public void LoadDataBatch(IDataBatch dataBatch)
{
ExecutorManager.LoadData(dataBatch, this._dataArrays);
ExecutorManager._load_label(dataBatch, this._labelArrays);
}
public List <SingleNArray> Predict(IDataIter inputX, int?numBatch = null, bool returnData = false, bool reset = true)
{
if (reset)
{
inputX.Reset();
}
var dataShapes = inputX.ProvideData;
var dataNames = dataShapes.Select(s => s.Key).ToList();
InitPredictor(dataShapes);
var batchSize = inputX.BatchSize;
var dataArrays = dataNames.Select(name => this._predExec.ArgDict[name]).ToList();
var outputList = this._predExec.Outputs.Select(s => new List <SingleNArray>()).ToList();
List <List <SingleNArray> > dataList = null;
List <List <SingleNArray> > labelList = null;
if (returnData)
{
dataList = inputX.ProvideData.Select(s => new List <SingleNArray>()).ToList();
labelList = inputX.ProvideLabel.Select(s => new List <SingleNArray>()).ToList();
}
int i = 0;
foreach (var batch in inputX)
{
ExecutorManager.LoadData(batch, dataArrays);
this._predExec.Forward(isTrain: false);
var padded = batch.Pad;
var realSize = batchSize - padded;
foreach (var vitem in outputList.Zip(this._predExec.Outputs, Tuple.Create))
{
vitem.Item1.Add(vitem.Item2.Slice(0, (uint)realSize).AsNumerics());
}
if (returnData)
{
for (int j = 0; j < batch.Data.Count; j++)
{
var x = batch.Data[j];
dataList[j].Add(x.Slice(0, (uint)realSize).AsNumerics());
}
for (int j = 0; j < batch.Data.Count; j++)
{
var x = batch.Label[j];
labelList[j].Add(x.Slice(0, (uint)realSize).AsNumerics());
}
}
i += 1;
if (numBatch != null && i == numBatch.Value)
{
break;
}
}
var outputs = outputList.Select(s => SingleNArray.Concatenate(0, s.ToArray())).ToList();
if (returnData)
{
var data = dataList.Select(s => SingleNArray.Concatenate(0, s.ToArray()));
var label = labelList.Select(s => SingleNArray.Concatenate(0, s.ToArray()));
}
return(outputs);
}
