code: def cuda_pointwise_context(loop_levels, block_count, block_size):
      if loop_levels:
          old_loop_levels = (
              torch._C._jit_get_te_cuda_pointwise_loop_levels()
          )
          torch._C._jit_set_te_cuda_pointwise_loop_levels(loop_levels)
      if block_count:
          old_block_count = (
              torch._C._jit_get_te_cuda_pointwise_block_count()
          )
          torch._C._jit_set_te_cuda_pointwise_block_count(block_count)
      if block_size:
          old_block_size = (
              torch._C._jit_get_te_cuda_pointwise_block_size()
          )
          torch._C._jit_set_te_cuda_pointwise_block_size(block_size)
  
      try:
          yield
      finally:
          if loop_levels:
              torch._C._jit_set_te_cuda_pointwise_loop_levels(
                  old_loop_levels
              )
          if block_count:
              torch._C._jit_set_te_cuda_pointwise_block_count(
                  old_block_count
              )
          if block_size:
              torch._C._jit_set_te_cuda_pointwise_block_size(
                  old_block_size
              )
  
imports: import contextlib
  import json
  import os
  import time
  import numpy
  import torch
  from .None import tensor_engine
label_desc: Use image node_id 1 for calling a global function with example usage: cuda_pointwise_context(loop_levels, block_count, block_size) without return types