code: def gimme_params(model):
      """
      Provide number of trainable parameters (i.e. those requiring gradient computation) for input network.
  
      Args:
          model: PyTorch Network
      Returns:
          int, number of parameters.
      """
      model_parameters = filter(
          lambda p: p.requires_grad, model.parameters()
      )
      params = sum([np.prod(p.size()) for p in model_parameters])
      return params
  
imports: import warnings
  import csv
  import datetime
  import os
  import pickle
  import faiss
  import matplotlib.pyplot
  import numpy
  import torch
  from PIL import Image
  from sklearn import metrics
  from torch import nn
  from tqdm import tqdm
  import pdb
label_desc: Use image node_id 2 for calling a global function with example usage: gimme_params(model) and returns: params