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

func.func @main(tensor<1x224x224x3xf32>) -> tensor<1x112x112x32xf32> {
^bb0(%arg0: tensor<1x224x224x3xf32>):
  // CHECK:      {
  // CHECK-NEXT:  version: 3,
  // CHECK-NEXT:  operator_codes: [ {
  // CHECK-NEXT:    deprecated_builtin_code: 6,
  // CHECK-NEXT:    version: 1,
  // CHECK-NEXT:    builtin_code: DEQUANTIZE
  // CHECK-NEXT:  }, {

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-select-tf-ops -o - | flatbuffer_to_string - | FileCheck %s

func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
// CHECK:  {
// CHECK-NEXT:  version: 3,
// CHECK-NEXT:  operator_codes: [ {
// CHECK-NEXT:    deprecated_builtin_code: 18,
// CHECK-NEXT:    version: 1,
// CHECK-NEXT:    builtin_code: MUL
// CHECK-NEXT:  }, {
// CHECK-NEXT:    deprecated_builtin_code: 32,

// RUN: tf-quant-opt %s -mark-functions-noinline='noinline-functions=noinline0' \
// RUN:     -allow-unregistered-dialect -mlir-disable-threading \
// RUN:     -split-input-file -verify-diagnostics | FileCheck %s

// Tests that the function is marked tf._noinline = true.

// CHECK-LABEL: @noinline0
// CHECK-SAME: attributes {{{.*tf._noinline = true.*}}}
func.func @noinline0() -> (tensor<0xf32>) {

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

module attributes {
  tfl.metadata = {key1 = "value1", key2 = "value2"}
} {
  func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32>
    attributes {tf.entry_function = {inputs = "input", outputs = "SameNameAsOutput"}} {
  ^bb0(%arg0: tensor<3x2xi32>):
    %0 = "tfl.pseudo_const" () {value = dense<[[1, 2], [3, 4], [5, 6]]> : tensor<3x2xi32>} : () -> tensor<3x2xi32>

// 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, 384 ],

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

// CHECK-LABEL: main
func.func @main(%arg0: tensor<1x224x224x3xf32>) -> tensor<1x401408xf32> {
// CHECK:   %{{.*}} = "tfl.quantize"(%{{.*}}) <{qtype = tensor<1x224x224x3x!quant.uniform<u8:f32, 7.812500e-03:128>>}> : (tensor<1x224x224x3xf32>) -> tensor<1x224x224x3x!quant.uniform<u8:f32, 7.812500e-03:128>>

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

func.func @main(tensor<4xf32>) -> tensor<4xf32> {
^bb0(%arg0: tensor<4xf32>):
  // CHECK:      {
  // CHECK-NEXT:   version: 3,
  // CHECK-NEXT:   operator_codes: [ {
  // CHECK-NEXT:     deprecated_builtin_code: 99,
  // CHECK-NEXT:     version: 1,
  // CHECK-NEXT:     builtin_code: SQUARED_DIFFERENCE
  // CHECK-NEXT:   }, {

// RUN: not flatbuffer_translate -mlir-to-tflite-flatbuffer %s 2>&1 | FileCheck %s

// CHECK: error: 'tf.Div' op is neither a custom op nor a flex op
// CHECK: error: failed while converting: 'main'
// 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>):

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer --use-buffer-offset %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// 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>
}

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