code: def _save_model(model: torch.nn.Module, path: str):
      if path.endswith(".pt"):
          torch.save(model, path)
      else:
          torch.save(
              model.state_dict(), Path(path) / "pruned_state_dict.pt"
          )
  
imports: import json
  import logging
  import os.path
  from pathlib import Path
  from tempfile import TemporaryDirectory
  from typing import Tuple, List, Any, Dict
  import torch
  from sparseml.onnx.optim import ModelAnalyzer, pruning_loss_sens_magnitude
  from sparseml.pytorch.optim import ScheduledModifierManager
  from sparseml.pytorch.sparsification import EpochRangeModifier, GMPruningModifier
  from sparseml.pytorch.utils import ModuleExporter
  from sparsify.blueprints.utils import default_epochs_distribution, PruningModelEvaluator, default_pruning_settings
  from sparsify.schemas import ProjectModelAnalysisSchema
  from torch.nn import CrossEntropyLoss, MSELoss
  from torch.optim import SGD
  from tqdm.auto import tqdm
label_desc: Use image node_id 6 for calling a global function with example usage: _save_model(model, path) without return types