






from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE   =  {
    "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:
    _SCREAMING_SNAKE_CASE   =  [
        "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

    _SCREAMING_SNAKE_CASE   =  _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





'''simple docstring'''





from typing import TYPE_CHECKING

from ...utils import _LazyModule


UpperCamelCase_    						=       {"""tokenization_byt5""": ["""ByT5Tokenizer"""]}


if TYPE_CHECKING:
							from .tokenization_byta import ByTaTokenizer
else:
							import sys

							UpperCamelCase_    						=       _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





