public NamedOnnxValue GetNamedOnnxValue()
{
_srcgetter(ref _vBuffer);
_vBuffer.CopyToDense(ref _vBufferDense);
return(OnnxUtils.CreateNamedOnnxValue(_colName, _vBufferDense.GetValues(), _tensorShape));
}
public Mapper(OnnxTransformer parent, Schema inputSchema) :
base(Contracts.CheckRef(parent, nameof(parent)).Host.Register(nameof(Mapper)), inputSchema)
{
_parent = parent;
_inputColIndices = new int[_parent.Inputs.Length];
_isInputVector = new bool[_parent.Inputs.Length];
_inputTensorShapes = new OnnxShape[_parent.Inputs.Length];
_inputOnnxTypes = new System.Type[_parent.Inputs.Length];
var model = _parent.Model;
for (int i = 0; i < _parent.Inputs.Length; i++)
{
var idx = model.InputNames.IndexOf(_parent.Inputs[i]);
if (idx < 0)
{
throw Host.Except($"Column {_parent.Inputs[i]} doesn't match input node names of model");
}
var inputNodeInfo = model.ModelInfo.InputsInfo[idx];
var shape = inputNodeInfo.Shape;
var inputType = OnnxUtils.OnnxToMlNetType(inputNodeInfo.Type);
var inputShape = AdjustDimensions(inputNodeInfo.Shape);
_inputTensorShapes[i] = inputShape.ToList();
_inputOnnxTypes[i] = inputNodeInfo.Type;
var col = inputSchema.GetColumnOrNull(_parent.Inputs[i]);
if (!col.HasValue)
{
throw Host.ExceptSchemaMismatch(nameof(inputSchema), "input", _parent.Inputs[i]);
}
_inputColIndices[i] = col.Value.Index;
var type = inputSchema[_inputColIndices[i]].Type;
var vectorType = type as VectorType;
_isInputVector[i] = vectorType != null;
if (vectorType != null && vectorType.Size == 0)
{
throw Host.Except($"Variable length input columns not supported");
}
if (type.GetItemType() != inputType)
{
throw Host.ExceptSchemaMismatch(nameof(inputSchema), "input", _parent.Inputs[i], inputType.ToString(), type.ToString());
}
// If the column is one dimension we make sure that the total size of the Onnx shape matches.
// Compute the total size of the known dimensions of the shape.
int valCount = inputShape.Select(x => (int)x).Where(x => x > 0).Aggregate((x, y) => x * y);
// The column length should be divisible by this, so that the other dimensions can be integral.
int typeValueCount = type.GetValueCount();
if (typeValueCount % valCount != 0)
{
throw Contracts.Except($"Input shape mismatch: Input '{_parent.Inputs[i]}' has shape {String.Join(",", inputShape)}, but input data is of length {typeValueCount}.");
}
//Host.Assert(_outputItemRawType == _outputColType.ItemType.RawType);
}
}
public NamedOnnxValue GetNamedOnnxValue()
{
var scalar = default(T);
_srcgetter(ref scalar);
return OnnxUtils.CreateScalarNamedOnnxValue(_colName, scalar);
}
public Tensor GetTensor()
{
_srcgetter(ref _vBuffer);
_vBuffer.CopyToDense(ref _vBufferDense);
return(OnnxUtils.CreateTensor(_vBufferDense.Values, _tensorShape));
}
private static INamedOnnxValueGetter CreateNamedOnnxValueGetter(Row input, System.Type onnxType, bool isVector, string colName, int colIndex, OnnxShape onnxShape)
{
var type = OnnxUtils.OnnxToMlNetType(onnxType).RawType;
Contracts.AssertValue(type);
return Utils.MarshalInvoke(CreateNameOnnxValueGetter<int>, type, input, isVector, colName, colIndex, onnxShape);
}