code: def _eager_loss_fn(outputs, targets, loss_fn, output_name):
      with backend.name_scope(output_name + "_loss"):
          loss = loss_fn(targets, outputs)
      return loss
  
file_path: tensorflow/tensorflow/python/keras/engine/training_eager_v1.py
imports: import numpy
  from tensorflow.python.eager.backprop import GradientTape
  from tensorflow.python.framework import tensor_conversion
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.engine import training_utils
  from tensorflow.python.keras.engine import training_utils_v1
  from tensorflow.python.keras.mixed_precision import loss_scale_optimizer
  from tensorflow.python.keras.utils import losses_utils
  from tensorflow.python.ops import math_ops
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 for calling a global function with example usage: _eager_loss_fn(outputs, targets, loss_fn, output_name) and returns: loss