func.func @testOneHot(%arg0: tensor<3xi32>, %arg1: tensor<i32>, %arg2: tensor<f32>, %arg3: tensor<f32>) -> tensor<*xf32> {
  // CHECK: "tfl.one_hot"(%arg0, %arg1, %arg2, %arg3) <{axis = -1 : i32}> : (tensor<3xi32>, tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<*xf32>
  %0 = "tfl.one_hot"(%arg0, %arg1, %arg2, %arg3) {axis = -1 : i32} : (tensor<3xi32>, tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<*xf32>
  func.return %0 : tensor<*xf32>
}

  %0 = "tf.OneHot"(%arg0, %arg1, %arg2, %arg3) {axis = -1 : i64} : (tensor<3xi32>, tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<*xf32>
  func.return %0: tensor<*xf32>

// CHECK-LABEL: OneHot
// CHECK: "tfl.one_hot"(%arg0, %arg1, %arg2, %arg3) <{axis = -1 : i32}> : (tensor<3xi32>, tensor<i32>, tensor<f32>, tensor<f32>) -> tensor<*xf32>
}

func.func @argmax(%arg0: tensor<3xi32>, %arg1: tensor<i32>) -> tensor<i32> {

  );

  let results = (outs
    TFL_TensorOf<[F32, I32, I64, QI8, QUI8, UI8, QI16]>:$output);

  let hasOptions = 1;
  let customOption = "ReducerOptions";
}

def TFL_OneHotOp : TFL_Op<"one_hot", [
    QuantizableResult,
    Pure]> {
  let summary = "OneHot operator";

  let description = [{
    Returns a one-hot tensor.The locations represented by indices in `indices`