code: def install_xla(upgrade: bool = False):
      """
      Helper function to install appropriate xla wheels based on the `torch` version in Google Colaboratory.
  
      Args:
          upgrade (`bool`, *optional*, defaults to `False`):
              Whether to upgrade `torch` and install the latest `torch_xla` wheels.
  
      Example:
  
      ```python
      >>> from accelerate.utils import install_xla
  
      >>> install_xla(upgrade=True)
      ```
      """
      in_colab = False
      if "IPython" in sys.modules:
          in_colab = "google.colab" in str(
              sys.modules["IPython"].get_ipython()
          )
  
      if in_colab:
          if upgrade:
              torch_install_cmd = ["pip", "install", "-U", "torch"]
              subprocess.run(torch_install_cmd, check=True)
          # get the current version of torch
          torch_version = importlib.metadata.version("torch")
          torch_version_trunc = torch_version[
              : torch_version.rindex(".")
          ]
          xla_wheel = f"https://storage.googleapis.com/tpu-pytorch/wheels/colab/torch_xla-{torch_version_trunc}-cp37-cp37m-linux_x86_64.whl"
          xla_install_cmd = ["pip", "install", xla_wheel]
          subprocess.run(xla_install_cmd, check=True)
      else:
          raise RuntimeError(
              "`install_xla` utility works only on google colab."
          )
  
imports: import importlib.metadata
  import subprocess
  import sys
label_desc: Use image node_id 1 for calling a global function with example usage: install_xla(upgrade) without return types