code: def install_faster_transformer(
      working_dir: str = None,
  ):
      """Helper function for installing FasterTransformer.
      https://github.com/NVIDIA/FasterTransformer
  
      This function needs some prerequisites for running, as a valid `git`
      installation and having MacOS or a Linux-distribution as OS.
  
      Args:
          working_dir (str, optional): The directory where the FasterTransformer
          repo will be cloned and installed. Default: None
      """
      if not gpu_is_available():
          return False
      path = Path(__file__).parent
      # install faster transformer
      try:
          import torch
  
          CP = compute_capability = torch.cuda.get_device_capability()
          assert len(compute_capability) == 2
      except (ImportError, AssertionError):
          return False
      installation_file = str(path / "install_fastertransformer.sh")
      env_dict = {
          "COMPUTE_CAPABILITY": f"{CP[0]}{CP[1]}",
          **dict(os.environ.copy()),
      }
  
      result = subprocess.run(
          ["bash", installation_file],
          cwd=get_faster_transformer_repo_path().parent,
          env=env_dict,
      )
      # check result
      if result.returncode != 0:
          return False
      return True
  
imports: import os
  import platform
  import subprocess
  import sys
  from abc import ABC
  from pathlib import Path
  from typing import List
  import cpuinfo
  from loguru import logger
  from nebullvm.config import LIBRARIES_GPU
  from nebullvm.operations.optimizations.compilers.utils import deepsparse_is_available, get_faster_transformer_repo_path, intel_neural_compressor_is_available, openvino_is_available, tensorrt_is_available, torch_tensorrt_is_available
  from nebullvm.optional_modules.torch import torch
  from nebullvm.tools.utils import check_module_version, gpu_is_available
label_desc: Use image node_id 13 for calling a global function with example usage: install_faster_transformer(working_dir) and returns: True, False, False, False