docstr: Returns nvcc compute capability compile flags.
  
  1. `TORCH_CUDA_ARCH_LIST` takes priority over `cross_compile_archs`.
  2. If neither is set default compute capabilities will be used
  3. Under `jit_mode` compute capabilities of all visible cards will be used plus PTX
  
  Format:
  
  - `TORCH_CUDA_ARCH_LIST` may use ; or whitespace separators. Examples:
  
  TORCH_CUDA_ARCH_LIST="6.1;7.5;8.6" pip install ...
  TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0 7.5 8.0 8.6+PTX" pip install ...
  
  - `cross_compile_archs` uses ; separator.
docstr_tok: ["Returns","nvcc","compute","capability","compile","flags",".","1",".","`","TORCH_CUDA_ARCH_LIST","`","takes","priority","over","`","cross_compile_archs","`",".","2",".","If","neither","is","set","default","compute","capabilities","will","be","used","3",".","Under","`","jit_mode","`","compute","capabilities","of","all","visible","cards","will","be","used","plus","PTX","Format",":","-","`","TORCH_CUDA_ARCH_LIST","`","may","use",";","or","whitespace","separators",".","Examples",":","TORCH_CUDA_ARCH_LIST=","''","6.1",";","7.5",";","8.6","''","pip","install","...","TORCH_CUDA_ARCH_LIST=","''","6.0","6.1","7.0","7.5","8.0","8.6+PTX","''","pip","install","...","-","`","cross_compile_archs","`","uses",";","separator","."]
code: def compute_capability_args(self, cross_compile_archs=None):
      """
      Returns nvcc compute capability compile flags.
  
      1. `TORCH_CUDA_ARCH_LIST` takes priority over `cross_compile_archs`.
      2. If neither is set default compute capabilities will be used
      3. Under `jit_mode` compute capabilities of all visible cards will be used plus PTX
  
      Format:
  
      - `TORCH_CUDA_ARCH_LIST` may use ; or whitespace separators. Examples:
  
      TORCH_CUDA_ARCH_LIST="6.1;7.5;8.6" pip install ...
      TORCH_CUDA_ARCH_LIST="6.0 6.1 7.0 7.5 8.0 8.6+PTX" pip install ...
  
      - `cross_compile_archs` uses ; separator.
  
      """
      ccs = []
      if self.jit_mode:
          # Compile for underlying architectures since we know those at runtime
          for i in range(torch.cuda.device_count()):
              CC_MAJOR, CC_MINOR = torch.cuda.get_device_capability(i)
              cc = f"{CC_MAJOR}.{CC_MINOR}"
              if cc not in ccs:
                  ccs.append(cc)
          ccs = sorted(ccs)
          ccs[-1] += "+PTX"
      else:
          # Cross-compile mode, compile for various architectures
          # env override takes priority
          cross_compile_archs_env = os.environ.get(
              "TORCH_CUDA_ARCH_LIST", None
          )
          if cross_compile_archs_env is not None:
              if cross_compile_archs is not None:
                  print(
                      f"{WARNING} env var `TORCH_CUDA_ARCH_LIST={cross_compile_archs_env}` overrides `cross_compile_archs={cross_compile_archs}`"
                  )
              cross_compile_archs = cross_compile_archs_env.replace(
                  " ", ";"
              )
          else:
              if cross_compile_archs is None:
                  cross_compile_archs = (
                      get_default_compute_capabilities()
                  )
          ccs = cross_compile_archs.split(";")
  
      ccs = self.filter_ccs(ccs)
      if len(ccs) == 0:
          raise RuntimeError(
              f"Unable to load {self.name} op due to no compute capabilities remaining after filtering"
          )
  
      args = []
      self.enable_bf16 = True
      for cc in ccs:
          num = cc[0] + cc[2]
          args.append(f"-gencode=arch=compute_{num},code=sm_{num}")
          if cc.endswith("+PTX"):
              args.append(
                  f"-gencode=arch=compute_{num},code=compute_{num}"
              )
  
          if int(cc[0]) <= 7:
              self.enable_bf16 = False
  
      return args
  
imports: import os
  import sys
  import time
  import importlib
  from pathlib import Path
  import subprocess
  import shlex
  import shutil
  import tempfile
  import distutils.ccompiler
  import distutils.log
  import distutils.sysconfig
  from distutils.errors import CompileError, LinkError
  from abc import ABC, abstractmethod
  from typing import List
label_desc: Use image node_id 1 for calling the CUDAOpBuilder obj's underlying member method code with example usage: obj.compute_capability_args(cross_compile_archs) and returns: args