code: def _check_input_size(n_components, n_features):
      """Factorize argument checking for random matrix generation"""
      if n_components <= 0:
          raise ValueError(
              "n_components must be strictly positive, got %d"
              % n_components
          )
      if n_features <= 0:
          raise ValueError(
              "n_features must be strictly positive, got %d"
              % n_components
          )
  
imports: from __future__ import division
  import warnings
  from abc import ABCMeta, abstractmethod
  import numpy
  from numpy.testing import assert_equal
  import scipy.sparse
  from .base import BaseEstimator, TransformerMixin
  from .externals import six
  from .externals.six.moves import xrange
  from .utils import check_random_state
  from .utils.extmath import safe_sparse_dot
  from .utils.random import sample_without_replacement
  from .utils.validation import check_array
  from .exceptions import DataDimensionalityWarning
  from .exceptions import NotFittedError
label_desc: Use image node_id 3 for calling a global function with example usage: _check_input_size(n_components, n_features) without return types