code: def squared_norm(x):
      """Squared Euclidean or Frobenius norm of x.
  
      Returns the Euclidean norm when x is a vector, the Frobenius norm when x
      is a matrix (2-d array). Faster than norm(x) ** 2.
      """
      x = _ravel(x)
      return np.dot(x, x)
  
imports: from __future__ import division
  from functools import partial
  import warnings
  import numpy
  from scipy import linalg
  from scipy.sparse import issparse, csr_matrix
  from .None import check_random_state
  from .fixes import np_version
  from ._logistic_sigmoid import _log_logistic_sigmoid
  from ..externals.six.moves import xrange
  from .sparsefuncs_fast import csr_row_norms
  from .validation import check_array
  from ..exceptions import NonBLASDotWarning
label_desc: Use image node_id 2 for calling a global function with example usage: squared_norm(x) and returns: np