code: def test_mmc(self):
      def_kwargs = {
          "tol": 0.001,
          "diagonal": False,
          "diagonal_c": 1.0,
          "init": "identity",
          "max_iter": 100,
          "max_proj": 10000,
          "preprocessor": None,
          "random_state": None,
          "verbose": False,
      }
      nndef_kwargs = {"diagonal": True}
      merged_kwargs = sk_repr_kwargs(def_kwargs, nndef_kwargs)
      self.assertEqual(
          remove_spaces(str(metric_learn.MMC(diagonal=True))),
          remove_spaces(f"MMC({merged_kwargs})"),
      )
      def_kwargs = {
          "tol": 1e-06,
          "diagonal": False,
          "diagonal_c": 1.0,
          "init": "identity",
          "max_iter": 100,
          "max_proj": 10000,
          "n_constraints": None,
          "preprocessor": None,
          "random_state": None,
          "verbose": False,
      }
      nndef_kwargs = {"max_iter": 1}
      merged_kwargs = sk_repr_kwargs(def_kwargs, nndef_kwargs)
      self.assertEqual(
          remove_spaces(str(metric_learn.MMC_Supervised(max_iter=1))),
          remove_spaces(f"MMC_Supervised({merged_kwargs})"),
      )
  
imports: from numpy.core.numeric import array_equal
  import pytest
  import re
  import unittest
  import metric_learn
  import numpy
  from sklearn import clone
  from test.test_utils import ids_metric_learners, metric_learners, remove_y
  from metric_learn.sklearn_shims import set_random_state, SKLEARN_AT_LEAST_0_22
label_desc: Use image node_id 10 for calling the TestStringRepr obj's underlying member method code with example usage: obj.test_mmc() without return types