code: def strides_from(shape, dtype, order="C"):
      """Return strides as for continuous array shape `shape` and given `dtype`
  
      Parameters
      ----------
      shape : sequence
          shape of array to calculate strides from
      dtype : dtype-like
          dtype specifier for array
      order : {'C', 'F'}, optional
          whether array is C or FORTRAN ordered
  
      Returns
      -------
      strides : tuple
          sequence length ``len(shape)`` giving strides for continuous array with
          given `shape`, `dtype` and `order`
  
      Examples
      --------
      >>> strides_from((2,3,4), 'i4')
      (48, 16, 4)
      >>> strides_from((3,2), np.float64)
      (16, 8)
      >>> strides_from((5,4,3), np.bool_, order='F')
      (1, 5, 20)
      """
      dt = np.dtype(dtype)
      if dt.itemsize == 0:
          raise ValueError(f'Empty dtype "{dt}"')
      if order == "F":
          strides = np.cumprod([dt.itemsize] + list(shape[:-1]))
      elif order == "C":
          strides = np.cumprod([dt.itemsize] + list(shape)[::-1][:-1])
          strides = strides[::-1]
      else:
          raise ValueError(f'Unexpected order "{order}"')
      return tuple(strides)
  
label_desc: Use image node_id 1 for calling a global function with example usage: strides_from(shape, dtype, order) and returns: tuple