%14 = mhlo.compare  LT, %13, %6 : (tensor<32x32xi64>, tensor<32x32xi64>) -> tensor<32x32xi1>
  %15 = mhlo.add %13, %4 : tensor<32x32xi64>
  %16 = mhlo.select %14, %15, %13 : tensor<32x32xi1>, tensor<32x32xi64>
  %17 = mhlo.reshape %16 : (tensor<32x32xi64>) -> tensor<32x32x1xi64>
  %18 = "mhlo.concatenate"(%12, %17) <{dimension = 2 : i64}> : (tensor<32x32x1xi64>, tensor<32x32x1xi64>) -> tensor<32x32x2xi64>

    module {
      func.func @main() -> (tensor<2x3x2x2xf32>) {
        %0 = stablehlo.constant dense<1.0> : tensor<3x4x2xf32>
        %1 = stablehlo.constant dense<2> : tensor<2x3x2xi64>
        %2 = "stablehlo.gather"(%0, %1) {
          dimension_numbers = #stablehlo.gather<
            offset_dims = [2, 3],
            collapsed_slice_dims = [0],
            start_index_map = [1, 0],

    tensor<3x4x2x2x!quant.uniform<i8:f32, 3.000000e-01:-5>>,
    tensor<2x3x2xi64>
  ) -> tensor<2x3x2x2x!quant.uniform<i8:f32, 3.000000e-01:-5>>
  return %0 : tensor<2x3x2x2x!quant.uniform<i8:f32, 3.000000e-01:-5>>
}

// CHECK-LABEL: func @gather
// CHECK-SAME: %[[ARG_0:.+]]: tensor<3x4x2x2x!quant.uniform<i8:f32, 3.000000e-01:-5>>, %[[ARG_1:.+]]: tensor<2x3x2xi64>
// CHECK: %[[GATHER:.+]] = "tfl.gather_nd"(%[[ARG_0]], %[[ARG_1]])

    indices_are_sorted = #vhlo.bool_v1<false>
  }> : (tensor<3x4x2xi32>, tensor<2x3x2xi64>) -> tensor<2x3x2x2xi32>
  return %result : tensor<2x3x2x2xi32>
}


// CHECK: func.func private @gather(%arg0: tensor<3x4x2xi32>, %arg1: tensor<2x3x2xi64>) -> tensor<2x3x2x2xi32> {

  // CHECK-SAME: %[[ARG0:.*]]: tensor<3x4x5xf32>
  // CHECK-SAME: %[[ARG1:.*]]: tensor<3x5x2xf32>
  // CHECK-SAME: %[[ARG2:.*]]: tensor<2x3x2xi64>
  func.func private @composite_and_gather(%arg0: tensor<3x4x5xf32>, %arg1: tensor<3x5x2xf32>, %arg2: tensor<2x3x2xi64>) -> tensor<2x3x2x2xf32> {
    // CHECK: %[[Q1:.*]] = "quantfork.qcast"(%[[ARG0]]) {volatile} : (tensor<3x4x5xf32>) -> tensor<3x4x5x!quant.uniform<i8:f32, 5.000000e-03>>

// -----

// Test that q/dq pair is not inserted between constant and XlaCallModule op
// whose entry function name does not include conv nor dot_general.

func.func @no_qdq_except_conv_and_dot_general(%arg0: tensor<2x3x2xi64>) -> tensor<2x3x2x2xf32> attributes {tf._original_func_name = "main_0"} {
  %cst = "tf.Const"() {value = dense<3.000000e-01> : tensor<3x4x2xf32>} : () -> tensor<3x4x2xf32>
  %0 = "tf.XlaCallModule"(%cst, %arg0) {

  %1 = stablehlo.constant dense<1> : tensor<2x3x2xi64>
  %2 = "stablehlo.gather"(%0, %1) {
  dimension_numbers = #stablehlo.gather<
    offset_dims = [2, 3],
    collapsed_slice_dims = [0],
    start_index_map = [1, 0],
    index_vector_dim = 2>,
  slice_sizes = array<i64: 1, 2, 2>,
  indices_are_sorted = false
} : (tensor<3x4x2xi32>, tensor<2x3x2xi64>) -> tensor<2x3x2x2xi32>
  func.return %2: tensor<2x3x2x2xi32>