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

func.func @main(tensor<40x37xf32>, tensor<40x37xf32>) -> tensor<40x40xf32> {
^bb0(%arg0: tensor<40x37xf32>, %arg1: tensor<40x37xf32>):
  // CHECK:      {
  // CHECK-NEXT:  version: 3,
  // CHECK-NEXT:  operator_codes: [ {
  // CHECK-NEXT:    deprecated_builtin_code: 9,
  // CHECK-NEXT:    version: 1,
  // CHECK-NEXT:    builtin_code: FULLY_CONNECTED

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

func.func @main(tensor<40x37xf32>, tensor<40x37xf32>) -> tensor<40x40xf32> {
^bb0(%arg0: tensor<40x37xf32>, %arg1: tensor<40x37xf32>):
  // CHECK:      {
  // CHECK-NEXT:  version: 3,
  // CHECK-NEXT:  operator_codes: [ {
  // CHECK-NEXT:    deprecated_builtin_code: 9,
  // CHECK-NEXT:    version: 2,
  // CHECK-NEXT:    builtin_code: FULLY_CONNECTED

// RUN: tf-opt %s --tf-print | FileCheck %s

module {
// Smoke test. We don't expect any modifications of the MLIR.

// CHECK-LABEL: foo
// CHECK: return
func.func @foo(%arg0: tensor<f32>, %arg1: tensor<f32>) -> tensor<f32> {
  return %arg0 : tensor<f32>
}

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

// CHECK: {
// CHECK-NEXT:   version: 3,
// CHECK-NEXT:   operator_codes: [ {
// CHECK-NEXT:     deprecated_builtin_code: 119,
// CHECK-NEXT:     version: 1,
// CHECK-NEXT:     builtin_code: WHILE
// CHECK-NEXT:   }, {
// CHECK-NEXT:     deprecated_builtin_code: 61,
// CHECK-NEXT:     version: 1,
// CHECK-NEXT:     builtin_code: GREATER

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

// CHECK: {
// CHECK-NEXT:  version: 3,
// CHECK-NEXT:  operator_codes: [ {
// CHECK-NEXT:    deprecated_builtin_code: 9,
// CHECK-NEXT:    version: 1,
// CHECK-NEXT:    builtin_code: FULLY_CONNECTED
// CHECK-NEXT:  } ],
// CHECK-NEXT:  subgraphs: [ {
// CHECK-NEXT:    tensors: [ {
// CHECK-NEXT:      shape: [ 1, 3 ],
// CHECK-NEXT:      buffer: 1,

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

func.func @main(%arg0: tensor<40x37xf32>, %arg1: tensor<40x37xf32>) -> tensor<40x40xf32> {
  %0 = "tfl.no_value"() {value = unit} : () -> none
  %1:2 = "tfl.fully_connected"(%arg0, %arg1, %0) {fused_activation_function = "NONE", keep_num_dims = false, weights_format = "DEFAULT"} : (tensor<40x37xf32>, tensor<40x37xf32>, none) -> (tensor<40x40xf32>, tensor<40x40xf32>)

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

func.func @main(%arg0: tensor<i32>, %arg1: tensor<i32>) -> tensor<!tf_type.variant<tensor<*xi32>>> {
  %0 = "tfl.custom"(%arg0, %arg1) {custom_code = "TensorListReserve", custom_option = #tfl<const_bytes : "0x02">} : (tensor<i32>, tensor<i32>) -> tensor<!tf_type.variant<tensor<*xi32>>>
  func.return %0 : tensor<!tf_type.variant<tensor<*xi32>>>
}

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

// We need a "main" function, or the flatbuffer exporter won't export anything.
// CHECK-LABEL: @main
func.func @main(%arg0: tensor<1xf32>) -> tensor<1xf32> {
  func.return %arg0: tensor<1xf32>
}
// CHECK-NEXT: return

// CHECK-LABEL: @unneeded_control_node_gets_deleted

// RUN: tf-mlir-translate -mlir-to-graphdef %s -o - | FileCheck %s

module attributes {tf.versions = {bad_consumers = [], min_consumer = 0 : i32, producer = 175 : i32}} {
  func.func @main(%arg0: tensor<32x!tf_type.string>) -> (tensor<?x2xi64>) attributes {tf.entry_function = {inputs = "input0", outputs = "ParseExample/ParseExampleV2"}} {

    %0 = tf_executor.graph {

// RUN: not flatbuffer_translate -mlir-to-tflite-flatbuffer -emit-builtin-tflite-ops=false %s 2>&1 | FileCheck %s

// CHECK: 'tfl.add' op is a TFLite builtin op but builtin emission is not enabled

func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32> {
^bb0(%arg0: tensor<3x2xi32>):
  %0 = "arith.constant"() {name = "Const2", value = dense<10> : tensor<i32>} : () -> tensor<i32>