code: def _torch_to_opengl(torch_tensor, cuda_context, cuda_buffer):
      # CUDA access to the OpenGL buffer is only allowed within a map-unmap block.
      cuda_context.push()
      mapping_obj = cuda_buffer.map()
  
      # data_ptr points to the OpenGL shader storage buffer memory.
      data_ptr, sz = mapping_obj.device_ptr_and_size()
  
      # Copy the torch tensor to the OpenGL buffer directly on device.
      cuda_copy = cuda.Memcpy2D()
      cuda_copy.set_src_device(torch_tensor.data_ptr())
      cuda_copy.set_dst_device(data_ptr)
      cuda_copy.width_in_bytes = (
          cuda_copy.src_pitch
      ) = cuda_copy.dst_ptch = (torch_tensor.shape[1] * 4)
      cuda_copy.height = torch_tensor.shape[0]
      cuda_copy(False)
  
      # Unmap and pop the cuda context to make sure OpenGL won't interfere with
      # PyTorch ops down the line.
      mapping_obj.unmap()
      cuda_context.pop()
  
imports: import contextlib
  import ctypes
  import os
  import threading
  from typing import Any, Dict
  import OpenGL.EGL
  import pycuda.driver
  from OpenGL._opaque import opaque_pointer_cls
  from OpenGL.raw.EGL._errors import EGLError
label_desc: Use image node_id 6 for calling a global function with example usage: _torch_to_opengl(torch_tensor, cuda_context, cuda_buffer) without return types