content: # Schedule'parameter
  "Interpreter::backend" = "PipelineV3" 
  batching_timeout = 6 #默认的凑batch的超时时间
  instance_num = 3 
  precision = "fp16" 
  
  [jpg_decoder]
  backend = "SyncTensor[ Sequential[DecodeTensor,ResizeTensor,cvtColorTensor]  ]" # 需要处理背景线程cuda流同步问题可用SyncTensor， 否则可用Sequential；SyncTensor确保初始化和前向在同一个线程时，能准确处理多个backend的同步时机
  resize_h = 224 
  resize_w = 224 
  
  color = "rgb"
  next = "jump"
  
  [jump]
  backend = "PipelineReviser"
  filter = "SerialSkip"
  next = "cpu_decoder"
  
  [cpu_decoder]
  backend = "SyncTensor[ Sequential[DecodeMat,ResizeMat,CvtColorMat,Mat2Tensor,SyncTensor]  ]" # 需要处理背景线程cuda流同步问题可用SyncTensor， 否则可用Sequential；SyncTensor确保初始化和前向在同一个线程时，能准确处理多个backend的同步时机
  filter = "or" 
  resize_h = 224 
  resize_w = 224 
  
  color = "rgb"
  next = "resnet18"
  
  [resnet18]
  backend = "SyncTensor[TensorrtTensor]" # 需要处理背景线程cuda流同步问题可用SyncTensor， SyncTensor确保初始化和前向在同一个线程时，能准确处理cuda流同步时机;注意DynamicTensorrtTensor本身也可以正确处理。
  
  max = "4x3x224x224"
  min = "1x3x224x224"
  # or max='4'
  model = "../../test/assets/resnet18.onnx" # or resnet18_merge_mean_std_by_onnx.onnx
  
  mean = "123.675, 116.28, 103.53" # 255*"0.485, 0.456, 0.406"
  std = "58.395, 57.120, 57.375" # 255*"0.229, 0.224, 0.225"
  
  instance_num = 2 
  "model::cache" = "./resnet18.trt" # or ./resnet18.trt.encrypted
  