code: def row_norms(X, squared=False):
      """Row-wise (squared) Euclidean norm of X.
  
      Performs no input validation.
  
      Parameters
      ----------
      X : array_like
          The input tensor
      squared : bool, optional (default = False)
          If True, return squared norms.
  
      Returns
      -------
      array_like
          The row-wise (squared) Euclidean norm of X.
      """
  
      norms = (X * X).sum(axis=1)
      if not squared:
          norms = mt.sqrt(norms)
      return norms
  
imports: import numpy
  from ...None import tensor
label_desc: Use image node_id 2 for calling a global function with example usage: row_norms(X, squared) and returns: norms