// Ensure constants roundtrip exactly

func.func @bool() -> tensor<4xi1> {
  // CHECK-LABEL: @bool
  // CHECK: value = dense<[false, true, true, false]> : tensor<4xi1>
  %0 = "tfl.pseudo_const"() { value = dense<[false, true, true, false]> : tensor<4xi1> } : () -> tensor<4xi1>
  func.return %0 : tensor<4xi1>
}

func.func @complex64() -> tensor<4xcomplex<f32>> {
  // CHECK-LABEL: @complex64

// Ensure constants roundtrip exactly

func.func @bool() -> tensor<4xi1> {
  // CHECK-LABEL: @bool
  // CHECK: value = dense<[false, true, true, false]> : tensor<4xi1>
  %0 = "tfl.pseudo_const"() { value = dense<[false, true, true, false]> : tensor<4xi1> } : () -> tensor<4xi1>
  func.return %0 : tensor<4xi1>
}

func.func @complex64() -> tensor<4xcomplex<f32>> {
  // CHECK-LABEL: @complex64

  %1 = mhlo.constant dense<0.000000e+00> : tensor<f32>
  %2 = "mhlo.pad"(%arg0, %1) {edge_padding_high = dense<[0, 0, 1, 1]> : tensor<4xi64>, edge_padding_low = dense<[0, 0, 1, 1]> : tensor<4xi64>, interior_padding = dense<0> : tensor<4xi64>} : (tensor<1x3x6x6xf32>, tensor<f32>) -> tensor<1x3x8x8xf32>
  %3 = "mhlo.reduce_window"(%2, %1) ({
  ^bb0(%arg1: tensor<f32>, %arg2: tensor<f32>):

func.func @cast_i8_to_i1() -> tensor<4xi1> {
  %cst = arith.constant dense<[0, 1, 2, -1]> : tensor<4xi8>
  %0 = "tfl.cast"(%cst) : (tensor<4xi8>) -> tensor<4xi1>
  func.return %0 : tensor<4xi1>

// CHECK: %[[CST:.*]] = arith.constant dense<[false, true, true, true]> : tensor<4xi1>
// CHECK:  return %[[CST]]
}

// CHECK-LABEL: @cast_ui8_to_i1
func.func @cast_ui8_to_i1() -> tensor<4xi1> {

  // CHECK:  %cst_2 = "tf.Const"() <{value = dense<0> : tensor<4xi64>}> : () -> tensor<4xi64>
  // CHECK-DAG:  %cst_3 = "tf.Const"() <{value = dense<[8, 8, 1, 1]> : tensor<4xi64>}> : () -> tensor<4xi64>
  // CHECK:  %cst_4 = "tf.Const"() <{value = dense<1> : tensor<4xi64>}> : () -> tensor<4xi64>

  func.func @init_all_tables()
  attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer"]} {
    %cst = arith.constant dense<[1, 2, 3, 4]> : tensor<4xi64>
    %cst_0 = arith.constant dense<["a", "b", "c", "d"]> : tensor<4x!tf_type.string>

  // CHECK-LABEL: init_all_tables
  func.func @init_all_tables()
  attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer"]} {
    %cst = arith.constant dense<[1, 2, 3, 4]> : tensor<4xi64>
    %cst_0 = arith.constant dense<["a", "b", "c", "d"]> : tensor<4x!tf_type.string>

// CHECK-LABEL: broadcast_to_to_reshape_i64
func.func @broadcast_to_to_reshape_i64(%arg0: tensor<4x4x4xf32>, %arg1 : tensor<4xi64>) -> tensor<1x4x4x4xf32> {
  %0 = "tfl.broadcast_to"(%arg0, %arg1) : (tensor<4x4x4xf32>, tensor<4xi64>) -> tensor<1x4x4x4xf32>
  // CHECK: "tfl.cast"
  // CHECK-SAME: (tensor<4xi64>) -> tensor<4xi32>
  // CHECK-NEXT: "tfl.reshape"
  // CHECK-SAME: (tensor<4x4x4xf32>, tensor<4xi32>) -> tensor<1x4x4x4xf32>

  func.return %2 : tensor<?x?x?x?xf32>

// CHECK-DAG: %[[CST:.*]] = arith.constant dense<0> : tensor<4xi64>
// CHECK-DAG: %[[CST0:.*]] = arith.constant dense<[1, 9, 23, 768]> : tensor<4xi64>
// CHECK-DAG: %[[CST1:.*]] = arith.constant dense<1> : tensor<4xi64>

func.return %0 : tensor<2x?x2x4xf32>

// CHECK-LABEL:     convert_dot_general_dynamic_batch_dim
// CHECK:           %0 = "tfl.pseudo_const"() <{value = dense<[0, 1, 3, 2]> : tensor<4xi64>}> : () -> tensor<4xi64>
// CHECK-NEXT:      %1 = "tfl.cast"(%0) : (tensor<4xi64>) -> tensor<4xi32>
// CHECK-NEXT:      %2 = "tfl.transpose"(%arg1, %1) : (tensor<2x?x4x3xf32>, tensor<4xi32>) -> tensor<2x?x3x4xf32>