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); }