public static float train_epoch_quickprop_parallel(SWIGTYPE_p_fann ann, SWIGTYPE_p_fann_train_data data, uint threadnumb)
{
float ret = fannfloatPINVOKE.train_epoch_quickprop_parallel__SWIG_0(SWIGTYPE_p_fann.getCPtr(ann), SWIGTYPE_p_fann_train_data.getCPtr(data), threadnumb);
return ret;
}
public static float train_epoch_quickprop_parallel(SWIGTYPE_p_fann ann, SWIGTYPE_p_fann_train_data data, uint threadnumb, floatVectorVector predicted_outputs)
{
float ret = fannfloatPINVOKE.train_epoch_quickprop_parallel__SWIG_1(SWIGTYPE_p_fann.getCPtr(ann), SWIGTYPE_p_fann_train_data.getCPtr(data), threadnumb, floatVectorVector.getCPtr(predicted_outputs));
if (fannfloatPINVOKE.SWIGPendingException.Pending) throw fannfloatPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public static float train_epoch_incremental_mod(SWIGTYPE_p_fann ann, SWIGTYPE_p_fann_train_data data, floatVectorVector predicted_outputs)
{
float ret = fannfloatPINVOKE.train_epoch_incremental_mod__SWIG_1(SWIGTYPE_p_fann.getCPtr(ann), SWIGTYPE_p_fann_train_data.getCPtr(data), floatVectorVector.getCPtr(predicted_outputs));
if (fannfloatPINVOKE.SWIGPendingException.Pending) throw fannfloatPINVOKE.SWIGPendingException.Retrieve();
return ret;
}
public static float train_epoch_incremental_mod(SWIGTYPE_p_fann ann, SWIGTYPE_p_fann_train_data data)
{
float ret = fannfloatPINVOKE.train_epoch_incremental_mod__SWIG_0(SWIGTYPE_p_fann.getCPtr(ann), SWIGTYPE_p_fann_train_data.getCPtr(data));
return ret;
}
public static float test_data_parallel(SWIGTYPE_p_fann ann, SWIGTYPE_p_fann_train_data data, uint threadnumb)
{
float ret = fanndoublePINVOKE.test_data_parallel__SWIG_0(SWIGTYPE_p_fann.getCPtr(ann), SWIGTYPE_p_fann_train_data.getCPtr(data), threadnumb);
return ret;
}
public neural_net(SWIGTYPE_p_fann other)
: this(fanndoublePINVOKE.new_neural_net__SWIG_7(SWIGTYPE_p_fann.getCPtr(other)), true)
{
}
public void copy_from_struct_fann(SWIGTYPE_p_fann other)
{
fanndoublePINVOKE.neural_net_copy_from_struct_fann(swigCPtr, SWIGTYPE_p_fann.getCPtr(other));
}
