code: def wandb_process(
      x: TensorImage,
      y: TensorCategory | TensorMultiCategory,
      samples,
      outs,
      preds,
  ):
      table = wandb.Table(
          columns=["Input image", "Ground_Truth", "Predictions"]
      )
      for (image, label), pred_label in zip(samples, outs):
          table.add_data(
              wandb.Image(image.permute(1, 2, 0)),
              label,
              _unlist(pred_label),
          )
      return {"Prediction_Samples": table}
  
imports: from __future__ import annotations
  from ..basics import *
  from .progress import *
  from ..text.data import TensorText
  from ..tabular.all import TabularDataLoaders, Tabular
  from .hook import total_params
  from .tracker import SaveModelCallback
  import wandb
label_desc: Use image node_id 10 for calling a global function with example usage: wandb_process(x, y, samples, outs, preds) and returns: dict