code: def ts_zeros(sz, d=1):
      """Returns a time series made of zero values.
  
      Parameters
      ----------
      sz : int
          Time series size.
      d : int (optional, default: 1)
          Time series dimensionality.
  
      Returns
      -------
      numpy.ndarray
          A time series made of zeros.
  
      Examples
      --------
      >>> ts_zeros(3, 2)  # doctest: +NORMALIZE_WHITESPACE
      array([[0., 0.],
             [0., 0.],
             [0., 0.]])
      >>> ts_zeros(5).shape
      (5, 1)
      """
      return numpy.zeros((sz, d))
  
imports: import warnings
  from io import StringIO
  import numpy
  from sklearn.base import TransformerMixin
  from sklearn.utils import column_or_1d
  from sklearn.utils.validation import check_is_fitted
  from tslearn.backend import instantiate_backend
  from tslearn.bases import TimeSeriesBaseEstimator
label_desc: Use image node_id 10 for calling a global function with example usage: ts_zeros(sz, d) and returns: numpy