code: def sparsify_tensor(tensor, card):
      """Zeros out all elements in the `tensor` except `card` elements with maximum absolute values.
  
      Parameters
      ----------
      tensor : ndarray
      card : int
          Desired number of non-zero elements in the `tensor`
  
      Returns
      -------
      ndarray of shape tensor.shape
      """
      if card >= np.prod(tensor.shape):
          return tensor
      bound = tl.sort(tl.abs(tensor), axis=None)[-card]
  
      return tl.where(
          tl.abs(tensor) < bound,
          tl.zeros(tensor.shape, **tl.context(tensor)),
          tensor,
      )
  
imports: import numpy
  import warnings
  import tensorly
  from ._base_decomposition import DecompositionMixin
  from ..random import random_cp
  from ..base import unfold
  from ..cp_tensor import cp_to_tensor, CPTensor, cp_norm, cp_normalize, validate_cp_rank
  from ..tenalg.svd import svd_interface
  from ..tenalg import unfolding_dot_khatri_rao
label_desc: Use image node_id 2 for calling a global function with example usage: sparsify_tensor(tensor, card) and returns: tl, tensor