code: def get_tflops(model_numel, batch_size, seq_len, step_time):
      return (
          model_numel
          * batch_size
          * seq_len
          * 8
          / 1e12
          / (step_time + 1e-12)
      )
  
imports: import argparse
  import gzip
  from contextlib import nullcontext
  from functools import partial
  from time import time
  import numpy
  import torch
  import torch.nn
  import torch.optim
  import tqdm
  from palm_pytorch import PaLM
  from palm_pytorch.autoregressive_wrapper import AutoregressiveWrapper
  from torch.utils.data import DataLoader, Dataset
  import colossalai
  from colossalai.booster import Booster
  from colossalai.booster.plugin import GeminiPlugin, LowLevelZeroPlugin, TorchDDPPlugin
  from colossalai.lazy import LazyInitContext
  from colossalai.logging import disable_existing_loggers, get_dist_logger
  from colossalai.nn import HybridAdam
  from colossalai.utils import get_current_device
label_desc: Use image node_id 4 for calling a global function with example usage: get_tflops(model_numel, batch_size, seq_len, step_time) and returns: unknown