code: def squared_norm(x):
      """Squared Euclidean or Frobenius norm of x.
  
      Faster than norm(x) ** 2.
  
      Parameters
      ----------
      x : array-like
          The input array which could be either be a vector or a 2 dimensional array.
  
      Returns
      -------
      float
          The Euclidean norm when x is a vector, the Frobenius norm when x
          is a matrix (2-d array).
      """
      x = np.ravel(x, order="K")
      if np.issubdtype(x.dtype, np.integer):
          warnings.warn(
              (
                  "Array type is integer, np.dot may overflow. "
                  "Data should be float type to avoid this issue"
              ),
              UserWarning,
          )
      return np.dot(x, x)
  
imports: import warnings
  import numpy
  from scipy import linalg, sparse
  from .None import check_random_state
  from ._array_api import _is_numpy_namespace, get_namespace
  from ._logistic_sigmoid import _log_logistic_sigmoid
  from .sparsefuncs_fast import csr_row_norms
  from .validation import check_array
label_desc: Use image node_id 1 for calling a global function with example usage: squared_norm(x) and returns: np