code: def to_np_list(l: Sized) -> List[np.ndarray]:
      if l is not None and len(l):
          tt = tensor_type(l[0])
          if tt == TensorType.Numeric:
              return [np.array(i) for i in l]
          if tt == TensorType.TF:
              return [i.numpy() for i in l]
          if tt == TensorType.Torch:
              return [i.data.cpu().numpy() for i in l]
          if tt == TensorType.Numpy:
              return [i for i in l]
          raise ValueError(
              "Cannot convert tensor list to scaler list \
  because list element are of unsupported type "
              + tt
          )
      else:
          return None if l is None else []
  
file_path: tensorwatch/tensorwatch/tensor_utils.py
imports: from typing import Sized, Any, List
  import numbers
  import numpy
label_desc: Use image node_id 6 for calling a global function with example usage: to_np_list(l) and returns: unknown, unknown, unknown, unknown, unknown