






from typing import TYPE_CHECKING

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


a		:	Optional[Any]      					=			{
    "configuration_realm": ["REALM_PRETRAINED_CONFIG_ARCHIVE_MAP", "RealmConfig"],
    "tokenization_realm": ["RealmTokenizer"],
}

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

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a		:	Tuple      					=			[
          "REALM_PRETRAINED_MODEL_ARCHIVE_LIST",
          "RealmEmbedder",
          "RealmForOpenQA",
          "RealmKnowledgeAugEncoder",
          "RealmPreTrainedModel",
          "RealmReader",
          "RealmScorer",
          "load_tf_weights_in_realm",
      ]
      a		:	Any      					=			["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		:	Tuple      					=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)










def     lowerCamelCase__				(   __lowerCamelCase      :					list  ,		__lowerCamelCase      :					int		):
  for index, item in enumerate(__lowerCamelCase		):
    if item == target:
      return index
  return -1






def     lowerCamelCase__				(   __lowerCamelCase      :					list  ,		__lowerCamelCase      :					int  ,		__lowerCamelCase      :					int  ,		__lowerCamelCase      :					int		):
  if not (0 <= high < len(__lowerCamelCase		) and 0 <= low < len(__lowerCamelCase		)):
    raise Exception("""Invalid upper or lower bound!"""		)
  if high < low:
    return -1
  if sequence[low] == target:
    return low
  if sequence[high] == target:
    return high
  return rec_linear_search(__lowerCamelCase  ,		low + 1  ,		high - 1  ,		__lowerCamelCase		)


if __name__ == "__main__":
       a		:	List[str]      					=			input("Enter numbers separated by comma:\n").strip()
       a		:	Tuple      					=			[int(item.strip()) for item in user_input.split(",")]

       a		:	List[str]      					=			int(input("Enter a single number to be found in the list:\n").strip())
       a		:	Optional[Any]      					=			linear_search(sequence, target)
       if result != -1:
              print(f"""linear_search({sequence}, {target}) = {result}""")
       else:
              print(f"""{target} was not found in {sequence}""")


