//CHECK-NEXT: return %0 : tensor<4x32x256xf32>
//CHECK-NEXT:}

func.func @slice(%arg0: tensor<160x20x1xf32>) -> tensor<1x1x1xf32> {
  %0 = "vhlo.slice_v1"(%arg0) <{limit_indices = #vhlo.tensor_v1<dense<[0, 0, 0]> : tensor<3xi64>>, 
                                start_indices = #vhlo.tensor_v1<dense<[1, 1, 1]> : tensor<3xi64>>,

	return s[0]
}

func slice10() []*int {
	i := 0          // ERROR "moved to heap: i"
	s := []*int{&i} // ERROR "\[\]\*int{...} escapes to heap"
	return s
}

func slice11() {
	i := 2
	s := make([]int, 2, 3) // ERROR "make\(\[\]int, 2, 3\) does not escape"
	s = make([]int, i, 3)  // ERROR "make\(\[\]int, i, 3\) does not escape"

      slice_op.getLoc(), new_output_type, reshape_op, new_begin, new_size);

  // Append a reshape at the bottom.
  auto output_reshape_op = InsertReshapeOp(slice_op.getLoc(), new_slice,
                                           output_type.getElementType(),
                                           output_type.getShape(), &rewriter);
  rewriter.replaceOp(slice_op, output_reshape_op.getResult());

	cache := newEndpointSliceCache()
	hostname := host.Name("foo")

	// add a endpoint
	ep1 := &model.IstioEndpoint{
		Address:         "1.2.3.4",
		ServicePortName: "http",
	}
	cache.Update(hostname, "slice1", []*model.IstioEndpoint{ep1})
	if !testEndpointsEqual(cache.Get(hostname), []*model.IstioEndpoint{ep1}) {
		t.Fatalf("unexpected endpoints")
	}
	if !cache.Has(hostname) {
		t.Fatalf("expect to find the host name")
	}

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

	createEndpointSlice(t, s.KubeClient().Kube(), "slice1", "service", namespace, []v1.EndpointPort{{Name: "http", Port: 80}}, []string{"1.2.3.4"})
	expectEndpoints(t, s, "outbound|80||service.namespace.svc.cluster.local", []string{"1.2.3.4:80"}, nil)

	// create an FQDN endpoint that should be ignored
	createEndpointSliceWithType(t, s.KubeClient().Kube(), "slice1", "service",

  collapsed_dims.insert(dimension_numbers.collapsed_slice_dims().begin(),
                        dimension_numbers.collapsed_slice_dims().end());

  // Slice operand by constructed start_indices and slice_sizes.
  auto slice_op = builder.create<TF::SliceOp>(
      loc, GetSliceOpOutputType(output.getType(), collapsed_dims), operand,
      /*start_indices=*/scattered_start_indices,
      /*slice_sizes=*/
      builder.create<TF::CastOp>(

func TestSortFloat64sCompareSlicesSort(t *testing.T) {
	slice1 := slices.Clone(float64s[:])
	slice2 := slices.Clone(float64s[:])

	Sort(Float64Slice(slice1))
	slices.Sort(slice2)

	// Compare for equality using cmp.Compare, which considers NaNs equal.
	if !slices.EqualFunc(slice1, slice2, func(a, b float64) bool { return cmp.Compare(a, b) == 0 }) {

// CHECK:  [[SLICE_1:%.*]] = "tf.Slice"([[INPUT]], [[START_POS_1]], [[SLICE_SIZE_1]]) : (tensor<3x10xf32>, tensor<?xi32>, tensor<?xi32>) -> tensor<*xf32>


// CHECK:  [[EXPANDED_ITEM:%.*]] = "tf.ExpandDims"([[ITEM]], [[ZERO]]) : (tensor<10xf32>, tensor<i32>) -> tensor<*xf32>

  // All masks are `0` except `shrink_axis_mask` which is equal to `1` (slicing
  // scalar value from input vector).
  if (slice_op.getBeginMask() != 0 || slice_op.getEllipsisMask() != 0 ||
      slice_op.getEndMask() != 0 || slice_op.getNewAxisMask() != 0 ||
      slice_op.getShrinkAxisMask() != 1)
    return {};

  // Returns a value if the `value` is defined by a ConstOp with a single