public object eval(Tensor tensor)
{
log(new { tensor });
CNTKTensor _tensor = In(tensor);
Variable variable = _tensor.function;
var inputs = new Dictionary <Variable, Value>();
var outputs = new Dictionary <Variable, Value>()
{
{ variable, null }
};
_tensor.function.Evaluate(inputs, outputs, DeviceDescriptor.CPUDevice);
Value value = outputs[variable];
var shape = value.Shape;
IEnumerable <IEnumerable <double> > r =
value.GetDenseData <double>(_tensor.function);
if (value.DataType == CNTKDataType.Double)
{
return(Out <double>(variable, value, shape));
}
if (value.DataType == CNTKDataType.Float)
{
return(Out <float>(variable, value, shape));
}
throw new InvalidOperationException();
}
public Tensor bias_add(Tensor output, Tensor bias)
{
CNTKTensor _x = In(output);
CNTKTensor _b = In(bias);
var _shape = In(_x.CNTK_Shape).Select(x => x < 0 ? 1 : x).ToArray();
var shape = NDShape.CreateNDShape(_shape);
var b = C.Reshape(_b, shape);
return(Out(new Variable(_x.function) + b));
}
public Tensor bias_add(Tensor output, Tensor bias, DataFormatType?data_format = null, string name = null)
{
if (data_format != null)
{
throw new NotImplementedException();
}
using (this.name_scope("bias_add"))
{
CNTKTensor _x = In(output);
CNTKTensor _b = In(bias);
var _shape = In(_x.CNTK_Shape).Select(x => x < 0 ? 1 : x).ToArray();
var shape = NDShape.CreateNDShape(_shape);
var b = C.Reshape(_b, shape);
return(Out(new Variable(_x.function) + b));
}
}