_type
    snake_case__     :					Union[str, Any]    =  block_per_row
    snake_case__     :					str    =  approx_mode
    snake_case__     :					int    =  initial_prior_first_n_blocks
    snake_case__     :					str    =  initial_prior_diagonal_n_blocks












from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__a:     int   					=					{
    '''configuration_mvp''': ['''MVP_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MvpConfig''', '''MvpOnnxConfig'''],
    '''tokenization_mvp''': ['''MvpTokenizer'''],
}

try:
  if not is_tokenizers_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a:     Dict   					=					['''MvpTokenizerFast''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a:     Tuple   					=					[
      '''MVP_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''MvpForCausalLM''',
      '''MvpForConditionalGeneration''',
      '''MvpForQuestionAnswering''',
      '''MvpForSequenceClassification''',
      '''MvpModel''',
      '''MvpPreTrainedModel''',
  ]

if TYPE_CHECKING:
  from .configuration_mvp import MVP_PRETRAINED_CONFIG_ARCHIVE_MAP, MvpConfig, MvpOnnxConfig
  from .tokenization_mvp import MvpTokenizer

  try:
    if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_mvp_fast import MvpTokenizerFast

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_mvp import (
        MVP_PRETRAINED_MODEL_ARCHIVE_LIST,
        MvpForCausalLM,
        MvpForConditionalGeneration,
        MvpForQuestionAnswering,
        MvpForSequenceClassification,
        MvpModel,
        MvpPreTrainedModel,
    )

else:
  import sys

  __a:     Optional[Any]   					=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)