public void Test()
{
//var test = Enumerable.Range(0, 10 * 3 * 4 * 5).Select(s => (float)s).ToArray();
//SingleNArray testsingle = new SingleNArray(new mxnet.numerics.nbase.Shape(10, 3, 4, 5), test);
//var test5_result = testsingle["::-1", "1:13"]["5:1:-1", "::-1", ":10"];
//var t1 = test5_result.Flat().data;
//var t2 = testsingle.Argmax(0);
Random rnd = new Random(0);
var test = Enumerable.Range(0, 10 * 3 * 4 * 5).Select(s => (float)rnd.Next(0, 50)).ToArray();
string testshape = "(10,3,4,5)";
SingleNArray testsingle = new SingleNArray(new mxnet.numerics.nbase.Shape(10, 3, 4, 5), test);
var test1_result = testsingle[new int[] { 1, 3, 5, 7 }, new int[] { 0, 2, 0, 2 }];
var a = new SingleNArray(new Shape(2, 2), new float[] { 1, 2, 3, 4 });
var b = new SingleNArray(new Shape(1, 2), new float[] { 5, 6 });
var test2_result = SingleNArray.Concatenate(0, a, b);
}
public void TestArithmetic()
{
Random rnd = new Random(0);
var test = Enumerable.Range(0, 10 * 3 * 4 * 5).Select(s => (float)rnd.Next(0, 50)).ToArray();
string testshape = "(10,3,4,5)";
SingleNArray testsingle = new SingleNArray(new Shape(10, 3, 4, 5), test);
var test1NpResult = eval_scalar <float>("arr[1::1,1:3].sum()", new Parameter <float>("arr", testshape, test));
var test1Result = testsingle["1::1", "1:3"].Sum();
Assert.AreEqual(test1NpResult, test1Result, "1");
var test2NpResult = eval_array <float>("arr.argmax(axis=0)", new Parameter <float>("arr", testshape, test));
var test2Result = testsingle.Argmax(0);
CollectionAssert.AreEqual(test2NpResult, test2Result.Flat().Data, "1");
var a = new float[] { 1, 2, 3, 4 };
var b = new float[] { 5, 6 };
var aarry = new SingleNArray(new Shape(2, 2), a);
var barry = new SingleNArray(new Shape(1, 2), b);
var test3NpResult = eval_array <float>("np.concatenate((a,b),0)",
new Parameter <float>("a", "(2,2)", a),
new Parameter <float>("b", "(1,2)", b));
var test3Result = SingleNArray.Concatenate(0, aarry, barry);
CollectionAssert.AreEqual(test3NpResult, test3Result.Flat().Data, "2");
//var test4_np_result = eval_array<float>("np.concatenate((a,b),axis = 1)",
//new Parameter<float>("a", "(2,2)", a),
//new Parameter<float>("b", "(1,2)", b));
//var test4_result = SingleNArray.Concatenate(1, aarry, barry);
//CollectionAssert.AreEqual(test4_np_result, test4_result.Flat().data, "2");
}
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);
}