TensorLabel

public class TensorLabel

TensorLabel is an util wrapper for TensorBuffers with meaningful labels on an axis.

For example, an image classification model may have an output tensor with shape as {1, 10}, where 1 is the batch size and 10 is the number of categories. In fact, on the 2nd axis, we could label each sub-tensor with the name or description of each corresponding category. TensorLabel could help converting the plain Tensor in TensorBuffer into a map from predefined labels to sub-tensors. In this case, if provided 10 labels for the 2nd axis, TensorLabel could convert the original {1, 10} Tensor to a 10 element map, each value of which is Tensor in shape {} (scalar). Usage example: 

   TensorBuffer outputTensor = ...;
   List<String> labels = FileUtil.loadLabels(context, labelFilePath);
   // labels the first axis with size greater than one
   TensorLabel labeled = new TensorLabel(labels, outputTensor);
   // If each sub-tensor has effectively size 1, we can directly get a float value
   Map<String, Float> probabilities = labeled.getMapWithFloatValue();
   // Or get sub-tensors, when each sub-tensor has elements more than 1
   Map<String, TensorBuffer> subTensors = labeled.getMapWithTensorBuffer();

Note: currently we only support tensor-to-map conversion for the first label with size greater than 1.

See Also

Public Constructors

TensorLabel(Map<Integer, List<String>> axisLabels, TensorBuffer tensorBuffer)
Creates a TensorLabel object which is able to label on the axes of multi-dimensional tensors.
TensorLabel(List<String> axisLabels, TensorBuffer tensorBuffer)
Creates a TensorLabel object which is able to label on one axis of multi-dimensional tensors.

Public Methods

List<Category>
getCategoryList()
Gets a list of Category from the TensorLabel object.
Map<String, Float>
getMapWithFloatValue()
Gets a map that maps label to float.
Map<String, TensorBuffer>
getMapWithTensorBuffer()
Gets the map with a pair of the label and the corresponding TensorBuffer.

Inherited Methods