rewriter->create<TFL::ConstOp>(split_op->getLoc(), slice_begin_attr);
    auto slice_size_const =
        rewriter->create<TFL::ConstOp>(split_op->getLoc(), slice_size_attr);

    auto slice_op = rewriter->create<TFL::SliceOp>(
        split_op->getLoc(), current_output_type, input, slice_begin_const,
        slice_size_const);

    // Rewire output.
    slice_outputs.push_back(slice_op.getResult());
  }
  return slice_outputs;

    return rewriter.notifyMatchFailure(
        concat, "Concatenate op should have at least two operands");

  auto first = concat.getVal()[0].getDefiningOp<mhlo::SliceOp>();
  auto second = concat.getVal()[1].getDefiningOp<mhlo::SliceOp>();
  if (!first || !second)
    return rewriter.notifyMatchFailure(concat, "operands are not slice ops");
  if (first.getOperand() != second.getOperand())

        TypeID::get<TF::SelfAdjointEigV2Op>(),
        TypeID::get<TF::SeluGradOp>(),
        TypeID::get<TF::SeluOp>(),
        TypeID::get<TF::SigmoidGradOp>(),
        TypeID::get<TF::SinOp>(),
        TypeID::get<TF::SliceOp>(),
        TypeID::get<TF::SoftplusGradOp>(),
        TypeID::get<TF::SoftsignGradOp>(),
        TypeID::get<TF::SoftsignOp>(),
        TypeID::get<TF::SpaceToBatchNDOp>(),
        TypeID::get<TF::SpaceToBatchOp>(),

	case *ast.SliceExpr:
		WriteExpr(buf, x.X)
		buf.WriteByte('[')
		if x.Low != nil {
			WriteExpr(buf, x.Low)
		}
		buf.WriteByte(':')
		if x.High != nil {
			WriteExpr(buf, x.High)
		}
		if x.Slice3 {
			buf.WriteByte(':')
			if x.Max != nil {
				WriteExpr(buf, x.Max)
			}
		}
		buf.WriteByte(']')

	case *ast.TypeAssertExpr:
		WriteExpr(buf, x.X)
		buf.WriteString(".(")
		WriteExpr(buf, x.Type)

           dnums.getKernelOutputFeatureDimension() == num_spatial_dims;
  }
};

class ConvertSliceOp : public OpConversionPattern<mhlo::SliceOp> {
 public:
  using OpConversionPattern::OpConversionPattern;

  LogicalResult matchAndRewrite(
      mhlo::SliceOp slice_op, OpAdaptor adaptor,
      ConversionPatternRewriter& rewriter) const final {
    auto begin = rewriter.create<TF::ConstOp>(slice_op.getLoc(),

		}
	}
}

func TestUpsertSlice(t *testing.T) {
	langs := []Language{
		{Code: "upsert-slice1", Name: "Upsert-slice1"},
		{Code: "upsert-slice2", Name: "Upsert-slice2"},
		{Code: "upsert-slice3", Name: "Upsert-slice3"},
	}
	DB.Clauses(clause.OnConflict{DoNothing: true}).Create(&langs)

	var langs2 []Language
	if err := DB.Find(&langs2, "code LIKE ?", "upsert-slice%").Error; err != nil {

      loc, input, /*use32Bit=*/builder.getBoolAttr(false));
  Value input_batch_dims = builder.create<TF::SliceOp>(
      loc, RankedTensorType::get({num_input_batch_dim}, builder.getI64Type()),
      input_shape, zero, num_input_batch_dim_value);
  Value input_matmul_dims = builder.create<TF::SliceOp>(
      loc, RankedTensorType::get({num_matmul_dim}, builder.getI64Type()),

	case nil:
		check.errorf(x, NonSliceableOperand, invalidOp+"cannot slice %s: %s has no core type", x, x.typ)
		x.mode = invalid
		return

	case *Basic:
		if isString(u) {
			if e.Slice3 {
				at := e.Max
				if at == nil {
					at = e // e.Index[2] should be present but be careful
				}
				check.error(at, InvalidSliceExpr, invalidOp+"3-index slice of string")
				x.mode = invalid
				return

  std::optional<int32_t> ComputeSliceK(Value value) const {
    if (value.use_empty()) return 0;
    auto slice_op =
        llvm::dyn_cast_or_null<TFL::SliceOp>(value.getUses().begin().getUser());
    // We only match for the case where value is used by SliceOp.
    if (!slice_op) return std::nullopt;
    DenseElementsAttr begin;
    DenseElementsAttr size;
    if (!matchPattern(slice_op->getOperand(1), m_Constant(&begin)) ||

    TF::SliceOp slice1 =
        CreateSliceOpForTensorList(loc, /*input_list=*/input,
                                   /*start_index=*/scalar_zero,
                                   /*size=*/index,
                                   /*item_rank=*/item_position_shape,
                                   /*result_type=*/unranked_tensor, &rewriter);
    TF::SliceOp slice2 =