





'''simple docstring'''






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


__A :  Any    							=				logging.get_logger(__name__)

__A :  List[str]    							=				{
    "google/canine-s": "https://huggingface.co/google/canine-s/resolve/main/config.json",
    # See all CANINE models at https://huggingface.co/models?filter=canine
}






class        __snake_case	(       _SCREAMING_SNAKE_CASE):







    """simple docstring"""



    lowercase       			= 'canine'

    def __init__(       self   :  int   ,						lowerCamelCase   :  Union[str, Any]=7_68   ,						lowerCamelCase   :  Union[str, Any]=12   ,						lowerCamelCase   :  List[Any]=12   ,						lowerCamelCase   :  Optional[Any]=30_72   ,						lowerCamelCase   :  str="gelu"   ,						lowerCamelCase   :  Optional[int]=0.1   ,						lowerCamelCase   :  Tuple=0.1   ,						lowerCamelCase   :  Optional[Any]=1_63_84   ,						lowerCamelCase   :  str=16   ,						lowerCamelCase   :  Tuple=0.02   ,						lowerCamelCase   :  int=1E-12   ,						lowerCamelCase   :  Dict=0   ,						lowerCamelCase   :  Optional[Any]=0xE000   ,						lowerCamelCase   :  Dict=0xE001   ,						lowerCamelCase   :  Tuple=4   ,						lowerCamelCase   :  str=4   ,						lowerCamelCase   :  Tuple=8   ,						lowerCamelCase   :  List[str]=1_63_84   ,						lowerCamelCase   :  Dict=1_28   ,						**lowerCamelCase   :  Tuple   ,						)       ->  Dict:
      super().__init__(pad_token_id=_a   ,						bos_token_id=_a   ,						eos_token_id=_a   ,						**_a		)

      lowerCAmelCase_      :				Union[str, Any]      =       max_position_embeddings
      lowerCAmelCase_      :				str      =       hidden_size
      lowerCAmelCase_      :				Union[str, Any]      =       num_hidden_layers
      lowerCAmelCase_      :				Any      =       num_attention_heads
      lowerCAmelCase_      :				Tuple      =       intermediate_size
      lowerCAmelCase_      :				Optional[int]      =       hidden_act
      lowerCAmelCase_      :				int      =       hidden_dropout_prob
      lowerCAmelCase_      :				Any      =       attention_probs_dropout_prob
      lowerCAmelCase_      :				Optional[Any]      =       initializer_range
      lowerCAmelCase_      :				Any      =       type_vocab_size
      lowerCAmelCase_      :				List[Any]      =       layer_norm_eps

      # Character config:
      lowerCAmelCase_      :				Any      =       downsampling_rate
      lowerCAmelCase_      :				Optional[int]      =       upsampling_kernel_size
      lowerCAmelCase_      :				List[Any]      =       num_hash_functions
      lowerCAmelCase_      :				Tuple      =       num_hash_buckets
      lowerCAmelCase_      :				Tuple      =       local_transformer_stride







'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__A :  List[str]    							=				{
    "configuration_bigbird_pegasus": [
        "BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "BigBirdPegasusConfig",
        "BigBirdPegasusOnnxConfig",
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __A :  Union[str, Any]    							=				[
      "BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST",
      "BigBirdPegasusForCausalLM",
      "BigBirdPegasusForConditionalGeneration",
      "BigBirdPegasusForQuestionAnswering",
      "BigBirdPegasusForSequenceClassification",
      "BigBirdPegasusModel",
      "BigBirdPegasusPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_bigbird_pegasus import (
      BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP,
      BigBirdPegasusConfig,
      BigBirdPegasusOnnxConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_bigbird_pegasus import (
        BIGBIRD_PEGASUS_PRETRAINED_MODEL_ARCHIVE_LIST,
        BigBirdPegasusForCausalLM,
        BigBirdPegasusForConditionalGeneration,
        BigBirdPegasusForQuestionAnswering,
        BigBirdPegasusForSequenceClassification,
        BigBirdPegasusModel,
        BigBirdPegasusPreTrainedModel,
    )


else:
  import sys

  __A :  List[Any]    							=				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



