/// <summary>
/// Invokes the model with the given input data.
/// </summary>
/// <param name="inTensorsData">The input data to be inferred.</param>
/// <returns>TensorsData instance which contains the inferred result.</returns>
/// <feature>http://tizen.org/feature/machine_learning.inference</feature>
/// <exception cref="ArgumentException">Thrown when the method failed due to an invalid parameter.</exception>
/// <exception cref="TimeoutException">Thrown when failed to get the result from sink element.</exception>
/// <exception cref="NotSupportedException">Thrown when the feature is not supported.</exception>
/// <since_tizen> 6 </since_tizen>
public TensorsData Invoke(TensorsData inTensorsData)
{
TensorsData out_data = null;
IntPtr outDataPtr = IntPtr.Zero;
NNStreamerError ret = NNStreamerError.None;
NNStreamer.CheckNNStreamerSupport();
if (inTensorsData == null)
{
string msg = "TensorsData is null";
throw NNStreamerExceptionFactory.CreateException(NNStreamerError.InvalidParameter, msg);
}
if (_dynamicMode)
{
TensorsInfo inInfo = inTensorsData.TensorsInfo;
if (inInfo == null)
{
throw NNStreamerExceptionFactory.CreateException(NNStreamerError.InvalidParameter, "TensorsInfo is null");
}
/* Apply all data */
inTensorsData.PrepareInvoke();
IntPtr outInfoPtr = IntPtr.Zero;
ret = Interop.SingleShot.InvokeSingleDynamic(_handle, inTensorsData.GetHandle(), inInfo.GetTensorsInfoHandle(), out outDataPtr, out outInfoPtr);
NNStreamer.CheckException(ret, "fail to invoke the single dynamic inference");
out_data = TensorsData.CreateFromNativeHandle(outDataPtr, outInfoPtr, true);
}
else
{
TensorsInfo data_inInfo = inTensorsData.TensorsInfo;
if (!data_inInfo.Equals(_inInfo))
{
string msg = "The TensorsInfo of Input TensorsData is different from that of SingleShot object";
throw NNStreamerExceptionFactory.CreateException(NNStreamerError.InvalidParameter, msg);
}
/* Apply all data */
inTensorsData.PrepareInvoke();
ret = Interop.SingleShot.InvokeSingle(_handle, inTensorsData.GetHandle(), out outDataPtr);
NNStreamer.CheckException(ret, "fail to invoke the single inference");
out_data = TensorsData.CreateFromNativeHandle(outDataPtr, data_inInfo.GetTensorsInfoHandle(), true);
}
return(out_data);
}
/// <summary>
/// Inputs tensor data to source node.
/// </summary>
/// <param name="data">The tensors data</param>
/// <feature>http://tizen.org/feature/machine_learning.inference</feature>
/// <exception cref="NotSupportedException">Thrown when the feature is not supported.</exception>
/// <exception cref="ArgumentException">Thrown when the method failed due to an invalid parameter.</exception>
/// <exception cref="InvalidOperationException">Thrown when the node is invalid, or failed to input tensors data.</exception>
/// <since_tizen> 8 </since_tizen>
public void Input(TensorsData data)
{
if (data == null)
{
throw NNStreamerExceptionFactory.CreateException(NNStreamerError.InvalidParameter, "Given data is invalid");
}
if (!Valid)
{
NNStreamer.CheckException(NNStreamerError.InvalidOperation, "Current node is invalid: " + Name);
}
data.PrepareInvoke();
NNStreamerError ret = Interop.Pipeline.InputSrcData(Handle, data.GetHandle(), PipelineBufferPolicy.NotFreed);
NNStreamer.CheckException(ret, "Failed to input tensors data to source node: " + Name);
}
