
from typing import TYPE_CHECKING

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


__snake_case    :    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:
					__snake_case    :    Dict         =     [
					    """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

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













from typing import TYPE_CHECKING

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


__snake_case    :    Dict         =     {"""configuration_speech_encoder_decoder""": ["""SpeechEncoderDecoderConfig"""]}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__snake_case    :    Union[str, Any]         =     ["""SpeechEncoderDecoderModel"""]

try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__snake_case    :    str         =     ["""FlaxSpeechEncoderDecoderModel"""]

if TYPE_CHECKING:
					from .configuration_speech_encoder_decoder import SpeechEncoderDecoderConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_speech_encoder_decoder import SpeechEncoderDecoderModel

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_speech_encoder_decoder import FlaxSpeechEncoderDecoderModel

else:
					import sys

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





