// check op and versioning.
  EXPECT_THAT(model_.operator_codes, SizeIs(2));
  EXPECT_THAT(GetBuiltinCode(model_.operator_codes[0].get()),
              Eq(BuiltinOperator_ADD));
  ASSERT_THAT(model_.operator_codes[0]->version, Eq(2));
  EXPECT_THAT(GetBuiltinCode(model_.operator_codes[1].get()),
              Eq(BuiltinOperator_RESHAPE));
  ASSERT_THAT(model_.operator_codes[1]->version, Eq(1));
}

// CHECK: #[[LOC1:.*]] = loc("output0"(#[[LOC0]]))
// CHECK: #[[LOC2:.*]] = loc("output1"(#[[LOC0]]))
// CHECK: #[[SPLIT_LOC]] = loc(fused[#[[LOC1]], #[[LOC2]]])

{
  "version": 3,
  "operator_codes": [
    {
      "builtin_code": "SPLIT"
    }
  ],
  "subgraphs": [
    {
      "tensors": [
        {
          "shape": [
            1
          ],
          "name": "split_dim",

  func.return %0 : tensor<!tf_type.variant<tensor<*xi32>>>
}

// CHECK:   operator_codes: [ {
// CHECK:       custom_code: "TensorListReserve",
// CHECK:       builtin_code: CUSTOM

// CHECK:         shape: [  ],
// CHECK:         type: VARIANT,
// CHECK:         name: "tfl.custom",

// 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: "HashTableV2",
// CHECK:    builtin_code: CUSTOM
// CHECK: } ],
// CHECK: subgraphs: [ {
// CHECK:   tensors: [ {
// CHECK:     shape: [  ],

func.func @main() -> tensor<4xi4> {
  // CHECK: {
  // CHECK:   version: 3,
  // CHECK:   operator_codes: [  ],
  // CHECK:   subgraphs: [ {
  // CHECK:     tensors: [ {
  // CHECK:       shape: [ 4 ],
  // CHECK:       type: INT4,
  // CHECK:       buffer: 1,
  // CHECK:       name: "Const",

// CHECK: return %[[RES0]] : tensor<256x32x32x16xf32>

{
  "version": 3,
  "operator_codes": [
    {
      "builtin_code": "CONV_2D"
    }
  ],
  "subgraphs": [
    {
      "tensors": [
        {
          "shape": [
            256,
            32,
            32,
            3

// 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:  subgraphs: [ {
// CHECK-NEXT:    tensors: [ {
// CHECK-NEXT:      shape: [  ],
// CHECK-NEXT:      type: VARIANT,
// CHECK-NEXT:      buffer: 1,
// CHECK-NEXT:      name: "arg0",
// CHECK-NEXT:      quantization: {
// CHECK-EMPTY:

  func.return %0 : tensor<3x2xi32>
}

// CHECK:      {
// CHECK-NEXT:     version: 3,
// CHECK-NEXT:     operator_codes: [ ],
// CHECK-NEXT:     subgraphs: [ {
// CHECK-NEXT:       tensors: [ {
// CHECK-NEXT:         shape: [ 3, 2 ],
// CHECK-NEXT:         type: INT32,
// CHECK-NEXT:         name: "variable",

      for (size_t i = 0; i < op->outputs()->size(); ++i) {
        if (op->outputs()->Get(i) == tensor_idx) {
          const uint32_t op_code_idx = op->opcode_index();
          *op_code = GetBuiltinCode(model->operator_codes()->Get(op_code_idx));
          return true;
        }
      }
    }
    return false;
  }
};

// Returns true if everything between the two graphs
// are identical except for name field.

// 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:  subgraphs: [ {
// CHECK-NEXT:    tensors: [ {
// CHECK-NEXT:      shape: [ 5 ],
// CHECK-NEXT:      buffer: 1,
// CHECK-NEXT:      name: "StatefulPartitionedCall:1",
// CHECK-NEXT:      quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:      },