public void ComputesCompatibleTensorDimsWithInvalidData()
{
var dims = TensorDimensions.GetBackwardCompatibleDims(0, 0);
Assert.Equal(1, dims.Rank);
Assert.Equal(0, dims[0]);
}
public void ComputesCompatibleTensorDims()
{
var dims = TensorDimensions.GetBackwardCompatibleDims(10, 2);
Assert.Equal(2, dims[0]);
Assert.Equal(5, dims[1]);
}
public void ComputesCompatibleTensorDimsWithWrongColumnHint()
{
var dims = TensorDimensions.GetBackwardCompatibleDims(10, 3);
Assert.Equal(1, dims.Rank);
Assert.Equal(10, dims[0]);
}
public override void UpdateMemoryBlocks()
{
Output.Count = OutputSize;
//Output.ColumnHint = ColumnHint;
Output.Dims = TensorDimensions.GetBackwardCompatibleDims(Output.Count, ColumnHint);
RandomPool.Count = PatternCount * OutputSize;
//RandomPool.ColumnHint = ColumnHint;
RandomPool.Dims = TensorDimensions.GetBackwardCompatibleDims(RandomPool.Count, ColumnHint);
Label.Count = PatternCount / PatternGroups;
//Label.ColumnHint = Label.Count;
Label.Dims = TensorDimensions.GetBackwardCompatibleDims(Label.Count, Label.Count);
}
public override void UpdateMemoryBlocks()
{
if (ConvertToBinary)
{
if (m_userInput == null || m_userInput.Length != 1)
{
m_userInput = new float[1];
}
}
else
{
if (m_userInput == null || m_userInput.Length != OutputSize)
{
m_userInput = new float[OutputSize];
}
}
//Output.ColumnHint = ColumnHint;
Output.Dims = TensorDimensions.GetBackwardCompatibleDims(Output.Count, ColumnHint);
}