docstr: Test for np ndarray input for l2 transformation
docstr_tok: ["Test","for","np","ndarray","input","for","l2","transformation"]
code: def test_numpyndarrayInput_l2(self):
      """Test for np ndarray input for l2 transformation"""
      ndarray_matrix = np.array([[1, 0, 2], [0, 0, 3], [4, 5, 6]])
      normalized = self.model_l2.normalize(ndarray_matrix)
  
      # Check if output is of same type
      self.assertTrue(isinstance(normalized, np.ndarray))
  
      # Check if output is correct
      expected = np.array(
          [
              [0.10482848, 0.0, 0.20965697],
              [0.0, 0.0, 0.31448545],
              [0.41931393, 0.52414242, 0.6289709],
          ]
      )
      self.assertTrue(np.allclose(normalized, expected))
  
      # Test if error is raised on unsupported input type
      self.assertRaises(
          ValueError,
          lambda model, doc: model.normalize(doc),
          self.model_l2,
          [1, 2, 3],
      )
  
imports: import logging
  import unittest
  import numpy
  from scipy.sparse import csr_matrix
  from scipy.sparse import issparse
  from gensim.corpora import mmcorpus
  from gensim.models import normmodel
  from gensim.test.utils import datapath, get_tmpfile
label_desc: Use image node_id 7 for calling the TestNormModel obj's underlying member method code with example usage: obj.test_numpyndarrayInput_l2() without return types