code: def on_train_batch_end(
      self, trainer, datamodule, outputs, batch, batch_idx
  ):
      input_nodes, output_nodes, mfgs = batch
      self.push(mfgs[0].num_src_nodes())
  
imports: import argparse
  import glob
  import math
  import os
  import time
  import dgl
  import torch
  import torch.nn
  import torch.nn.functional
  from ladies_sampler import LadiesSampler, normalized_edata, PoissonLadiesSampler
  from load_graph import load_dataset
  from model import SAGE
  from pytorch_lightning import LightningDataModule, LightningModule, Trainer
  from pytorch_lightning.callbacks import Callback, EarlyStopping, ModelCheckpoint
  from pytorch_lightning.loggers import TensorBoardLogger
  from torchmetrics.classification import MulticlassF1Score, MultilabelF1Score
label_desc: Use image node_id 7 for calling the BatchSizeCallback obj's underlying member method code with example usage: obj.on_train_batch_end(trainer, datamodule, outputs, batch, batch_idx) without return types