func.return %0 : tensor<2x4xui8>
}

// CHECK-LABEL: func @and
func.func @and(%arg0: tensor<2xi1>, %arg1: tensor<2xi1>) -> tensor<2xi1> {
  // CHECK-NEXT:  mhlo.and
  %0 = "tf.LogicalAnd"(%arg0, %arg1) : (tensor<2xi1>, tensor<2xi1>) -> tensor<2xi1>
  func.return %0: tensor<2xi1>
}

// CHECK-LABEL: func @and_unranked
func.func @and_unranked(%arg0: tensor<*xi1>, %arg1: tensor<*xi1>) -> tensor<*xi1> {

  %a = corert.const_dense_tensor dense<[true, false]> : tensor<2xi1>
  %b = corert.const_dense_tensor dense<[false, true]> : tensor<2xi1>
  // CHECK: [[b:%.*]] = tfrt_fallback_async.const_dense_tensor dense<[false, true]> : tensor<2xi1>
  // CHECK-NEXT:      [[a:%.*]] = tfrt_fallback_async.const_dense_tensor dense<[true, false]> : tensor<2xi1>
  // CHECK-NEXT: tfrt_fallback_async.corert_tensorhandle_to_fallback_tensor [[arg0]]

// Identity function to make the exporter happy
func.func @main(%arg0: tensor<4xi8>) -> tensor<4xi8> {
  func.return %arg0 : tensor<4xi8>
}

//CHECK:func.func @main(%arg0: tensor<4xi8>) -> tensor<4xi8> attributes {tf.entry_function = {inputs = "arg0", outputs = "arg0"}} {
//CHECK: return %arg0 : tensor<4xi8>
//CHECK:}

// test stablehlo roundtrip

// Identity function to make the exporter happy
func.func @main(%arg0: tensor<4xi8>) -> tensor<4xi8> {
  func.return %arg0 : tensor<4xi8>
}

//CHECK:func.func @main(%arg0: tensor<4xi8>) -> tensor<4xi8> attributes {tf.entry_function = {inputs = "arg0", outputs = "arg0"}} {
//CHECK: return %arg0 : tensor<4xi8>
//CHECK:}

func.func @logistic(%arg0: tensor<1x1x1x96xf32>) -> tensor<1x1x1x96xf32> {

// RUN: stablehlo-quant-opt %s -verify-quant-legalization -split-input-file -verify-diagnostics | FileCheck %s

// CHECK-LABEL: func @legal_i8
func.func @legal_i8(%arg0: tensor<1xi8>) -> tensor<1xi8> {
  func.return %arg0: tensor<1xi8>
}

// -----

func.func @illegal_qint8(%arg0: tensor<1x!tf_type.qint8>) -> tensor<1x!tf_type.qint8> {
  // expected-error@+1 {{'func.return' op is illegal as it is a UQ op or contains uq/qint types}}

    %19 = "tf.BroadcastTo"(%4, %17) : (tensor<2x?x?xi8>, tensor<3xi64>) -> tensor<2x?x?xi8>
    %20 = "tf.BroadcastTo"(%9, %18) : (tensor<2x?x?xi8>, tensor<3xi64>) -> tensor<2x?x?xi8>
    %21 = "tf.XlaDotV2"(%19, %20) {dimension_numbers = "\22\01\00\1A\01\00\12\01\01\0A\01\02", precision_config = ""} : (tensor<2x?x?xi8>, tensor<2x?x?xi8>) -> tensor<2x?x?xi32>
    %22 = "tf.Cast"(%19) {Truncate = false} : (tensor<2x?x?xi8>) -> tensor<2x?x?xi32>

  }

  func.func private @internal_conv3d_fn(
                         %input : tensor<*xf32>, %filter : tensor<*xi8>) -> tensor<*xf32> {

   // Use identity op to avoid the filter being constant-folded.
    %identity = "tf.Identity"(%filter) : (tensor<*xi8>) -> tensor<*xi8>
    %2 = "tf.Cast"(%identity) {Truncate = false} : (tensor<*xi8>) -> tensor<*xf32>
    %3 = "tf.Conv3D"(%input, %2) {
      padding = "VALID", strides = [1, 1, 1, 1, 1],

  }

  // For weight-only
  func.func @dequantize_i8(%input : tensor<*xi8>, %scale : tensor<*xf32>, %zp : tensor<*xi32>) -> tensor<*xf32> {
    // Use identity op to avoid the weight being constant-folded.
    %identity = "tf.Identity"(%input) : (tensor<*xi8>) -> tensor<*xi8>
    %input_i32 = "tf.Cast"(%identity) : (tensor<*xi8>) -> tensor<*xi32>

    %i8 = "tf.Cast"(%round) : (tensor<*xf32>) -> tensor<*xi8>
    func.return %i8 : tensor<*xi8>
  }

  func.func @dequantize_i8(%input : tensor<*xi8>, %scale : tensor<*xf32>, %zp : tensor<*xi32>) -> tensor<*xf32> {
    // Use identity op to avoid the weight being constant-folded.
    %identity = "tf.Identity"(%input) : (tensor<*xi8>) -> tensor<*xi8>
    %input_i32 = "tf.Cast"(%identity) : (tensor<*xi8>) -> tensor<*xi32>

// CHECK: %[[BITCAST_CONVERT_0:.*]] = stablehlo.bitcast_convert %[[UQ]] : (tensor<1x!quant.uniform<i8:f32, 1.000000e+00:3>>) -> tensor<1xi8>
// CHECK: %[[BITCAST_CONVERT_1:.*]] = stablehlo.bitcast_convert %[[BITCAST_CONVERT_0]] : (tensor<1xi8>) -> tensor<1x!quant.uniform<i8:f32, 1.000000e+00:3>>