// Confirm output-arrays works.

func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
  %0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")

    %4 = stablehlo.select %2, %3, %arg2 : tensor<100xi1>, tensor<100xi64>
    %5 = stablehlo.reshape %4 : (tensor<100xi64>) -> tensor<100x1xi64>
    %6 = "stablehlo.scatter"(%arg0, %5, %arg3) ({
    ^bb0(%arg5: tensor<f32>, %arg6: tensor<f32>):
      stablehlo.return %arg6 : tensor<f32>

// Confirm float constants and operators survive a roundtrip

func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
  // CHECK:      [[CONST:%.*]] = "tfl.pseudo_const"() <{value = dense<1.000000e+00> : tensor<4xf32>}> : () -> tensor<4xf32>
  // CHECK-NEXT: [[SQDIFF:%.*]] = tfl.squared_difference %arg0, [[CONST]] : tensor<4xf32>

# CHECK: attributes {tf.entry_function = {control_outputs = "", inputs = "input0,input1", outputs = "output"}} {
# CHECK-NEXT: %[[CUSTOM:.*]] = "tfl.custom_tf"(%arg0, %arg1) ({
# CHECK-NEXT: ^bb0(%arg2: tensor<4xi32>, %arg3: tensor<4xi32>):
# CHECK-NEXT:   %[[OUTPUTS:.*]] = "tf.BannaPotatoSaladWithColeslaw"(%arg2, %arg3) {T = i32, device = ""} : (tensor<4xi32>, tensor<4xi32>) -> tensor<*xi32>

// Confirm graph pruning.

func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
  %0 = "tfl.pseudo_const" () {value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32> loc("Const")

  // CHECK: [[WHILE:%.*]]:2 = mhlo.while
  %0 = "mhlo.while"(%arg0) ({
  ^bb0(%arg1: tensor<f32>):
    "tf.XlaSendToHost"(%arg1) {key = "send_key0"} : (tensor<f32>) -> ()
    %1 = "mhlo.compare"(%arg1, %arg1) {comparison_direction = #mhlo<comparison_direction LT>} : (tensor<f32>, tensor<f32>) -> tensor<i1>
    "mhlo.return"(%1) : (tensor<i1>) -> ()
  },  {
  ^bb0(%arg1: tensor<f32>):
    "mhlo.return"(%arg1) : (tensor<f32>) -> ()

// CHECK: Some ops are not supported by the native TFLite runtime
// CHECK: tf.Div(tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>) : {name = "div"}

func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
  %0 = "tfl.pseudo_const" () {name = "Const", value = dense<1.0> : tensor<4xf32>} : () -> tensor<4xf32>

  func.return %1 : tensor<2x100xf32>
}

// -----

func.func @testConv2DCPU(tensor<256x32x32x3xf32>, tensor<16x3x3x3xf32>, tensor<16xf32>) -> tensor<256x32x32x16xf32> {
^bb0(%arg0: tensor<256x32x32x3xf32>, %arg1: tensor<16x3x3x3xf32>, %arg2: tensor<16xf32>):
  // CHECK: tac.cost = 0x4D5C0000

// Check a few basic properties of the import-export,
// including constants retaining their shape
// and the module including the TFLite version.

func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32> {
^bb0(%arg0: tensor<3x2xi32>):
  // CHECK: module attributes
  // CHECK-SAME: tfl.description = "MLIR Converted."
  // CHECK-SAME: tfl.schema_version = 3 : i32

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s

func.func @main(tensor<1x6x6x16xf32>) -> tensor<1x1x1x16xf32> {
^bb0(%arg0: tensor<1x6x6x16xf32>):
  // CHECK:      {
  // CHECK-NEXT:   version: 3,
  // CHECK-NEXT:   operator_codes: [ {
  // CHECK-NEXT:     deprecated_builtin_code: 1,
  // CHECK-NEXT:     version: 1,
  // CHECK-NEXT:     builtin_code: AVERAGE_POOL_2D
  // CHECK-NEXT:   } ],