

"""simple docstring"""





from typing import TYPE_CHECKING

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


_a							=							{
    'configuration_roc_bert': ['ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoCBertConfig'],
    'tokenization_roc_bert': ['RoCBertTokenizer'],
}

try:
   if not is_tokenizers_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   pass

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _a							=							[
       'ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'RoCBertForCausalLM',
       'RoCBertForMaskedLM',
       'RoCBertForMultipleChoice',
       'RoCBertForPreTraining',
       'RoCBertForQuestionAnswering',
       'RoCBertForSequenceClassification',
       'RoCBertForTokenClassification',
       'RoCBertLayer',
       'RoCBertModel',
       'RoCBertPreTrainedModel',
       'load_tf_weights_in_roc_bert',
   ]

if TYPE_CHECKING:
   from .configuration_roc_bert import ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RoCBertConfig
   from .tokenization_roc_bert import RoCBertTokenizer

   try:
      if not is_tokenizers_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      raise OptionalDependencyNotAvailable()

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_roc_bert import (
          ROC_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
          RoCBertForCausalLM,
          RoCBertForMaskedLM,
          RoCBertForMultipleChoice,
          RoCBertForPreTraining,
          RoCBertForQuestionAnswering,
          RoCBertForSequenceClassification,
          RoCBertForTokenClassification,
          RoCBertLayer,
          RoCBertModel,
          RoCBertPreTrainedModel,
          load_tf_weights_in_roc_bert,
      )


else:
   import sys

   _a							=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)







"""simple docstring"""





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


_a							=							logging.get_logger(__name__)

_a							=							{
    'MIT/ast-finetuned-audioset-10-10-0.4593': (
        'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json'
    ),
}




class  _lowerCAmelCase  (     lowercase       ):







 """simple docstring"""







 __UpperCAmelCase     : Any       		=     "audio-spectrogram-transformer"


 def __init__(      self							:      Optional[Any], UpperCAmelCase__							:      Dict=7_6_8, UpperCAmelCase__							:      Optional[Any]=1_2, UpperCAmelCase__							:      Optional[int]=1_2, UpperCAmelCase__							:      List[str]=3_0_7_2, UpperCAmelCase__							:      List[str]="gelu", UpperCAmelCase__							:      Dict=0.0, UpperCAmelCase__							:      str=0.0, UpperCAmelCase__							:      Any=0.02, UpperCAmelCase__							:      Any=1E-12, UpperCAmelCase__							:      Dict=1_6, UpperCAmelCase__							:      Optional[int]=True, UpperCAmelCase__							:      Union[str, Any]=1_0, UpperCAmelCase__							:      List[Any]=1_0, UpperCAmelCase__							:      Optional[int]=1_0_2_4, UpperCAmelCase__							:      List[str]=1_2_8, **UpperCAmelCase__							:      List[Any], ):
    super().__init__(**UpperCAmelCase__     )

    __lowercase								=						hidden_size
    __lowercase								=						num_hidden_layers
    __lowercase								=						num_attention_heads
    __lowercase								=						intermediate_size
    __lowercase								=						hidden_act
    __lowercase								=						hidden_dropout_prob
    __lowercase								=						attention_probs_dropout_prob
    __lowercase								=						initializer_range
    __lowercase								=						layer_norm_eps
    __lowercase								=						patch_size
    __lowercase								=						qkv_bias
    __lowercase								=						frequency_stride
    __lowercase								=						time_stride
    __lowercase								=						max_length
    __lowercase								=						num_mel_bins




