loader = saved_model_loader.SavedModelLoader(self._output_saved_model_path)
    graphdef = loader.get_meta_graph_def_from_tags(tags).graph_def
    # The Conv2D op shouldn't be quantized as it has no FakeQuant on input.
    self.assertTrue(self._contains_op(graphdef, 'Conv2D'))
    # If the Gather op is quantized, input_model_size / output_model_size > 2.
    self.assertLess(
        testing.get_size_ratio(

  let results = (outs TFL_FpTensor:$output);
}

def TFL_FakeQuantOp : TFL_Op<"fake_quant", [
    Pure,
    QuantizableResult]> {
  let summary = "FakeQuant operator";

  let description = [{
    Fake-quantize the 'inputs' tensor of type float via float scalars min and
    max to 'outputs' tensor of same shape as inputs.
  }];

  let arguments = (