code: def _svd_flip(u, v, u_based_decision=True):
      """
      Sign correction to ensure deterministic output from SVD.
      Adjusts the columns of u and the rows of v such that the loadings in the
      columns in u that are largest in absolute value are always positive.
  
      Parameters
      ----------
  
      u : cupy.ndarray
          u and v are the output of `cupy.linalg.svd`
      v : cupy.ndarray
          u and v are the output of `cupy.linalg.svd`
      u_based_decision : boolean, (default=True)
          If True, use the columns of u as the basis for sign flipping.
          Otherwise, use the rows of v. The choice of which variable to base the
          decision on is generally algorithm dependent.
  
      Returns
      -------
      u_adjusted, v_adjusted : arrays with the same dimensions as the input.
  
      """
      if u_based_decision:
          # columns of u, rows of v
          max_abs_cols = cp.argmax(cp.abs(u), axis=0)
          signs = cp.sign(u[max_abs_cols, list(range(u.shape[1]))])
          u *= signs
          v *= signs[:, cp.newaxis]
      else:
          # rows of v, columns of u
          max_abs_rows = cp.argmax(cp.abs(v), axis=1)
          signs = cp.sign(v[list(range(v.shape[0])), max_abs_rows])
          u *= signs
          v *= signs[:, cp.newaxis]
      return u, v
  
imports: from cuml.decomposition import PCA
  from cuml.internals.array import CumlArray
  import cuml.internals
  from cuml.internals.input_utils import input_to_cupy_array
  from cuml.common import input_to_cuml_array
  from cuml import Base
  from cuml.internals.safe_imports import cpu_only_import
  import numbers
  from cuml.internals.safe_imports import gpu_only_import
label_desc: Use image node_id 5 for calling a global function with example usage: _svd_flip(u, v, u_based_decision) and returns: u,  v