# ContrastiveDivergenceExample

#### class ContrastiveDivergenceExample[C] extends Example

A training example for using contrastive divergence.

C

The type of sampler context

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### Instance Constructors

1. #### new ContrastiveDivergenceExample(context: C, model: model.Model with model.Parameters, sampler: Sampler[C], k: Int = 1)

context

The argument to the sampler

model

The model to be optimized

sampler

The sampler.

k

The number of steps to sample for.

### Value Members

1. #### final def !=(arg0: AnyRef): Boolean

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2. #### final def !=(arg0: Any): Boolean

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3. #### final def ##(): Int

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4. #### final def ==(arg0: AnyRef): Boolean

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5. #### final def ==(arg0: Any): Boolean

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6. #### def accumulateValueAndGradient(value: DoubleAccumulator, gradient: WeightsMapAccumulator): Unit

Put objective value and gradient into the accumulators.

Put objective value and gradient into the accumulators. Either argument can be null if they don't need to be computed.

value

Accumulator to hold value

Accumulator to hold gradient

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ContrastiveDivergenceExampleExample
7. #### final def asInstanceOf[T0]: T0

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8. #### def clone(): AnyRef

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9. #### val context: C

The argument to the sampler

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

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11. #### def equals(arg0: Any): Boolean

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12. #### def finalize(): Unit

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13. #### final def getClass(): Class[_]

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14. #### def hashCode(): Int

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15. #### final def isInstanceOf[T0]: Boolean

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16. #### val k: Int

The number of steps to sample for.

17. #### final def ne(arg0: AnyRef): Boolean

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18. #### final def notify(): Unit

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19. #### final def notifyAll(): Unit

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The sampler.

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

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22. #### def toString(): String

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23. #### final def wait(): Unit

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

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25. #### final def wait(arg0: Long): Unit

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