return %0 : tensor<2x2xf32>
    }
    func.func private @composite_fn_1(%arg0: tensor<2x2xf32>, %arg1: tensor<2x2xf32>) -> tensor<2x2xf32> attributes {tf_quant.composite_function} {

      %2 = "tf.XlaCallModule"(%arg0, %1, %0) <{Sout = [#tf_type.shape<?x2>], module = "", version = 9 : i64}> {_entry_function = @composite_dot_general_fn_1, _original_entry_function = "composite_dot_general_fn_1", _tfl_quant_trait = "fully_quantizable", _quantization_method = "weight_only_ptq { }"} : (tensor<?x2xf32>, tensor<2x2xf32>, tensor<2xf32>) -> tensor<?x2xf32>
      return %2 : tensor<?x2xf32>

func.func @uniform_quantize_and_dequantize_per_axis(%arg0 : tensor<2x2xf32>) -> tensor<2x2xf32> {
  %scales = "tf.Const"() { value = dense<[1.0, 2.0]> : tensor<2xf32> } : () -> tensor<2xf32>
  %zps = "tf.Const"() { value = dense<[3, 4]> : tensor<2xi32> } : () -> tensor<2xi32>

  // CHECK: %[[QUANTIZE:.*]] = mhlo.uniform_quantize %arg0 : (tensor<2x2xf32>) -> tensor<2x2x!quant.uniform<i8:f32:0, {1.000000e+00:3,2.000000e+00:4}>>

func.func @NotQuantizeFloatConst() -> tensor<2x2xf32> {
  %0 = arith.constant dense<-0.1> : tensor<2x2xf32>
  %1 = "tfl.quantize"(%0) {qtype = tensor<2x2x!quant.uniform<u8:f32, 7.8431372549019615E-4:128>>} : (tensor<2x2xf32>) -> tensor<2x2x!quant.uniform<u8:f32, 7.8431372549019615E-4:128>>
  %2 = "tfl.dequantize"(%1) : (tensor<2x2x!quant.uniform<u8:f32, 7.8431372549019615E-4:128>>) -> tensor<2x2xf32>
  func.return %2 : tensor<2x2xf32>

    %7 = stablehlo.slice %6 [1:3, 2:4] : (tensor<3x4xf32>) -> tensor<2x2xf32>
    %8 = "quantfork.qcast"(%7) {volatile} : (tensor<2x2xf32>) -> tensor<2x2x!quant.uniform<i8:f32, 0.13170163023705575:-1>>
    %9 = "quantfork.dcast"(%8) : (tensor<2x2x!quant.uniform<i8:f32, 0.13170163023705575:-1>>) -> tensor<2x2xf32>
    return %9 : tensor<2x2xf32>
  }

  // CHECK: quantized_dot_general_fn_1

// CHECK-NOT: quantfork.qcast
// CHECK-NOT: quantfork.dcast

// -----

// Test that q/dq pair is not inserted when constant has multiple users.

func.func @no_qdq_for_multiple_users(%arg0: tensor<2x2xf32>) -> tensor<2x3xf32> attributes {tf._original_func_name = "main_0"} {
  %cst = "tf.Const"() {value = dense<3.000000e-01> : tensor<2x3xf32>} : () -> tensor<2x3xf32>
  %0 = "tf.XlaCallModule"(%arg0, %cst) {