func.func @Int64SliceBeginSize(%arg0: tensor<4x128x32xf32>) -> tensor<1x128x32xf32> {
  %0 = "tfl.pseudo_const"() {value = dense<0> : tensor<3xi64>} : () -> tensor<3xi64>
  %1 = "tfl.pseudo_const"() {value = dense<[1, 128, 32]> : tensor<3xi64>} : () -> tensor<3xi64>
  %2 = "tfl.slice"(%arg0, %0, %1) : (tensor<4x128x32xf32>, tensor<3xi64>, tensor<3xi64>) -> tensor<1x128x32xf32>
  func.return %2 : tensor<1x128x32xf32>

  func.return %3 : tensor<2xi64>
  // CHECK: %[[CST:.*]] = "tf.Const"() <{value = dense<[1, 2]> : tensor<2xi64>}> : () -> tensor<2xi64>
  // CHECK: return %[[CST]]
}

// CHECK-LABEL: testFoldStridedSliceShapeDynamicOutput
func.func @testFoldStridedSliceShapeDynamicOutput(%arg0: tensor<?x1x2x?xf32>) -> (tensor<?xi32>) {

  %2 = mhlo.constant dense<0.000000e+00> : tensor<f32>

    -> (tensor<?x2xi64>, tensor<?x2xi64>, tensor<?x!tf_type.string>, tensor<?xi64>, tensor<2xi64>, tensor<2xi64>, tensor<32xf32>, tensor<32xf32>)

  // CHECK: tfrt.return {{.*}}, [[outputs]]#0
  func.return %outputs#0 : tensor<?x2xi64>
}

// CHECK-LABEL: func @no_native

  // CHECK-NEXT:  return [[FIND]] : tensor<*xi64>
  func.return %1 : tensor<*xi64>
}

// -----

// Test for case with int64 -> string hashtable.
func.func @hashtable_int64_to_string(%arg0: tensor<i64>) -> tensor<*x!tf_type.string> {
  %cst = arith.constant dense<"f"> : tensor<!tf_type.string>

  %2 = "mhlo.dynamic_broadcast_in_dim"(%cst_0, %1) <{broadcast_dimensions = dense<3> : tensor<1xi64>}> : (tensor<2xf32>, tensor<4xindex>) -> tensor<?x256x256x2xf32>
  %3 = mhlo.multiply %0, %2 : tensor<?x256x256x2xf32>
  %4 = "mhlo.dynamic_broadcast_in_dim"(%cst_1, %1) <{broadcast_dimensions = dense<3> : tensor<1xi64>}> : (tensor<2xf32>, tensor<4xindex>) -> tensor<?x256x256x2xf32>
  %5 = mhlo.add %3, %4 : tensor<?x256x256x2xf32>

  func.return %cst : tensor<1x750xf32>

  // CHECK-DAG: %0 = mhlo.constant dense<7.680000e+02> : tensor<f32>
  // CHECK: %1 = "mhlo.broadcast_in_dim"(%0) <{broadcast_dimensions = dense<> : tensor<0xi64>}> : (tensor<f32>) -> tensor<1x750xf32>
  // CHECK: return %1 : tensor<1x750xf32>
}

// CHECK-LABEL: @unfold_splat_constant_integer
func.func @unfold_splat_constant_integer() -> tensor<1x750xi32> {

module {
  func.func @main() -> tensor<1xi64> {
  %0 = "tfl.custom"() {custom_code = "stablehlo.constant", custom_option = #tfl<const_bytes : "0x76616C75650001020109010101062C022401">} : () -> tensor<1xi64>
  func.return %0 : tensor<1xi64>
  }
}

// CHECK:  module {
// CHECK-NEXT:    func @main() -> tensor<1xi64> {
// CHECK-NEXT:    %[[c0:.+]] = stablehlo.constant dense<2> : tensor<1xi64>
// CHECK-NEXT:    return %[[c0]] : tensor<1xi64>

  // CHECK-DAG: %[[SCALE_BCAST:.+]] = "mhlo.broadcast_in_dim"(%[[SCALE]]) <{broadcast_dimensions = dense<1> : tensor<1xi64>}> : (tensor<256xf32>) -> tensor<4x256xf32>
  // CHECK-DAG: %[[OFFSET_BCAST:.+]] = "mhlo.broadcast_in_dim"(%[[OFFSET]]) <{broadcast_dimensions = dense<1> : tensor<1xi64>}> : (tensor<256xf32>) -> tensor<4x256xf32>

    %4 = "tf.AddV2"(%3, %1) {device = ""} : (tensor<?xi64>, tensor<i64>) -> tensor<?xi64>
    %5 = "tf.LookupTableFindV2"(%0, %arg0, %cst) {device = ""} : (tensor<!tf_type.resource>, tensor<?x!tf_type.string>, tensor<i64>) -> tensor<*xi64>
    return %5 : tensor<*xi64>
  }

// Check that HashTable op is lifted.
// CHECK: func.func private @serving_default