// CHECK: return %[[VAL2]]
  %0 = "tfl.pseudo_qconst"() {qtype = tensor<16x1x1x8x!quant.uniform<i8:f32, 1.0>>, value = dense<42> : tensor<16x1x1x8xi8>} : () -> tensor<16x1x1x8x!quant.uniform<i8:f32, 1.0>>
  %1 = "tfl.pseudo_qconst"() {qtype = tensor<16x!quant.uniform<i32:f32, 1.0>>, value = dense<0> : tensor<16xi32>} : () -> tensor<16x!quant.uniform<i32:f32, 1.0>>

    %2 = stablehlo.constant dense<-128> : tensor<1x1x1x1xi8>  // Input zero point.
    %3 = stablehlo.constant dense<1> : tensor<3x3x4x4xi8>  // Quantized filter tensor.
    %4 = stablehlo.constant dense<3.000000e+03> : tensor<1x1x1x4xf32>
    %5 = stablehlo.constant dense<4.000000e+03> : tensor<1x1x1x1xf32>  // Output inverse scale.
    %6 = stablehlo.constant dense<127> : tensor<1x1x1x1xi8>  // Output zero point.

}

TEST_F(AttrsAndConstraintsTest, HasRankOfReturnsTrueForMatchingRank) {
  constexpr absl::string_view kConstantOpWithRankFour =
      R"mlir(%0 = stablehlo.constant dense<0> : tensor<1x1x1x1xi8>)mlir";
  OwningOpRef<ModuleOp> module_op =
      ParseModuleOpString(kConstantOpWithRankFour);
  ASSERT_TRUE(module_op);

  ASSERT_FALSE(module_op->getBodyRegion().empty());