code: def validate_vector(u, dtype=None):
      # replica of scipy.spatial.distance._validate_vector, for making scipy
      # compatible functions on vectors (such as distances computations)
      u = np.asarray(u, dtype=dtype, order="c").squeeze()
      # Ensure values such as u=1 and u=[1] still return 1-D arrays.
      u = np.atleast_1d(u)
      if u.ndim > 1:
          raise ValueError("Input vector should be 1-D.")
      return u
  
imports: import numpy
  from numpy.linalg import LinAlgError
  from sklearn.datasets import make_spd_matrix
  from sklearn.decomposition import PCA
  from sklearn.utils import check_array
  from sklearn.utils.validation import check_X_y, check_random_state
  from .exceptions import PreprocessorError, NonPSDError
  from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
  from scipy.linalg import pinvh, eigh
  import sys
  import time
  import warnings
label_desc: Use image node_id 14 for calling a global function with example usage: validate_vector(u, dtype) and returns: u