code: def config_network_to_int8(network):
      for layer_idx in range(network.num_layers):
          layer = network.get_layer(layer_idx)
          layer.precision = trt.int8
  
imports: import time
  import logging
  import tensorrt
  import numpy
  import torch
  from .None import frontend_to_onnx
  from .None import trt_pycuda
  from .backend import BaseModelSpeedup
label_desc: Use image node_id 8 for calling a global function with example usage: config_network_to_int8(network) without return types