public bool AddDependency(Applier applier)
{
ThrowIfNotAllocated();
if (!applier.IsAllocated)
{
throw new ArgumentException("The Applier is not allocated.");
}
var r = plaidml.__Internal.PlaidmlAddComposerDependency(this, applier);
if (r)
{
Dependencies.Add(applier);
}
else
{
ReportApiCallError("plaidml_add_composer_dependency");
}
return(r);
}
public Invoker(Context ctx, Function f, DeviceTensor[] input, DeviceTensor[] output) : base(ctx)
{
_ptr = plaidml.__Internal.PlaidmlAllocInvoker(_context, f);
if (_ptr.IsZero())
{
ReportApiCallError("plaidml_alloc_invoker");
return;
}
IsAllocated = true;
var r = false;
for (int i = 0; i < input.Length; i++)
{
r = plaidml.__Internal.PlaidmlSetInvokerInput(this, input[i].Name, input[i]);
if (!r)
{
ReportApiCallError("plaidml_set_invoker_input");
break;
}
}
if (r)
{
InputTensorsSet = true;
InputTensors = input;
}
else
{
InputTensorsSet = false;
return;
}
for (int i = 0; i < output.Length; i++)
{
r = plaidml.__Internal.PlaidmlSetInvokerOutput(this, output[i].Name, output[i]);
if (!r)
{
ReportApiCallError("plaidml_set_invoker_output");
break;
}
}
if (r)
{
OutputTensorsSet = true;
OutputTensor = output[0];
}
else
{
OutputTensorsSet = false;
return;
}
Applier = new Applier(_context, f);
foreach (DeviceTensor t in InputTensors)
{
Applier.AddInputValue(t);
}
OutputValue = Applier.AddOutputValue(OutputTensor.Name);
}
