

import argparse
import os


UpperCAmelCase__	:       Any			      =      {
    """pytorch""": {
        """1.13""": {
            """torch""": """1.13.1""",
            """torchvision""": """0.14.1""",
            """torchaudio""": """0.13.1""",
            """python""": 3.9,
            """cuda""": """cu116""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1"""
                """ --extra-index-url https://download.pytorch.org/whl/cu116"""
            ),
            """base_image""": """nvidia/cuda:11.6.2-cudnn8-devel-ubuntu20.04""",
        },
        """1.12""": {
            """torch""": """1.12.1""",
            """torchvision""": """0.13.1""",
            """torchaudio""": """0.12.1""",
            """python""": 3.9,
            """cuda""": """cu113""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1"""
                """ --extra-index-url https://download.pytorch.org/whl/cu113"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """1.11""": {
            """torch""": """1.11.0""",
            """torchvision""": """0.12.0""",
            """torchaudio""": """0.11.0""",
            """python""": 3.9,
            """cuda""": """cu113""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.11.0 torchvision==0.12.0 torchaudio==0.11.0"""
                """ --extra-index-url https://download.pytorch.org/whl/cu113"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """1.10""": {
            """torch""": """1.10.2""",
            """torchvision""": """0.11.3""",
            """torchaudio""": """0.10.2""",
            """python""": 3.9,
            """cuda""": """cu113""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.10.2 torchvision==0.11.3 torchaudio==0.10.2"""
                """ --extra-index-url https://download.pytorch.org/whl/cu113"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        # torchaudio < 0.10 has no CUDA-enabled binary distributions
        """1.9""": {
            """torch""": """1.9.1""",
            """torchvision""": """0.10.1""",
            """torchaudio""": """0.9.1""",
            """python""": 3.9,
            """cuda""": """cu111""",
            """install""": (
                """python3 -m pip install --no-cache-dir -U torch==1.9.1 torchvision==0.10.1 torchaudio==0.9.1"""
                """ --extra-index-url https://download.pytorch.org/whl/cu111"""
            ),
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
    },
    """tensorflow""": {
        """2.11""": {
            """tensorflow""": """2.11.1""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.11.1""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.10""": {
            """tensorflow""": """2.10.1""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.10.1""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.9""": {
            """tensorflow""": """2.9.3""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.9.3""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.8""": {
            """tensorflow""": """2.8.2""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.8.2""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.7""": {
            """tensorflow""": """2.7.3""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.7.3""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.6""": {
            """tensorflow""": """2.6.5""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.6.5""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
        """2.5""": {
            """tensorflow""": """2.5.3""",
            """install""": """python3 -m pip install --no-cache-dir -U tensorflow==2.5.3""",
            """base_image""": """nvidia/cuda:11.2.2-cudnn8-devel-ubuntu20.04""",
        },
    },
}


if __name__ == "__main__":
  UpperCAmelCase__	:       List[str]			      =      argparse.ArgumentParser("""Choose the framework and version to install""")
  parser.add_argument(
      """--framework""", help="""The framework to install. Should be `torch` or `tensorflow`""", type=str, required=True
  )
  parser.add_argument("""--version""", help="""The version of the framework to install.""", type=str, required=True)
  UpperCAmelCase__	:       List[Any]			      =      parser.parse_args()

  UpperCAmelCase__	:       Tuple			      =      past_versions_testing[args.framework][args.version]

  os.system(F"""echo \"export INSTALL_CMD=\'{info['install']}\'\" >> ~/.profile""")
  print(F"""echo \"export INSTALL_CMD=\'{info['install']}\'\" >> ~/.profile""")

  UpperCAmelCase__	:       int			      =      """"""
  if args.framework == "pytorch":
    UpperCAmelCase__	:       Optional[Any]			      =      info["""cuda"""]
  os.system(F"""echo \"export CUDA='{cuda}'\" >> ~/.profile""")
  print(F"""echo \"export CUDA='{cuda}'\" >> ~/.profile""")







from __future__ import annotations

UpperCAmelCase__	:       Optional[int]			      =      [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]







class     a__    :







  """simple docstring"""




  def __init__(     self      :	Optional[Any]			,			UpperCAmelCase__      :	int						)   ->None:
        """simple docstring"""







