// RUN: tf_tfl_translate --enable-hlo-to-tf-conversion --input-mlir %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s --check-prefix=CHECK-ROUNDTRIP


module {
  func.func public @main( %arg0: tensor<i64>) ->  tensor<i64> {
    %0 = func.call @test_add_roundtrip(%arg0) : (tensor<i64>) -> tensor<i64>

    return %0 : tensor<i64>
  }


  // CHECK-LABEL: func.func private @test_add_roundtrip

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

func.func @main(%arg0: tensor<3x2xf32>) -> tensor<3x2xi32> {
  // CHECK-LABEL: @main
  // CHECK: "tfl.bucketize"(%arg0) <{boundaries = [0.000000e+00 : f32, 1.000000e+01 : f32, 1.000000e+02 : f32]}> : (tensor<3x2xf32>) -> tensor<3x2xi32>

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Ensure cast with bfloat16 roundtrip exactly

func.func @main(tensor<4x5xbf16>) -> tensor<4x5xbf16> {
^bb0(%arg0: tensor<4x5xbf16>):
  // CHECK-LABEL: @main
  // CHECK:  (tensor<4x5xbf16>) -> tensor<4x5xf32>
  // CHECK-NEXT:  (tensor<4x5xf32>) -> tensor<4x5xbf16>

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Ensure "quantfork.stats" roundtrip exactly

func.func @main(%arg0: tensor<1x512x672x8xf32>) -> tensor<1x512x672x8xf32> {
// CHECK-LABEL: @main
// CHECK: %[[RES0:.*]] = "quantfork.stats"(%arg0) <{layerStats = dense<[0.000000e+00, 2.550000e+02]> : tensor<2xf32>}> : (tensor<1x512x672x8xf32>) -> tensor<1x512x672x8xf32>

// RUN: tf-tfrt-opt -tf-to-tfrt %s | FileCheck %s --dump-input=fail

// CHECK-LABEL: func @device_test
func.func @device_test(
    %arg0: tensor<3x1xf32> {tf_saved_model.index_path = [0]},
    %arg1: tensor<1x3xf32> {tf_saved_model.index_path = [0]})
      -> (tensor<3x3xf32> {tf_saved_model.index_path = []}) {
  // CHECK: {{%.*}} = corert.get_op_handler %arg0 "/device:GPU:0"

// RUN: tf-opt %s -allow-unregistered-dialect --tf-move-tpu-compile-to-front --split-input-file | FileCheck %s

module {

// CHECK-LABEL: does_basic_reordering
func.func @does_basic_reordering() -> () {
   // CHECK: _TPUCompileMlir
   // CHECK-SAME: X
   // CHECK: _TPUCompileMlir
   // CHECK-SAME: Y
   // CHECK: OpA
   // CHECK: OpB
   // CHECK: OpC
   "tf.OpA"() : () -> ()

# RUN:                  -tf-input-min-values='-2,-3' \
# RUN:                  -tf-input-max-values='2,3' \
# RUN:                  --quant-stats=%s.stats \
# RUN:                  %s -o - --output-mlir 2>&1 \
# RUN:  | FileCheck --check-prefix=MLIR %s
# RUN: tf_tfl_translate -tf-input-arrays=input0,input1 \
# RUN:                  -tf-input-shapes=4:4 \
# RUN:                  -tf-input-data-types=DT_FLOAT,DT_FLOAT \

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

# This test is tailored to reproduce b/141617294. In particular, the function
# library contains "foo1", "foo2", ..., "foo20", from which "foo1" and "foo11"
# were mapped to the same name "foo110" in the bug.
node {
  name: "unnamed"
  op: "foo1"
}
node {
  name: "unnamed1"
  op: "foo11"
}
library {
  function {
    signature {

// RUN: flatbuffer_translate -mlir-to-tflite-flatbuffer %s -o - | flatbuffer_translate --tflite-flatbuffer-to-mlir - -o - | FileCheck %s
// Confirm we can extract type info from reshape

func.func @main() -> tensor<2x2xf32> {
  // CHECK: %[[cst:.*]] = "tfl.pseudo_const"() <{value = dense<2> : tensor<2xi32>}> : () -> tensor<2xi32>
  // CHECK: %{{.*}} = "tfl.reshape"(%{{.*}}, %[[cst]]) : (tensor<4xf32>, tensor<2xi32>) -> tensor<2x2xf32>

// RUN: tf-opt -pass-pipeline='builtin.module(func.func(infeed-ops-xla-adjust-layout))' %s | FILECHECK_OPTS="" FileCheck %s

func.func @infeed_dequeue_tuple() -> (tensor<1x8x4x4xi32>, tensor<1x100x1xf32>) {
  // CHECK: [[TOKEN:%.*]] = mhlo.create_token : !mhlo.token
  %0 = "mhlo.create_token"() : () -> !mhlo.token

  // CHECK:               [[INFEED:%.*]]:3 = "mhlo.infeed"([[TOKEN]]) <{
  // CHECK-SAME{LITERAL}:   infeed_config = "", layout = [[1, 3, 2, 0], [1, 2, 0]]