code: def strided_scalar(shape, scalar=0.0):
      """Return array shape `shape` where all entries point to value `scalar`
  
      Parameters
      ----------
      shape : sequence
          Shape of output array.
      scalar : scalar
          Scalar value with which to fill array.
  
      Returns
      -------
      strided_arr : array
          Array of shape `shape` for which all values == `scalar`, built by
          setting all strides of `strided_arr` to 0, so the scalar is broadcast
          out to the full array `shape`. `strided_arr` is flagged as not
          `writeable`.
  
          The array is set read-only to avoid a numpy error when broadcasting -
          see https://github.com/numpy/numpy/issues/6491
      """
      shape = tuple(shape)
      scalar = np.array(scalar)
      strides = [0] * len(shape)
      strided_scalar = np.lib.stride_tricks.as_strided(
          scalar, shape, strides
      )
      strided_scalar.flags.writeable = False
      return strided_scalar
  
imports: import operator
  from functools import reduce
  from mmap import mmap
  from numbers import Integral
  import numpy
label_desc: Use image node_id 17 for calling a global function with example usage: strided_scalar(shape, scalar) and returns: strided_scalar