Stable Diffusion Model Configuration Options

The example python based backend /backend/diffusion/model.py supports the following configuration parameters to customize the model being served.

Full Configuration Examples

• Stable Diffusion v1.5

• Stable Diffusion XL

Batch Size and Dynamic Batching

You can select the batch size and dynamic batching queue delay. With batch size 1 dynamic batching is disabled.

[!Note] Changing the batch size requires rebuilding the TensorRT Engines

max_batch_size: 1

dynamic_batching {
 max_queue_delay_microseconds: 100000
}

Engine Building Parameters

The following configuration parameters affect the engine build.

Please see the TensorRT demo for more information.

{
  key: "onnx_opset"
  value: {
    string_value: "18"
  }
},
{
  key: "image_height"
  value: {
    string_value: "512"
  }
},
{
  key: "image_width"
  value: {
    string_value: "512"
  }
},
{
  key: "version"
  value: {
    string_value: "1.5"
  }
}

Forcing Engine Build

Setting the following parameter to a non empty value will force an engine rebuild.

{
  key: "force_engine_build"
  value: {
    string_value: ""
  }
}

Runtime Settings

The following configuration parameters affect the runtime behavior of the model. Please see the TensorRT demo for more information.

Setting a non null integer value for seed will result in deterministic results.

{
  key: "steps"
  value: {
    string_value: "50"
  }
},
{
  key: "scheduler"
  value: {
    string_value: ""
  }
},
{
  key: "guidance_scale"
  value: {
    string_value: "7.5"
  }
},
{
  key: "seed"
  value: {
    string_value: ""
  }
}