first *sudog
	last  *sudog
}

//go:linkname reflect_makechan reflect.makechan
func reflect_makechan(t *chantype, size int) *hchan {
	return makechan(t, size)
}

func makechan64(t *chantype, size int64) *hchan {
	if int64(int(size)) != size {
		panic(plainError("makechan: size out of range"))
	}

	return makechan(t, int(size))
}

func makechan(t *chantype, size int) *hchan {
	elem := t.Elem

	// The case of size overflow when converting TUINT or TUINTPTR to TINT
	// will be handled by the negative range checks in makechan during runtime.
	if size.Type().IsKind(types.TIDEAL) || size.Type().Size() <= types.Types[types.TUINT].Size() {
		fnname = "makechan"
		argtype = types.Types[types.TINT]
	}

func mapiternext(hiter *any)
func mapclear(mapType *byte, hmap map[any]any)

// *byte is really *runtime.Type
func makechan64(chanType *byte, size int64) (hchan chan any)
func makechan(chanType *byte, size int) (hchan chan any)
func chanrecv1(hchan <-chan any, elem *any)
func chanrecv2(hchan <-chan any, elem *any) bool
func chansend1(hchan chan<- any, elem *any)
func closechan(hchan chan<- any)

	{"mapdelete_fast32", funcTag, 92},
	{"mapdelete_fast64", funcTag, 93},
	{"mapdelete_faststr", funcTag, 94},
	{"mapiternext", funcTag, 95},
	{"mapclear", funcTag, 96},
	{"makechan64", funcTag, 98},
	{"makechan", funcTag, 99},
	{"chanrecv1", funcTag, 101},
	{"chanrecv2", funcTag, 102},
	{"chansend1", funcTag, 104},
	{"closechan", funcTag, 105},
	{"chanlen", funcTag, 106},
	{"chancap", funcTag, 106},

		if n.Y.Op() != ir.OLITERAL || constant.Sign(n.Y.Val()) == 0 {
			return true
		}

	// Only possible side effect is panic on invalid size,
	// but many makechan and makemap use size zero, which is definitely OK.
	case ir.OMAKECHAN, ir.OMAKEMAP:
		n := n.(*ir.MakeExpr)
		if !ir.IsConst(n.Len, constant.Int) || constant.Sign(n.Len.Val()) != 0 {
			return true
		}

      GatherVariableInfo(ctx, *result, 0);
  TF_RETURN_IF_ERROR(variable_infos.status());
  TF_RETURN_IF_ERROR(LockVariables(absl::MakeSpan(*variable_infos)));
  TF_RETURN_IF_ERROR(launch_context.PopulateOutputs(
      ctx, result, execution_output.ConsumeResult(),
      /*missing_ctx_input_prefix=*/0, absl::MakeSpan(*variable_infos),
      input_output_alias, snapshot_ptrs));
  return absl::OkStatus();
}

  OP_REQUIRES_OK(ctx, variable_infos.status());
  OP_REQUIRES_OK(ctx, LockVariables(absl::MakeSpan(*variable_infos)));
  OP_REQUIRES_OK(
      ctx,
      launch_context.PopulateOutputs(
          ctx, closure.compilation_result(), execution_output->ConsumeResult(),
          /*missing_ctx_input_prefix=*/closure.num_constant_args(),
          absl::MakeSpan(*variable_infos), input_output_alias, snapshot_ptrs));
}

	}
	if len(pods) == 0 {
		return nil, ControlPlaneNotFoundError{istioNamespace}
	}

	responses := []*discovery.DiscoveryResponse{}
	xdsOpts := clioptions.CentralControlPlaneOptions{
		XDSSAN:  makeSan(istioNamespace, kubeClient.Revision()),
		CertDir: centralOpts.CertDir,
		Timeout: centralOpts.Timeout,
	}
	dialOpts, err := xds.DialOptions(xdsOpts, istioNamespace, tokenServiceAccount, kubeClient)
	if err != nil {

    std::vector<AbstractTensorHandle*> outputs(2);
    status_ =
        RunModel(MatMulGradModel, immediate_execution_ctx_.get(),
                 {A.get(), B.get()}, absl::MakeSpan(outputs), UseFunction());
    ASSERT_EQ(errors::OK, status_.code()) << status_.message();
    ASSERT_NO_FATAL_FAILURE(CheckTensorValue(outputs[0], dA_vals[i],
                                             /*dims*/ {3, 3},

  TF_ASSERT_OK_AND_ASSIGN(std::vector<int> constant_input_indices,
                          GetConstantInputIndicesFromContext(context_.get()));
  TF_ASSERT_OK(LockVariables(absl::MakeSpan(variables)));
  TF_ASSERT_OK_AND_ASSIGN(
      std::vector<XlaCompiler::Argument> args,
      XlaComputationLaunchContext::BuildXlaCompilerArguments(
          constant_input_indices, inputs, variables,