docstr: Test for np ndarray input for l1 transformation
docstr_tok: ["Test","for","np","ndarray","input","for","l1","transformation"]
code: def test_numpyndarrayInput_l1(self):
      """Test for np ndarray input for l1 transformation"""
      ndarray_matrix = np.array([[1, 0, 2], [0, 0, 3], [4, 5, 6]])
      normalized = self.model_l1.normalize(ndarray_matrix)
  
      # Check if output is of same type
      self.assertTrue(isinstance(normalized, np.ndarray))
  
      # Check if output is correct
      expected = np.array(
          [
              [0.04761905, 0.0, 0.0952381],
              [0.0, 0.0, 0.14285714],
              [0.19047619, 0.23809524, 0.28571429],
          ]
      )
      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_l1,
          [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 4 for calling the TestNormModel obj's underlying member method code with example usage: obj.test_numpyndarrayInput_l1() without return types