        SCREAMING_SNAKE_CASE	: int					       =				-1
        SCREAMING_SNAKE_CASE	: int					       =				-1
        SCREAMING_SNAKE_CASE	: list[int]					       =				[-1] * length
        SCREAMING_SNAKE_CASE	: Node | None					       =				None
        SCREAMING_SNAKE_CASE	: Node | None					       =				None




  def __repr__(     self      :	Dict						)   ->str:
        """simple docstring"""







        return f"Node(min_value={self.minn} max_value={self.maxx})"






def    __lowercase (       _A     )       ->  Node | None:
      SCREAMING_SNAKE_CASE	: Tuple					       =				Node(len(_A     )     )
      SCREAMING_SNAKE_CASE       ,		SCREAMING_SNAKE_CASE	: int					       =				min(_A     ), max(_A     )
      # Leaf node case where the node contains only one unique value
      if root.minn == root.maxx:
            return root
      SCREAMING_SNAKE_CASE	: int					       =				(root.minn + root.maxx) // 2

      SCREAMING_SNAKE_CASE	: list[int]					       =				[]
      SCREAMING_SNAKE_CASE	: list[int]					       =				[]

      for index, num in enumerate(_A     ):
            if num <= pivot:
                  left_arr.append(_A     )
            else:
                  right_arr.append(_A     )
            SCREAMING_SNAKE_CASE	: int					       =				len(_A     )
      SCREAMING_SNAKE_CASE	: int					       =				build_tree(_A     )
      SCREAMING_SNAKE_CASE	: Tuple					       =				build_tree(_A     )
      return root






def    __lowercase (       _A  ,      _A  ,      _A     )       ->  int:
      if index < 0 or node is None:
            return 0
      # Leaf node cases
      if node.minn == node.maxx:
            return index + 1 if node.minn == num else 0
      SCREAMING_SNAKE_CASE	: List[str]					       =				(node.minn + node.maxx) // 2
      if num <= pivot:
            # go the left subtree and map index to the left subtree
            return rank_till_index(node.left  ,      _A  ,      node.map_left[index] - 1     )
      else:
            # go to the right subtree and map index to the right subtree
            return rank_till_index(node.right  ,      _A  ,      index - node.map_left[index]     )






def    __lowercase (       _A  ,      _A  ,      _A  ,      _A     )       ->  int:
      if start > end:
            return 0
      SCREAMING_SNAKE_CASE	: Any					       =				rank_till_index(_A  ,      _A  ,      _A     )
      SCREAMING_SNAKE_CASE	: Optional[int]					       =				rank_till_index(_A  ,      _A  ,      start - 1     )
      return rank_till_end - rank_before_start






def    __lowercase (       _A  ,      _A  ,      _A  ,      _A     )       ->  int:
      if index > (end - start) or start > end or node is None:
            return -1
      # Leaf node case
      if node.minn == node.maxx:
            return node.minn
      # Number of elements in the left subtree in interval [start, end]
      SCREAMING_SNAKE_CASE	: Tuple					       =				node.map_left[end] - (
          node.map_left[start - 1] if start else 0
      )
      if num_elements_in_left_tree > index:
            return quantile(
                node.left  ,      _A  ,      (node.map_left[start - 1] if start else 0)  ,      node.map_left[end] - 1  ,      )
      else:
            return quantile(
                node.right  ,      index - num_elements_in_left_tree  ,      start - (node.map_left[start - 1] if start else 0)  ,      end - node.map_left[end]  ,      )






def    __lowercase (       _A  ,      _A  ,      _A  ,      _A  ,      _A     )       ->  int:
      if (
          start > end
          or node is None
          or start_num > end_num
          or node.minn > end_num
          or node.maxx < start_num
      ):
            return 0
      if start_num <= node.minn and node.maxx <= end_num:
            return end - start + 1
      SCREAMING_SNAKE_CASE	: Dict					       =				range_counting(
          node.left  ,      (node.map_left[start - 1] if start else 0)  ,      node.map_left[end] - 1  ,      _A  ,      _A  ,      )
      SCREAMING_SNAKE_CASE	: List[str]					       =				range_counting(
          node.right  ,      start - (node.map_left[start - 1] if start else 0)  ,      end - node.map_left[end]  ,      _A  ,      _A  ,      )
      return left + right


if __name__ == "__main__":
  import doctest

  doctest.testmod()




