code: def optimizer_func(lr):
      return F.optimizer.AdamOptimizer(learning_rate=lr)
  
imports: import math
  import torch
  import paddle
  import pgl
  import numpy
  import paddle.fluid
  import paddle.fluid.layers
  import copy
  from pgl.contrib.ogb.nodeproppred.dataset_pgl import PglNodePropPredDataset
  from ogb.nodeproppred import Evaluator
  from utils import to_undirected, add_self_loop, linear_warmup_decay
  from model import Products_label_embedding_model
  from dataloader.ogb_products_dataloader import SampleDataGenerator
  import paddle.fluid.profiler
  from pgl.utils import paddle_helper
  import argparse
  from tqdm import tqdm
label_desc: Use image node_id 2 for calling a global function with example usage: optimizer_func(lr) and returns: F