code: def _test_string_not_equal(self, compval, missing, labelarray_dtype):
      compval = labelarray_dtype.type(compval)
  
      class C(Classifier):
          dtype = categorical_dtype
          missing_value = missing
          inputs = ()
          window_length = 0
  
      c = C()
  
      # There's no significance to the values here other than that they
      # contain a mix of the comparison value and other values.
      data = LabelArray(
          np.asarray(
              [
                  ["", "a", "ab", "ba"],
                  ["z", "ab", "a", "ab"],
                  ["aa", "ab", "", "ab"],
                  ["aa", "a", "ba", "ba"],
              ],
              dtype=labelarray_dtype,
          ),
          missing_value=missing,
      )
  
      expected = (
          data.as_int_array()
          != data.reverse_categories.get(compval, -1)
      ) & (
          data.as_int_array()
          != data.reverse_categories[C.missing_value]
      )
  
      self.check_terms(
          terms={
              "ne": c != compval,
          },
          expected={
              "ne": expected,
          },
          initial_workspace={c: data},
          mask=self.build_mask(self.ones_mask(shape=data.shape)),
      )
  
imports: from functools import reduce
  from operator import or_
  import numpy
  import pandas
  from catalyst.lib.labelarray import LabelArray
  from catalyst.pipeline import Classifier
  from catalyst.testing import parameter_space
  from catalyst.testing.fixtures import CatalystTestCase
  from catalyst.testing.predicates import assert_equal
  from catalyst.utils.numpy_utils import categorical_dtype, int64_dtype
  from .base import BasePipelineTestCase
label_desc: Use image node_id 7 for calling the ClassifierTestCase obj's underlying member method code with example usage: obj._test_string_not_equal(compval, missing, labelarray_dtype) without return types