
"""simple docstring"""

from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_			    =  {
    '''configuration_realm''': ['''REALM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RealmConfig'''],
    '''tokenization_realm''': ['''RealmTokenizer'''],
}

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

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

   SCREAMING_SNAKE_CASE_			    =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





"""simple docstring"""

import doctest

import projectq
from projectq.ops import H, Measure




def 			lowercase__  (    lowerCAmelCase :    projectq.cengines._main.MainEngine       )       ->					int:






    """simple docstring"""




    UpperCAmelCase  	=    quantum_engine.allocate_qubit()
    H | qubit
    Measure | qubit
    return int(lowerCAmelCase       )


if __name__ == "__main__":
   doctest.testmod()

   # initialises a new quantum backend
   SCREAMING_SNAKE_CASE_			    =  projectq.MainEngine()

   # Generate a list of 10 random numbers
   SCREAMING_SNAKE_CASE_			    =  [get_random_number(quantum_engine) for _ in range(10)]

   # Flushes the quantum engine from memory
   quantum_engine.flush()

   print('''Random numbers''', random_numbers_list)



