code: def vecdot(a, b, axis=None):
      r"""
      Return the dot product of two vectors.
      Note that `vecdot` handles multidimensional arrays differently than `dot`:
      it does *not* perform a matrix product, but flattens input arguments
      to 1-D vectors first. Consequently, it should only be used for vectors.
  
      Notes
      ----------
      `vecdot` is a alias for `vdot`. It is a standard API in
      https://data-apis.org/array-api/latest/API_specification/linear_algebra_functions.html#vecdot-x1-x2-axis-1
      instead of an official NumPy operator.
  
      Parameters
      ----------
      a : ndarray
          First argument to the dot product.
      b : ndarray
          Second argument to the dot product.
      axis : axis over which to compute the dot product. Must be an integer on
          the interval [-N, N) , where N is the rank (number of dimensions) of
          the shape determined according to Broadcasting . If specified as a
          negative integer, the function must determine the axis along which
          to compute the dot product by counting backward from the last dimension
          (where -1 refers to the last dimension). If None , the function must
          compute the dot product over the last axis. Default: None .
  
      Returns
      -------
      output : ndarray
          Dot product of `a` and `b`.
  
      See Also
      --------
      dot : Return the dot product without using the complex conjugate of the
          first argument.
  
      Examples
      --------
      Note that higher-dimensional arrays are flattened!
  
      >>> a = np.array([[1, 4], [5, 6]])
      >>> b = np.array([[4, 1], [2, 2]])
      >>> np.linalg.vecdot(a, b)
      array(30.)
      >>> np.linalg.vecdot(b, a)
      array(30.)
      >>> 1*4 + 4*1 + 5*2 + 6*2
      30
      """
      return _mx_nd_np.tensordot(a.flatten(), b.flatten(), axis)
  
imports: from functools import reduce
  from ..ndarray import numpy
  from ..util import wrap_data_api_linalg_func
  from .fallback_linalg import *
  from .None import fallback_linalg
label_desc: Use image node_id 8 for calling a global function with example usage: vecdot(a, b, axis) and returns: _mx_nd_np