



from typing import TYPE_CHECKING

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


A__			   = {
    "configuration_realm": ["REALM_PRETRAINED_CONFIG_ARCHIVE_MAP", "RealmConfig"],
    "tokenization_realm": ["RealmTokenizer"],
}

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

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 A__			   = [
     "REALM_PRETRAINED_MODEL_ARCHIVE_LIST",
     "RealmEmbedder",
     "RealmForOpenQA",
     "RealmKnowledgeAugEncoder",
     "RealmPreTrainedModel",
     "RealmReader",
     "RealmScorer",
     "load_tf_weights_in_realm",
 ]
 A__			   = ["RealmRetriever"]


if TYPE_CHECKING:
 from .configuration_realm import REALM_PRETRAINED_CONFIG_ARCHIVE_MAP, RealmConfig
 from .tokenization_realm import RealmTokenizer

 try:
  if not is_tokenizers_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .tokenization_realm import RealmTokenizerFast

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_realm import (
      REALM_PRETRAINED_MODEL_ARCHIVE_LIST,
      RealmEmbedder,
      RealmForOpenQA,
      RealmKnowledgeAugEncoder,
      RealmPreTrainedModel,
      RealmReader,
      RealmScorer,
      load_tf_weights_in_realm,
  )
  from .retrieval_realm import RealmRetriever


else:
 import sys

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








from typing import TYPE_CHECKING

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


A__			   = {"""configuration_hubert""": ["""HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """HubertConfig"""]}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A__			   = [
	    """HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """HubertForCTC""",
	    """HubertForSequenceClassification""",
	    """HubertModel""",
	    """HubertPreTrainedModel""",
	]


try:
	if not is_tf_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A__			   = [
	    """TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """TFHubertForCTC""",
	    """TFHubertModel""",
	    """TFHubertPreTrainedModel""",
	]

if TYPE_CHECKING:
	from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_hubert import (
		    HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    HubertForCTC,
		    HubertForSequenceClassification,
		    HubertModel,
		    HubertPreTrainedModel,
		)

	try:
		if not is_tf_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_tf_hubert import (
		    TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
		    TFHubertForCTC,
		    TFHubertModel,
		    TFHubertPreTrainedModel,
		)


else:
	import sys

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



