



"""simple docstring"""







from typing import TYPE_CHECKING

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


lowercase__		:    Union[str, Any]				   =     {
    """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:
     lowercase__		:    Union[str, Any]				   =     [
         """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

     lowercase__		:    Tuple				   =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)










"""simple docstring"""







import os

from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home


lowercase__		:    int				   =     HUGGINGFACE_HUB_CACHE


lowercase__		:    Tuple				   =     """config.json"""
lowercase__		:    Union[str, Any]				   =     """diffusion_pytorch_model.bin"""
lowercase__		:    List[Any]				   =     """diffusion_flax_model.msgpack"""
lowercase__		:    List[str]				   =     """model.onnx"""
lowercase__		:    List[Any]				   =     """diffusion_pytorch_model.safetensors"""
lowercase__		:    Dict				   =     """weights.pb"""
lowercase__		:    List[Any]				   =     """https://huggingface.co"""
lowercase__		:    List[Any]				   =     default_cache_path
lowercase__		:    Tuple				   =     """diffusers_modules"""
lowercase__		:    Tuple				   =     os.getenv("""HF_MODULES_CACHE""", os.path.join(hf_cache_home, """modules"""))
lowercase__		:    List[str]				   =     ["""fp16""", """non-ema"""]
lowercase__		:    Optional[Any]				   =     """.self_attn"""





