code: def call(self, targets, logits, sample_weights=None):
      # Compute the training-time loss value and add it
      # to the layer using `self.add_loss()`.
      loss = self.loss_fn(targets, logits, sample_weights)
      self.add_loss(loss)
  
      # Return the inference-time prediction tensor (for `.predict()`).
      return ops.softmax(logits)
  
imports: import torch
  import tensorflow
  import os
  import numpy
  import keras
  from keras import layers
  from keras import ops
label_desc: Use image node_id 2 for calling the LogisticEndpoint obj's underlying member method code with example usage: obj.call(targets, logits, sample_weights) and returns: ops