code: def track_gradients_dists(model, run):
      from aim import Distribution
  
      grad_hist = get_model_layers(model, "grad")
  
      for name, params in grad_hist.items():
          if "weight" in params:
              run.track(
                  Distribution(params["weight"]),
                  name=name,
                  context={
                      "type": "gradients",
                      "params": "weights",
                  },
              )
          if "bias" in params:
              run.track(
                  Distribution(params["bias"]),
                  name=name,
                  context={
                      "type": "gradients",
                      "params": "biases",
                  },
              )
  
label_desc: Use image node_id 2 for calling a global function with example usage: track_gradients_dists(model, run) without return types