code: def test_fit_transform(self):
      umap_model = umap.UmapModel(n_components=3)
  
      # Make fake embeddings.
      n = 100
      inputs = testing_utils.fake_projection_input(n, 10)
  
      outputs = umap_model.fit_transform(inputs)
      outputs_list = list(outputs)
  
      # Check that the output dict keys are correct.
      self.assertIn("z", outputs_list[0])
  
      # Check that the _fitted flag has been flipped.
      self.assertTrue(umap_model._fitted)
  
      # Check correctness of the output shape.
      output_np = np.array([o["z"] for o in outputs_list])
      shape = output_np.shape
      expected_shape = (n, 3)
      self.assertEqual(shape, expected_shape)
      self.assertFalse(np.any(np.iscomplex(output_np)))
  
file_path: lit/lit_nlp/components/umap_test.py
imports: from absl.testing import absltest
  from lit_nlp.components import umap
  from lit_nlp.lib import testing_utils
  import numpy
label_desc: Use image node_id 1 for calling the UmapTest obj's underlying member method code with example usage: obj.test_fit_transform() without return types