# optional, If name is specified it must match the name of the model repository directory containing the model.
name: "runtime"
backend: "fastdeploy"
max_batch_size: 16

# Input configuration of the model
input [
  {
    # input name
    name: "inputs"
    # input type such as TYPE_FP32、TYPE_UINT8、TYPE_INT8、TYPE_INT16、TYPE_INT32、TYPE_INT64、TYPE_FP16、TYPE_STRING
    data_type: TYPE_FP32
    # input shape， The batch dimension is omitted and the actual shape is [batch, c, h, w]
    dims: [ 3, 224, 224 ]
  }
]

# The output of the model is configured in the same format as the input
output [
  {
    name: "save_infer_model/scale_0.tmp_1"
    data_type: TYPE_FP32
    dims: [ 1000 ]
  }
]

# Number of instances of the model
instance_group [
  {
    # The number of instances is 1
    count: 1
    # Use GPU, CPU inference option is:KIND_CPU
    kind: KIND_GPU
    # The instance is deployed on the 0th GPU card
    gpus: [0]
  }
]

optimization {
  execution_accelerators {
  gpu_execution_accelerator : [ {
    # use TRT engine
    name: "tensorrt",
    # use fp16 on TRT engine
    parameters { key: "precision" value: "trt_fp16" }
  },
  {
    name: "min_shape"
    parameters { key: "inputs" value: "1 3 224 224" }
  },
  {
    name: "opt_shape"
    parameters { key: "inputs" value: "1 3 224 224" }
  },
  {
    name: "max_shape"
    parameters { key: "inputs" value: "16 3 224 224" }
  }
  ]
}}