StrEq("composite_dot_general_fn_2"));
  EXPECT_TRUE(quantized_result.method().has_static_range_ptq());

  // Test that the non-quantized op is captured in `results`.
  const QuantizationResult& non_quantized_result = results.results(1);
  EXPECT_THAT(non_quantized_result.quantizable_unit().name(),
              StrEq("composite_dot_general_fn_1"));

        # function name matches "composite_dot_general_fn_1".
        # "composite_dot_general_fn_2" will be quantized.
        specs=qc.QuantizationSpecs(
            specs=[
                qc.QuantizationSpec(
                    matcher=qc.MatcherSpec(
                        function_name=qc.FunctionNameMatcherSpec(
                            regex='composite_dot_general_fn_1'
                        )

func.func private @quantize_simple_xla_call_module_no_operand() -> tensor<1x3xf32> {

  ASSERT_TRUE(module_op);

  auto composite_dot_general_fn =
      module_op->lookupSymbol<func::FuncOp>("composite_dot_general_fn_1");
  ASSERT_THAT(composite_dot_general_fn, NotNull());

  auto dot_general_op = FindOperationOfType<mlir::stablehlo::DotGeneralOp>(
      composite_dot_general_fn);
  EXPECT_TRUE(IsInLiftedFunc(dot_general_op));
}

  EXPECT_THAT(xla_call_module_op,
              HasSymNameAttr("_entry_function",
                             StartsWith("composite_dot_general_fn")));
  EXPECT_THAT(xla_call_module_op,
              HasStringAttr("_original_entry_function",
                            StartsWith("composite_dot_general_fn")));

  // Tests that there are CustomAggregatorOps inserted.
  SmallVector<TF::CustomAggregatorOp> custom_aggregator_ops;

      %1 = "tf.XlaCallModule"(%0, %cst) {Sout = [#tf_type.shape<1x3>], _entry_function = @composite_dot_general_fn, _original_entry_function = "composite_dot_general_fn", _quantization_method = "static_range_ptq { }", _stablehlo_module_attrs = {}, _tfl_quant_trait = "fully_quantizable", device = "", dim_args_spec = [], disabled_checks = [], has_token_input_output = false, module...

    return %2 : tensor<1x3xf32>
  }
  // CHECK-LABEL: func.func private @composite_dot_general_fn_1
  // CHECK-SAME: -> tensor<1x3xf32>

    return %0 : tensor<1x3xf32>
    // CHECK: %[[CALL:.+]] = "tf.XlaCallModule"(%[[ARG0]], %[[ARG1]])
    // CHECK-SAME: _entry_function = @composite_dot_general_fn_1
    // CHECK-SAME: _original_entry_function = "composite_dot_general_fn_1"
    // CHECK: return %[[CALL]]
  }

  // CHECK: @composite_dot_general_fn_1
  // CHECK-SAME: %[[ARG2:[^:[:space:]]+]]
  // CHECK-SAME: %[[ARG3:[^:[:space:]]+]]

// WholeModel-DAG: "tf.DumpTensor"(%[[matmul0_q]]) <{enabled = true, file_name = "unquantized_tensor_data.pb", func_name = "composite_dot_general_fn_1", log_dir_path = "/tmp/dumps/composite_dot_general_fn_1",...

// quantization method, implying "no_quantization".
// EMPTY-SAME: _entry_function = @composite_dot_general_fn_1
// EMPTY-SAME: _original_entry_function
// EMPTY-NOT: _quantization_method
// EMPTY-SAME: _tfl_quant_trait = "fully_quantizable"

// EMPTY: return %[[XLA_CALL_MODULE:.+]] : tensor<1x1x64xf32>
// EMPTY: }

// EMPTY-LABEL: private @composite_dot_general_fn_1
// EMPTY-SAME: tf_quant.composite_function