code: def decode_batch(self, batch):
      for row in batch.to_pandas().to_dict("records"):
          for column_name, shape_column in self.reshape_columns:
              row[column_name] = row[column_name].reshape(
                  row.pop(shape_column)
              )
  
          for name, value in row.items():
              if type(value) == np.ndarray and value.dtype == object:
                  row[name] = np.stack(value)
  
          yield row
  
imports: from dataclasses import dataclass
  from typing import List, Tuple
  import numpy
label_desc: Use image node_id 3 for calling the ArrowDecoder obj's underlying member method code with example usage: obj.decode_batch(batch) without return types