code: def in_batch_negative_softmax_loss(config, predictions):
      """doc"""
      logits = predictions["logits"]
      labels = paddle.unsqueeze(
          paddle.arange(0, paddle.shape(logits)[0], dtype="int64"),
          axis=1,
      )
      loss = paddle.nn.functional.softmax_with_cross_entropy(
          logits, labels
      )
      loss = paddle.mean(loss)
      return loss
  
file_path: PGL/apps/PGLBox/src/models/loss.py
imports: import os
  import sys
  import math
  import time
  import numpy
  import pickle
  import paddle
  import paddle.static
  import paddle.fluid
  import pgl
  from pgl.utils.logger import log
label_desc: Use image node_id 6 for calling a global function with example usage: in_batch_negative_softmax_loss(config, predictions) and returns: loss