


'''simple docstring'''



from __future__ import annotations

__UpperCAmelCase      :List[str]			    =       [-1_0, -5, 0, 5, 5.1, 1_1, 1_3, 2_1, 3, 4, -2_1, -1_0, -5, -1, 0]
__UpperCAmelCase      :int			    =       [-5, 0, 5, 5.1, 1_1, 1_3, 2_1, -1, 4, -1, -1_0, -5, -1, 0, -1]




def      _a     (						_lowercase :     list[float]  ):





     '''simple docstring'''






     __UpperCAmelCase     :			str  							=      []
     __UpperCAmelCase     :			int  							=      len(_lowercase  )

     for i in range(_lowercase  ):
          __UpperCAmelCase     :			float  							=      -1
          for j in range(i + 1      , _lowercase  ):
               if arr[i] < arr[j]:
                    __UpperCAmelCase     :			str  							=      arr[j]
                    break
          result.append(_lowercase  )
     return result




def      _a     (						_lowercase :     list[float]  ):





     '''simple docstring'''






     __UpperCAmelCase     :			Tuple  							=      []
     for i, outer in enumerate(_lowercase  ):
          __UpperCAmelCase     :			float  							=      -1
          for inner in arr[i + 1 :]:
               if outer < inner:
                    __UpperCAmelCase     :			List[Any]  							=      inner
                    break
          result.append(_lowercase  )
     return result




def      _a     (						_lowercase :     list[float]  ):





     '''simple docstring'''






     __UpperCAmelCase     :			Dict  							=      len(_lowercase  )
     __UpperCAmelCase     :			list[float]  							=      []
     __UpperCAmelCase     :			list[float]  							=      [-1] * arr_size

     for index in reversed(range(_lowercase  )  ):
          if stack:
               while stack[-1] <= arr[index]:
                    stack.pop()
                    if not stack:
                         break
          if stack:
               __UpperCAmelCase     :			Optional[int]  							=      stack[-1]
          stack.append(arr[index]  )
     return result


if __name__ == "__main__":
      from doctest import testmod
      from timeit import timeit

      testmod()
      print(next_greatest_element_slow(arr))
      print(next_greatest_element_fast(arr))
      print(next_greatest_element(arr))

      __UpperCAmelCase      :int			    =       (
          "from __main__ import arr, next_greatest_element_slow, "
          "next_greatest_element_fast, next_greatest_element"
      )
      print(
          "next_greatest_element_slow():",
          timeit("next_greatest_element_slow(arr)", setup=setup),
      )
      print(
          "next_greatest_element_fast():",
          timeit("next_greatest_element_fast(arr)", setup=setup),
      )
      print(
          "     next_greatest_element():",
          timeit("next_greatest_element(arr)", setup=setup),
      )



'''simple docstring'''



from typing import TYPE_CHECKING

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


__UpperCAmelCase      :Union[str, Any]			    =       {
    "configuration_rag": ["RagConfig"],
    "retrieval_rag": ["RagRetriever"],
    "tokenization_rag": ["RagTokenizer"],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase      :Dict			    =       [
          "RagModel",
          "RagPreTrainedModel",
          "RagSequenceForGeneration",
          "RagTokenForGeneration",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase      :Dict			    =       [
          "TFRagModel",
          "TFRagPreTrainedModel",
          "TFRagSequenceForGeneration",
          "TFRagTokenForGeneration",
      ]


if TYPE_CHECKING:
      from .configuration_rag import RagConfig
      from .retrieval_rag import RagRetriever
      from .tokenization_rag import RagTokenizer

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_rag import (
                TFRagModel,
                TFRagPreTrainedModel,
                TFRagSequenceForGeneration,
                TFRagTokenForGeneration,
            )

else:
      import sys

      __UpperCAmelCase      :Any			    =       _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)