code: def test_translate_architecture_to_assignment(self):
      algorithm = categorical_harmonica.Harmonica(
          test_utils.create_spec(
              phoenix_spec_pb2.PhoenixSpec.DNN,
              blocks_to_use=[
                  "FIXED_CHANNEL_CONVOLUTION_16",
                  "FIXED_CHANNEL_CONVOLUTION_32",
                  "FIXED_CHANNEL_CONVOLUTION_64",
                  "CONVOLUTION_3X3",
              ],
              min_depth=4,
          )
      )
      assignment = (
          algorithm.translate_architecture_to_feature_assignment(
              np.array([2, 3, 4])
          )
      )
      expected_output = [
          [
              1.00000000e00,
              6.12323400e-17,
              -1.00000000e00,
              -1.83697020e-16,
              1.00000000e00,
              -1.00000000e00,
              1.00000000e00,
              -1.00000000e00,
              1.00000000e00,
              -1.83697020e-16,
              -1.00000000e00,
              5.51091060e-16,
              0.00000000e00,
              -1.00000000e00,
              3.67394040e-16,
              1.00000000e00,
          ],
          [
              0.00000000e00,
              1.00000000e00,
              1.22464680e-16,
              -1.00000000e00,
              0.00000000e00,
              1.22464680e-16,
              -2.44929360e-16,
              3.67394040e-16,
              0.00000000e00,
              -1.00000000e00,
              3.67394040e-16,
              1.00000000e00,
              1.00000000e00,
              -1.83697020e-16,
              -1.00000000e00,
              5.51091060e-16,
          ],
      ]
      for i in range(len(assignment)):
          self.assertAllAlmostEqual(expected_output[i], assignment[i])
  
imports: from absl import logging
  from absl.testing import parameterized
  import mock
  from model_search import hparam
  from model_search.metadata import trial
  from model_search.proto import phoenix_spec_pb2
  from model_search.search import categorical_harmonica
  from model_search.search import test_utils
  import numpy
  from sklearn import preprocessing
  import tensorflow.compat.v2
label_desc: Use image node_id 3 for calling the HarmonicaTest obj's underlying member method code with example usage: obj.test_translate_architecture_to_assignment() without return types