ValuePnp

Value Members

1. final def !=(arg0: Any): Boolean

   

   Definition Classes

   AnyRef → Any

2. final def ##(): Int

   

   Definition Classes

   AnyRef → Any

3. final def ==(arg0: Any): Boolean

   

   Definition Classes

   AnyRef → Any

4. final def asInstanceOf[T0]: T0

   

   Definition Classes

   Any

5. def beamSearch(k: Int, env: Env, context: PnpInferenceContext): PnpBeamMarginals[A]

   

   Definition Classes

   Pnp

6. def beamSearch(k: Int, env: Env): PnpBeamMarginals[A]

   

   Definition Classes

   Pnp

7. def beamSearch(k: Int, model: PnpModel): PnpBeamMarginals[A]

   

   Definition Classes

   Pnp

8. def beamSearch(beamSize: Int = 1, maxIters: Int = 1, env: Env = Env.init, context: PnpInferenceContext = PnpInferenceContext.init): PnpBeamMarginals[A]

   

   Performs a beam search over executions of this program returning at most beamSize execution results.

   Performs a beam search over executions of this program returning at most beamSize execution results. env is the initial global state of the program, and graph is the initial computation graph. These must contain values for any global variables or neural network parameters referenced in the program.

   Definition Classes

   Pnp

9. def clone(): AnyRef

   

   Attributes

   protected[java.lang]

   Definition Classes

   AnyRef

   Annotations

   @throws( ... )

10. final def eq(arg0: AnyRef): Boolean

    

    Definition Classes

    AnyRef

11. def filter(f: (A) ⇒ Boolean): Pnp[A]

    

    Definition Classes

    Pnp

12. def finalize(): Unit

    

    Attributes

    protected[java.lang]

    Definition Classes

    AnyRef

    Annotations

    @throws( classOf[java.lang.Throwable] )

13. def flatMap[B](f: (A) ⇒ Pnp[B]): Pnp[B]

    

    flatMap is the monad's bind operator.

    flatMap is the monad's bind operator. It chains two probabilistic computations together in the natural way where f represents a conditional distribution P(B | A). Hence, binding f to a distribution P(A) returns the marginal distribution over B, sum_a P(A=a) P(B | A=a).

    Definition Classes

    Pnp

14. final def getClass(): Class[_]

    

    Definition Classes

    AnyRef → Any

15. def inOneStep(): Pnp[A]

    

    Definition Classes

    Pnp

16. final def isInstanceOf[T0]: Boolean

    

    Definition Classes

    Any

17. def map[B](f: (A) ⇒ B): Pnp[B]

    

    Definition Classes

    Pnp

18. final def ne(arg0: AnyRef): Boolean

    

    Definition Classes

    AnyRef

19. final def notify(): Unit

    

    Definition Classes

    AnyRef

20. final def notifyAll(): Unit

    

    Definition Classes

    AnyRef

21. def sample(numSamples: Int = 1, env: Env = Env.init, context: PnpInferenceContext = PnpInferenceContext.init): Execution[A]

    

    Definition Classes

    Pnp

22. def sampleStep[C](env: Env, logProb: Double, context: PnpInferenceContext, continuation: PnpContinuation[A, C], queue: PnpSearchQueue[C], finished: PnpSearchQueue[C]): Unit

    

    Implements a single step of forward sampling.

    Implements a single step of forward sampling.

    Definition Classes

    ValuePnp → Pnp

23. def searchStep[C](env: Env, logProb: Double, context: PnpInferenceContext, continuation: PnpContinuation[A, C], queue: PnpSearchQueue[C], finished: PnpSearchQueue[C]): Unit

    

    Implements a single search step of beam search.

    Implements a single search step of beam search.

    Definition Classes

    ValuePnp → Pnp

24. final def synchronized[T0](arg0: ⇒ T0): T0

    

    Definition Classes

    AnyRef

25. val value: A

    

26. final def wait(): Unit

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

27. final def wait(arg0: Long, arg1: Int): Unit

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )

28. final def wait(arg0: Long): Unit

    

    Definition Classes

    AnyRef

    Annotations

    @throws( ... )