# Consider if there is a way to check if activation fusion is properly
    # done in MLIR level.
    # Tests that the quantized graph outputs similar values. The rtol and atol
    # values are arbitrary.
    self.assertAllClose(new_outputs, expected_outputs, rtol=0.3, atol=0.2)

    # Due to other meta data, the compression is not exactly 1/4.
    self.assertLess(
        testing.get_size_ratio(

    # expected to be small.
    # The atol value is arbitrary.
    if not enable_per_channel_quantization:
      expected_outputs = model.conv(input_data)
      target_outputs = converted_model.signatures['serving_default'](
          input_tensor=ops.convert_to_tensor(input_data)
      )
      self.assertAllClose(target_outputs, expected_outputs, atol=0.06)

    if target_opset == quant_opts_pb2.XLA:

}

func Strtol(s string, base int) (int, error) {
	p := C.CString(s)
	n, err := C.strtol(p, nil, C.int(base))
	C.free(unsafe.Pointer(p))
	return int(n), err
}

func Atol(s string) int {
	p := C.CString(s)
	n := C.atol(p)
	C.free(unsafe.Pointer(p))
	return int(n)
}

func testConst(t *testing.T) {
	C.myConstFunc(nil, 0, nil)
}

func testEnum(t *testing.T) {

			if VerifyAgainstWhitelist(input, whitelist) {
				for _, tol := range input {
					require.True(t, isContained(tol, whitelist), debugMsg(input, whitelist))
				}
			} else {
				uncontained := false
				for _, tol := range input {
					if !isContained(tol, whitelist) {
						uncontained = true
						break
					}
				}

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