code: def check_longitudinal_features_consistency(X, shape, dtype):
      """Checks if all elements of longitudinal features X have the same shape
       and correct dtype. In case the dtype is not correct, convert X elements
       to the proper dtypes.
  
      Parameters
      ----------
      X : list of np.ndarray or list of scipy.sparse.csr_matrix,
          list of length n_samples, each element of the list of
          shape=(n_intervals, n_features)
          The list of features matrices.
  
      shape : Tuple(`int`, `int`)
          Expected shape of each X element.
  
      dtype : np.dtype object or string
          Expected dtype of each X element.
  
      Returns
      -------
      output : list of np.ndarray or list of scipy.sparse.csr_matrix,
          list of length n_samples, each element of the list of
          shape=(n_intervals, n_features)
          The list of features matrices with corrected shapes and dtypes.
      """
      if not all([x.shape == shape for x in X]):
          raise ValueError(
              "All the elements of X should have the same\
           shape."
          )
      return [safe_array(x, dtype) for x in X]
  
imports: import numpy
  import pandas
  from warnings import warn
label_desc: Use image node_id 2 for calling a global function with example usage: check_longitudinal_features_consistency(X, shape, dtype) and returns: unknown