code: def _reshape_with_nan(X, n_samples, lengths, max_length):
      X_fill = np.full((n_samples, max_length), np.nan)
      for i in prange(n_samples):
          X_fill[i, : lengths[i]] = X[i]
      return X_fill
  
imports: import numpy
  from numba import njit, prange
  from numba.typed import List
  from scipy.stats import norm
  from sklearn.base import BaseEstimator
  from sklearn.utils.validation import check_array
  from warnings import warn
  from ..base import UnivariateTransformerMixin
label_desc: Use image node_id 5 for calling a global function with example usage: _reshape_with_nan(X, n_samples, lengths, max_length) and returns: X_fill