module attributes {tf.versions = {producer = 179 : i32}} {
  func.func @main(%arg0: tensor<f32>) -> tensor<f32> {
    %0 = "stablehlo.uniform_quantize"(%arg0) : (tensor<f32>) -> tensor<!quant.uniform<ui8:f32, 34.0:16>>
    %1 = "stablehlo.uniform_dequantize"(%0) : (tensor<!quant.uniform<ui8:f32, 34.0:16>>) -> tensor<f32>
    func.return %1 : tensor<f32>
  }
}

// CHECK-LABEL: HloModule main
// CHECK:       ENTRY %main.{{[0-9]+}} ([[ARG0:.*]]: f32[]) -> (f32[]) {

// `tfl.quantize` or `tfl.dequantize` ops. ui8, i8 and i16 are supported.
bool IsSupportedByTfliteQuantizeOrDequantizeOps(IntegerType storage_type) {
  if (storage_type.getWidth() == 8 ||
      (storage_type.isSigned() && storage_type.getWidth() == 16)) {
    return true;
  }
  LLVM_DEBUG(llvm::dbgs()
             << "Uniform quantize / dequantize op only supports ui8, i8 or "

bool IsI32F32UniformQuantizedPerAxisType(Type type);

// Determines whether the storage type of a quantized type is supported by
// `tfl.quantize` or `tfl.dequantize` ops. ui8, i8 and i16 are supported.
bool IsSupportedByTfliteQuantizeOrDequantizeOps(IntegerType storage_type);

// Returns true if a type is quantized tensor type.
bool IsQuantizedTensorType(Type type);

	// integer values
	ui0 = 0
	ui1 = 1
	ui2 = 42
	ui3 = 3141592653589793238462643383279502884197169399375105820974944592307816406286
	ui4 = -10

	ui5 = ui0 + ui1
	ui6 = ui1 - ui1
	ui7 = ui2 * ui1
	ui8 = ui3 / ui3
	ui9 = ui3 % ui3

	ui10 = 1 / 0 /* ERROR "division by zero" */
	ui11 = ui1 / 0 /* ERROR "division by zero" */
	ui12 = ui3 / ui0 /* ERROR "division by zero" */
	ui13 = 1 % 0 /* ERROR "division by zero" */