BL	(R4)

	// Create a new thread to do the runtime initialization and return.
	MOVD	_cgo_sys_thread_create(SB), R4
	CBZ	R4, nocgo
	MOVD	$_rt0_arm64_openbsd_lib_go(SB), R0
	MOVD	$0, R1
	SUB	$16, RSP		// reserve 16 bytes for sp-8 where fp may be saved.
	BL	(R4)
	ADD	$16, RSP
	B	restore

nocgo:
	MOVD	$0x800000, R0                     // stacksize = 8192KB
	MOVD	$_rt0_arm64_openbsd_lib_go(SB), R1
	MOVD	R0, 8(RSP)

}

inline Status AbstractOperation::SetAttrStringList(
    const char* attr_name, absl::Span<string const> values) {
  std::vector<const char*> raw_strs;
  std::vector<size_t> lengths;
  raw_strs.reserve(values.size());
  lengths.reserve(values.size());
  for (const auto& s : values) {
    raw_strs.emplace_back(s.data());
    lengths.emplace_back(s.size());
  }
  return SetAttrStringList(attr_name,

                                  const std::set<int>* variables_updated,
                                  std::vector<VariableInfo>* result) {
  result->clear();
  result->reserve(variable_indices.size());
  for (int var_idx : variable_indices) {
    Var* variable = nullptr;
    if (inputs[var_idx]->NumElements() == 0) {
      return errors::InvalidArgument("Empty resource tensor passed  at index ",

	MOVD	_cgo_sys_thread_create(SB), R4
	CBZ	R4, nocgo
	MOVD	$_rt0_arm64_freebsd_lib_go(SB), R0
	MOVD	$0, R1
	SUB	$16, RSP	// reserve 16 bytes for sp-8 where fp may be saved.
	BL	(R4)
	ADD	$16, RSP
	B	restore

nocgo:
	MOVD	$0x800000, R0                     // stacksize = 8192KB
	MOVD	$_rt0_arm64_freebsd_lib_go(SB), R1
	MOVD	R0, 8(RSP)
	MOVD	R1, 16(RSP)
	MOVD	$runtime·newosproc0(SB),R4

                                         tensorflow::Status* status) {
  std::vector<int64_t> shape;
  int rank = -1;
  *status = handle.NumDims(&rank);
  if (!status->ok()) {
    return shape;
  }
  shape.reserve(rank);
  for (int i = 0; i < rank; ++i) {
    int64_t dim;
    *status = handle.Dim(i, &dim);
    if (!status->ok()) {
      return shape;
    }
    shape.push_back(dim);
  }
  return shape;
}

  if (!session) return module.emitOpError() << "no session provided";

  // Read all resource variables from the session.
  std::vector<std::string> variable_names;
  variable_names.reserve(resource_names.size());
  for (StringRef name : resource_names) variable_names.push_back(name.str());

  std::vector<Tensor> resource_tensors;
  Status status = session->Run(
      /*inputs=*/{}, variable_names,

struct Stats {
  std::vector<int64_t> per_iter_us;  // Per-iteration deltas in us.
  int64_t total_us;                  // Total time in us.

  Stats() : total_us(0) { per_iter_us.reserve(5000); }
};

// DumpStatsToStdout printfs to stdout stats in a multi-line human-friendly
// form.
void DumpStatsToStdout(const Stats& stats);

// BenchmarkFn is the signature of the function generated by tfcompile.

					return tmpPl, nil
				}); err != nil {
					t.Fatalf("Unable to register pre bind plugins: %s", pl.name)
				}

				configPlugins.Reserve.Enabled = append(
					configPlugins.Reserve.Enabled,
					config.Plugin{Name: pl.name},
				)
			}
			profile := config.KubeSchedulerProfile{Plugins: configPlugins}
			ctx, cancel := context.WithCancel(context.Background())

  // compilation.
  std::vector<tensorflow::XlaExpression> expressions;
  std::vector<tensorflow::Tensor> tensors;
  std::vector<tensorflow::TensorValue> inputs;
  expressions.reserve(op_->getNumOperands());
  tensors.reserve(op_->getNumOperands());
  inputs.reserve(op_->getNumOperands());

  if (failed(
          PrepareKernelInputs(required_consts, expressions, tensors, inputs)))
    return failure();

  params_.inputs = inputs;

    }
    if (argument.HasDefaultValue()) {
      args_with_default_val.push_back(text);
    } else {
      args_without_default_val.push_back(text);
    }
  }
  std::vector<string> arguments;
  arguments.reserve(args_without_default_val.size() +
                    args_with_default_val.size());
  arguments.insert(arguments.end(),
                   std::make_move_iterator(args_without_default_val.begin()),