code: def initialize_params_from_file(
      model,
      weights_file,
      num_xpus,
      opts,
      broadcast_computed_param=False,
      reset_epoch=False,
  ):
      start_epoch, lr, best_metric = initialize_master_xpu_model_params(
          model, weights_file, opts, reset_epoch
      )
      broadcast_parameters(
          opts, model, num_xpus, broadcast_computed_param
      )
      return start_epoch, lr, best_metric
  
file_path: pytorch/caffe2/contrib/playground/checkpoint.py
imports: import numpy
  import pickle
  from collections import OrderedDict
  from caffe2.proto import caffe2_pb2
  from caffe2.python import workspace, core, scope
  import logging
label_desc: Use image node_id 1 for calling a global function with example usage: initialize_params_from_file(model, weights_file, num_xpus, opts, broadcast_computed_param, reset_epoch) and returns: start_epoch,  lr,  best_metric