

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_flax_available,
    is_tensorflow_text_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase__	   = {
    """configuration_bert""": ["""BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BertConfig""", """BertOnnxConfig"""],
    """tokenization_bert""": ["""BasicTokenizer""", """BertTokenizer""", """WordpieceTokenizer"""],
}

try:
	if not is_tokenizers_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase__	   = ["""BertTokenizerFast"""]

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase__	   = [
	    """BERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """BertForMaskedLM""",
	    """BertForMultipleChoice""",
	    """BertForNextSentencePrediction""",
	    """BertForPreTraining""",
	    """BertForQuestionAnswering""",
	    """BertForSequenceClassification""",
	    """BertForTokenClassification""",
	    """BertLayer""",
	    """BertLMHeadModel""",
	    """BertModel""",
	    """BertPreTrainedModel""",
	    """load_tf_weights_in_bert""",
	]

try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase__	   = [
	    """TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TFBertEmbeddings""",
	    """TFBertForMaskedLM""",
	    """TFBertForMultipleChoice""",
	    """TFBertForNextSentencePrediction""",
	    """TFBertForPreTraining""",
	    """TFBertForQuestionAnswering""",
	    """TFBertForSequenceClassification""",
	    """TFBertForTokenClassification""",
	    """TFBertLMHeadModel""",
	    """TFBertMainLayer""",
	    """TFBertModel""",
	    """TFBertPreTrainedModel""",
	]
try:
	if not is_tensorflow_text_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase__	   = ["""TFBertTokenizer"""]

try:
	if not is_flax_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	lowerCAmelCase__	   = [
	    """FlaxBertForCausalLM""",
	    """FlaxBertForMaskedLM""",
	    """FlaxBertForMultipleChoice""",
	    """FlaxBertForNextSentencePrediction""",
	    """FlaxBertForPreTraining""",
	    """FlaxBertForQuestionAnswering""",
	    """FlaxBertForSequenceClassification""",
	    """FlaxBertForTokenClassification""",
	    """FlaxBertModel""",
	    """FlaxBertPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_bert import BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, BertConfig, BertOnnxConfig
	from .tokenization_bert import BasicTokenizer, BertTokenizer, WordpieceTokenizer

	try:
		if not is_tokenizers_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_bert_fast import BertTokenizerFast

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_bert import (
		    BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    BertForMaskedLM,
		    BertForMultipleChoice,
		    BertForNextSentencePrediction,
		    BertForPreTraining,
		    BertForQuestionAnswering,
		    BertForSequenceClassification,
		    BertForTokenClassification,
		    BertLayer,
		    BertLMHeadModel,
		    BertModel,
		    BertPreTrainedModel,
		    load_tf_weights_in_bert,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_bert import (
		    TF_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFBertEmbeddings,
		    TFBertForMaskedLM,
		    TFBertForMultipleChoice,
		    TFBertForNextSentencePrediction,
		    TFBertForPreTraining,
		    TFBertForQuestionAnswering,
		    TFBertForSequenceClassification,
		    TFBertForTokenClassification,
		    TFBertLMHeadModel,
		    TFBertMainLayer,
		    TFBertModel,
		    TFBertPreTrainedModel,
		)

	try:
		if not is_tensorflow_text_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .tokenization_bert_tf import TFBertTokenizer

	try:
		if not is_flax_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_flax_bert import (
		    FlaxBertForCausalLM,
		    FlaxBertForMaskedLM,
		    FlaxBertForMultipleChoice,
		    FlaxBertForNextSentencePrediction,
		    FlaxBertForPreTraining,
		    FlaxBertForQuestionAnswering,
		    FlaxBertForSequenceClassification,
		    FlaxBertForTokenClassification,
		    FlaxBertModel,
		    FlaxBertPreTrainedModel,
		)

else:
	import sys

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




from ..utils import is_flax_available, is_torch_available


if is_torch_available():
	from .autoencoder_kl import AutoencoderKL
	from .controlnet import ControlNetModel
	from .dual_transformer_ad import DualTransformeraDModel
	from .modeling_utils import ModelMixin
	from .prior_transformer import PriorTransformer
	from .ta_film_transformer import TaFilmDecoder
	from .transformer_ad import TransformeraDModel
	from .unet_ad import UNetaDModel
	from .unet_ad import UNetaDModel
	from .unet_ad_condition import UNetaDConditionModel
	from .unet_ad_condition import UNetaDConditionModel
	from .vq_model import VQModel

if is_flax_available():
	from .controlnet_flax import FlaxControlNetModel
	from .unet_ad_condition_flax import FlaxUNetaDConditionModel
	from .vae_flax import FlaxAutoencoderKL

