content: batching_timeout = 10 #默认的凑batch的超时时间
  instance_num = 5 
  precision = "fp16" 
  #### main graph ####
  [jpg_decoder]
  backend = "Sequential[DecodeMat,(result2other)CvtColorMat,ResizePadMat,Mat2Tensor,SyncTensor]"
  color = "bgr"
  instance_num = 16
  max_h = 416
  max_w = 416
  
  next = "detect"
  
  [detect]
  backend = "S[TensorrtTensor,SyncTensor]" 
  batching_timeout = 5 #默认的凑batch的超时时间
  instance_num = 4 
  max = "8" 
  model = "../../../examples/yolox/yolox_tiny.onnx" 
  "model::cache" = "./yolox_tiny.trt" 
  net_h = 416 
  net_w = 416 
  # postprocessor = "BatchingPostProcYolox_45_30" 
  "model::timingcache" = "./yolox_tiny.timingcache"
  
  next = "post_det"
  [post_det]
  backend = "SyncTensor[PostProcYolox]" 
  instance_num = 8 
  net_h = 416 
  net_w = 416 # for PostProcYolox
  next = "sub_graph" 
  
  [sub_graph]
  map = "jpg_decoder[other:data,color:color],post_det[TASK_BOX_KEY:TASK_BOX_KEY]"
  
  backend = "MapReduce"
  jump = "cls_preprocess"
  
  merge = "score_1,score_2,result,cls_1_result"
  split = "TASK_BOX_KEY"
  
  instance_num = 8
  next = "final"
  
  [final]
  
  #### sub graph ####
  [cls_preprocess]
  backend = "Sequential[CropMat,ResizeMat,CvtColorMat,Mat2Tensor,SyncTensor]"
  color = "rgb"
  instance_num = 12
  resize_h = 224
  resize_w = 224
  # save_dir="./"
  
  next = "cls_1,cls_2"
  
  #### branch 1 ####
  # SoftmaxArgMaxTensor
  [cls_1]
  backend = "S[TensorrtTensor,SyncTensor]" 
  max = 8 
  mean = "123.675, 116.28, 103.53" # 255*"0.485, 0.456, 0.406"
  model = "./resnet18.onnx" 
  "model::cache" = "./resnet18.trt" 
  "model::timingcache" = "resnet18.timingcache" 
  std = "58.395, 57.120, 57.375" # 255*"0.229, 0.224, 0.225"
  
  instance_num = 4
  postprocessor = "SoftmaxArgMax"
  
  next = "post_cls_1"
  
  [post_cls_1]
  filter = "filter_score"
  
  backend = "S[TensorrtTensor,SyncTensor]" 
  max = 8 
  mean = "123.675, 116.28, 103.53" # 255*"0.485, 0.456, 0.406"
  model = "././resnet50.onnx" 
  "model::cache" = "./resnet50.trt" 
  "model::timingcache" = "resnet50.timingcache" 
  std = "58.395, 57.120, 57.375" # 255*"0.229, 0.224, 0.225"
  
  instance_num = 4
  postprocessor = "SoftmaxArgMax"
  
  next = "subgraph_final"
  
  #### branch 2 ####
  
  [cls_2]
  
  backend = "S[TensorrtTensor,SyncTensor]" 
  max = "8" 
  mean = "123.675, 116.28, 103.53" # 255*"0.485, 0.456, 0.406"
  model = "././fastervit_0_224_224.onnx" 
  "model::cache" = "./fastervit_0_224_224.trt" 
  "model::timingcache" = "fastervit_0_224_224.timingcache" 
  std = "58.395, 57.120, 57.375" # 255*"0.229, 0.224, 0.225"
  
  batching_timeout = 10
  instance_num = 6
  postprocessor = "SoftmaxArgMax"
  
  next = "subgraph_final"
  
  [subgraph_final]
  map = "post_cls_1[score:score_1,result:cls_1_result],cls_2[score:score_2,result:data]"
  