EuclideanLossLayer.md

CEuclideanLossLayer Class

• CEuclideanLossLayer Class
  • Settings
  • Trainable parameters
  • Inputs
  • Outputs
    • Getting the value of the loss function

This class implements a layer that calculates a loss function equal to the Euclidean distance between the classes from the network response and the objects belonging to the correct classes.

Settings

The layer has no settings.

Trainable parameters

The layer has no trainable parameters.

Inputs

The layer may have 2 to 3 inputs:

1. The network output for which you are calculating the loss function. It contains BatchLength * BatchWidth * ListSize objects, each of Height * Width * Depth * Channels size.
2. A blob of the same size as the first input, containing the correct class objects. The loss function will calculate the Euclidean distance between the first and the second input.
3. [Optional] The objects' weights. This blob should have the same dimensions as the first input.

Outputs

This layer has no output.

Getting the value of the loss function

float GetLastLoss() const;

Use this method to get the value of the loss function calculated on the network's last run.