/// <summary>
/// Initializes the Brain with the Model that it will use when selecting actions for
/// the agents
/// </summary>
/// <param name="model"> The Barracuda model to load </param>
/// <param name="brainParameters"> The parameters of the Brain used to generate the
/// placeholder tensors </param>
/// <param name="inferenceDevice"> Inference execution device. CPU is the fastest
/// option for most of ML Agents models. </param>
/// <param name="seed"> The seed that will be used to initialize the RandomNormal
/// and Multinomial objects used when running inference.</param>
/// <exception cref="UnityAgentsException">Throws an error when the model is null
/// </exception>
public ModelRunner(
NNModel model,
BrainParameters brainParameters,
InferenceDevice inferenceDevice = InferenceDevice.CPU,
int seed = 0)
{
Model barracudaModel;
m_Model = model;
m_InferenceDevice = inferenceDevice;
m_TensorAllocator = new TensorCachingAllocator();
if (model != null)
{
#if BARRACUDA_VERBOSE
m_Verbose = true;
#endif
D.logEnabled = m_Verbose;
//barracudaModel = ModelLoader.Load(model.Value);
barracudaModel = ModelLoader.Load(model);
var executionDevice = inferenceDevice == InferenceDevice.GPU
// ? BarracudaWorkerFactory.Type.ComputePrecompiled
// : BarracudaWorkerFactory.Type.CSharp;
// m_Engine = BarracudaWorkerFactory.CreateWorker(executionDevice, barracudaModel, m_Verbose);
? WorkerFactory.Type.ComputePrecompiled
: WorkerFactory.Type.CSharp;
m_Engine = WorkerFactory.CreateWorker(executionDevice, barracudaModel, m_Verbose);
}
else
{
barracudaModel = null;
m_Engine = null;
}
m_InferenceInputs = BarracudaModelParamLoader.GetInputTensors(barracudaModel);
m_OutputNames = BarracudaModelParamLoader.GetOutputNames(barracudaModel);
m_TensorGenerator = new TensorGenerator(
seed, m_TensorAllocator, m_Memories, barracudaModel);
m_TensorApplier = new TensorApplier(
brainParameters, seed, m_TensorAllocator, m_Memories, barracudaModel);
}
public bool HasModel(NNModel other, InferenceDevice otherInferenceDevice)
{
return(m_Model == other && m_InferenceDevice == otherInferenceDevice);
}
