class_docstr: Container to identify training set.
  
  Samples a random subset from set passed to the `fit` method, to allow
  identification of the training set in a `transform` or `predict` method.
  
  Parameters
  ----------
  size : int
      size to sample. A random subset of size [size, size] will be stored
      in the instance.
docstr: Check if X has the shape as the training set.
code: def _check_shape(self, X):
      """Check if X has the shape as the training set."""
      return all([X.shape[i] == self.train_shape[i] for i in range(2)])
  
file_path: mlens/mlens/utils/id_train.py
imports: from __future__ import division, print_function
  from ..utils.exceptions import NotFittedError
  from ..externals.sklearn.base import BaseEstimator
  from numpy import array_equal, ix_
  from numpy.random import permutation
  from numbers import Integral
label_desc: Use image node_id 4 for calling the IdTrain obj's underlying member method code with example usage: obj._check_shape(X) and returns: all