code: def delegate_load_from_path(
      jiant_model: primary.JiantModel, weights_path: str, load_mode: str
  ):
      """Load weights dict from file and load weights according to specified loading mode.
  
      Args:
          jiant_model (JiantModel): jiant model (encoder and task models are core components).
          weights_path (str): filepath to weights object saved with torch.save().
          load_mode (str): TODO
  
      Returns:
          TODO: return behavior is not consistent between load_mode options, clarify as needed here.
  
      """
      weights_dict = torch.load(weights_path)
      return delegate_load(
          jiant_model=jiant_model,
          weights_dict=weights_dict,
          load_mode=load_mode,
      )
  
imports: from dataclasses import dataclass
  from typing import Any
  from typing import Dict
  from typing import List
  import torch
  import torch.nn
  import transformers
  import warnings
  import jiant.proj.main.components.container_setup
  import jiant.proj.main.modeling.primary
  import jiant.utils.python.strings
  from jiant.proj.main.modeling.heads import JiantHeadFactory
  from jiant.proj.main.modeling.taskmodels import JiantTaskModelFactory, Taskmodel, MLMModel
  from jiant.shared.model_resolution import ModelArchitectures
  from jiant.tasks.core import Task
label_desc: Use image node_id 2 for calling a global function with example usage: delegate_load_from_path(jiant_model, weights_path, load_mode) and returns: delegate_load