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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def make_mutant_features(original_feature, index_to_mutate, viz_params):
 """Return a list of `MutantFeatureValue`s that are variants of original."""

  lower = viz_params.x_min
  upper = viz_params.x_max
  examples = viz_params.examples
  num_mutants = viz_params.num_mutants

  if original_feature.feature_type == 'float_list':
    return [
        MutantFeatureValue(original_feature, index_to_mutate, value)
        for value in np.linspace(lower, upper, num_mutants)
    ]
  elif original_feature.feature_type == 'int64_list':
    mutant_values = np.linspace(int(lower), int(upper),
                                num_mutants).astype(int).tolist()
    # Remove duplicates that can occur due to integer constraint.
    mutant_values = sorted(set(mutant_values))
    return [
        MutantFeatureValue(original_feature, index_to_mutate, value)
        for value in mutant_values
    ]
  elif original_feature.feature_type == 'bytes_list':
    feature_to_samples = get_categorical_features_to_sampling(
        examples, num_mutants)

    # `mutant_values` looks like:
    # [['Married-civ-spouse'], ['Never-married'], ['Divorced'], ['Separated']]
    mutant_values = feature_to_samples[original_feature.feature_name]['samples']
    return [
        MutantFeatureValue(original_feature, None, value)
        for value in mutant_values
    ]
  else:
    raise ValueError('Malformed original feature had type of: ' +
                     original_feature.feature_type)