
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__)








'''simple docstring'''



def 	_A						(							lowercase__		):
						return " ".join(sorted(set(sentence.split()		)		)		)


if __name__ == "__main__":
				import doctest

				doctest.testmod()






