// RUN: odml-to-stablehlo-opt %s -tfl-parse-stablehlo-ops | FileCheck %s

module {
func.func @main(%arg0: tensor<2xi32>) -> tensor<2xi32> attributes {tf.entry_function = {inputs = "arg0", outputs = "tfl.custom1"}} {
  %0 = "tfl.custom"(%arg0, %arg0) {custom_code = "stablehlo.add", custom_option = #tfl<const_bytes : "0x00000100002401">} : (tensor<2xi32>, tensor<2xi32>) -> tensor<2xi32>
  func.return %0 : tensor<2xi32>
}
}

// CHECK:       module {

// RUN: odml-to-stablehlo-opt %s -tfl-parse-stablehlo-ops | FileCheck %s

module {
func.func @main(%arg0: tensor<2xi32>, %arg1: tensor<2xi32>, %arg2: tensor<2xi32>) -> tensor<2xi32> {
  %0 = "tfl.custom"(%arg0, %arg1, %arg2) {custom_code = "stablehlo.clamp", custom_option = #tfl<const_bytes : "0x00000100002401">} : (tensor<2xi32>, tensor<2xi32>, tensor<2xi32>) -> tensor<2xi32>
  func.return %0 : tensor<2xi32>
}
}

// CHECK:       module {

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

// CHECK: op: "Split"
// CHECK: attr {
// CHECK:   key: "num_split"
// CHECK:   value {
// CHECK:     i: 2
// CHECK:   }
// CHECK: }

func.func @main() {
  tf_executor.graph {
    %dim:2 = tf_executor.island wraps "tf.Const"() {dtype = "tftype$DT_INT32", value = dense<0> : tensor<i32>} : () -> tensor<i32>

# RUN: tf-mlir-translate -graphdef-to-mlir -tf-enable-shape-inference-on-import=false %s -tf-graph-as-function -o - | FileCheck %s

node {
  name: "arg"
  op: "_Arg"
  attr {
    key: "T"
    value {
      type: DT_INT32
    }
  }
  attr {
    key: "index"
    value {
      i: 0
    }
  }
}
node {
  name: "ret"
  op: "_Retval"
  input: "arg"
  attr {
    key: "T"
    value {
      type: DT_INT32

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Ensure basic_lstm roundtrip exactly

func.func @main(%arg0: tensor<1x384xf32>, %arg1: tensor<1x96xf32>, %arg2: tensor<384x480xf32>, %arg3: tensor<384xf32>, %arg4: tensor<1x96xf32>) -> tensor<1x96xf32> {
// CHECK-LABEL: @main

// RUN: odml-to-stablehlo-opt %s -tfl-parse-stablehlo-ops | FileCheck -dump-input always %s

module {
  func.func @main(%arg0: tensor<8x8x1x207xf32>, %arg1: tensor<3x3x16x207xf32>) -> tensor<16x8x8x1xf32> {

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

// CHECK: error: 'tf.MyCustomOp' op is neither a custom op nor a flex op
// CHECK: error: failed while converting: 'main'
// CHECK: Some ops in the model are custom ops, See instructions to implement
// CHECK: tf.MyCustomOp(tensor<4xf32>, tensor<4xf32>) -> (tensor<4xf32>, tensor<3xf32>) : {name = "MyCustomOp"}

func.func @main(tensor<4xf32>) -> tensor<4xf32> {

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -emit-custom-ops -emit-builtin-tflite-ops=false -o - | flatbuffer_to_string - | FileCheck %s

// CHECK: {
// CHECK:   version: 3,
// CHECK:   operator_codes: [ {
// CHECK:     deprecated_builtin_code: 32,
// CHECK:     custom_code: "SomeOperation",
// CHECK:     builtin_code: CUSTOM
// CHECK:   } ],
// CHECK:   subgraphs: [ {
// CHECK:     tensors: [ {
// CHECK:       shape: [  ],

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir --use-external-constant - -o - | FileCheck %s
// Ensure that `tfl.external_const` is imported when the flag `-use-external-constant` is enabled.

func.func @main(tensor<40x37xf32>, tensor<40x37xf32>) -> tensor<40x40xf32> {
^bb0(%arg0: tensor<40x37xf32>, %arg1: tensor<40x37xf32>):
  %cst = arith.constant dense<1.0> : tensor<40xf32>

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_to_string - | FileCheck %s
// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - -strip-debug-info | flatbuffer_to_string - | FileCheck %s --check-prefix=STRIP

func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32>
  attributes {tf.entry_function = {inputs = "input", outputs = "SameNameAsOutput"}} {
^bb0(%arg0: tensor<3x2xi32>):
// CHECK: {
// CHECK-NEXT:   version: 3,