size and high performance (among the core value proposition of
TensorFlow Lite models).
- The Export pass writes out TensorFlow Lite FlatBuffer format. This pass
operates on MLIR TensorFlow Lite dialect and is simple/direct translation.

See
https://github.com/tensorflow/tensorflow/blob/master/tensorflow/compiler/mlir/lite/tf_tfl_passes.cc

 * as any other object serialized into the Configuration Cache.</p>
 *
 * @param <T> The type of object the action operates on.
 * @since 8.8
 */
@HasImplicitReceiver
@Incubating
public interface IsolatedAction<T> extends Serializable {
    /**
     * Performs this action against the given object.
     *

};

}  // namespace

void CreateTFStandardPipeline(OpPassManager &pm,
                              const StandardPipelineOptions &options) {
  OpPassManager &func_pm = pm.nest<func::FuncOp>();

  // First operates on the executor dialect:
  // - remove dead islands.
  // - fuse islands as much as possible.
  // - materialize the eventual "pass-through" ops by inlining their content.

// and Next. Advance is called to try and advance an event and
// add completed events to the ordering. Next is used to pick
// off events in the ordering.
type ordering struct {
	gStates     map[GoID]*gState
	pStates     map[ProcID]*pState // TODO: The keys are dense, so this can be a slice.
	mStates     map[ThreadID]*mState
	activeTasks map[TaskID]taskState
	gcSeq       uint64
	gcState     gcState
	initialGen  uint64

      cpuUsage:
        self.query(
          'Container ({{pod}})',
          |||
            sum by (pod) (
              irate(
                container_cpu_usage_seconds_total{%(containerLabels)s}
              [$__rate_interval])
            )
          |||
        ),

      memUsage:
        self.query(

    }

    @Override
    public boolean isSatisfiedBy(DependencyResult candidate) {
        //The matching is very simple at the moment but it should solve majority of cases.
        //It operates using String#contains and it tests either requested or selected module.
        if (candidate instanceof ResolvedDependencyResult) {

  target.addLegalDialect<shape::ShapeDialect>();
  target.addLegalOp<func::CallOp>();

  // These ops are legalized in LegalizeTFCommunication after this and that pass
  // only operates on MHLO control flow ops.
  target.addLegalOp<TF::_XlaHostComputeMlirOp, TF::XlaSendToHostOp,
                    TF::XlaRecvFromHostOp>();

  return target;
}

}  // namespace mhlo

Ele é projetado para ter funções que recebem dois parâmetros, uma "requisição" e uma "resposta". Então você "lê" as partes da requisição, e "escreve" partes para a resposta. Devido ao seu design, não é possível declarar parâmetros de requisição e corpos com _type hints_ Python padrão como parâmetros de funções.

#
# First, ensure that we really are in module mode, and that we really don't have
# a go.mod file.
go env GOMOD
stdout 'NUL|/dev/null'


# 'go list' without arguments implicitly operates on the current directory,
# which is not in a module.
! go list
stderr '^go: go.mod file not found in current directory or any parent directory; see ''go help modules''$'
go list -m
stdout '^command-line-arguments$'

TEXT ·addMulVVW2048(SB), $0-32
	MOVD	$32, R0
	JMP		addMulVVWx(SB)

TEXT addMulVVWx(SB), NOFRAME|NOSPLIT, $0
	MOVD	z+0(FP), R1
	MOVD	x+8(FP), R2
	MOVD	y+16(FP), R3
	MOVD	$0, R4

// The main loop of this code operates on a block of 4 words every iteration
// performing [R4:R12:R11:R10:R9] = R4 + R3 * [R8:R7:R6:R5] + [R12:R11:R10:R9]
// where R4 is carried from the previous iteration, R8:R7:R6:R5 hold the next