Conv1D

lamp.nn.Conv1D
See theConv1D companion object
case class Conv1D(weights: Constant, bias: Constant, stride: Long, padding: Long, dilation: Long, groups: Long) extends Module

Attributes

Companion
object
Graph
Supertypes
trait Serializable
trait Product
trait Equals
class Object
trait Matchable
class Any
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Value members

Concrete methods

def forward[S : Sc](x: Variable): Variable

The implementation of the function.

The implementation of the function.

In addition of x it can also use all the `state to compute its value.

Attributes

Inherited methods

def apply[S : Sc](a: Variable): B

Alias of forward

Alias of forward

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Inherited from:
GenericModule
final def gradients(loss: Variable, zeroGrad: Boolean): Seq[Option[STen]]

Computes the gradient of loss with respect to the parameters.

Computes the gradient of loss with respect to the parameters.

Attributes

Inherited from:
GenericModule
final def learnableParameters: Long

Returns the total number of optimizable parameters.

Returns the total number of optimizable parameters.

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Inherited from:
GenericModule
final def parameters: Seq[(Constant, PTag)]

Returns the state variables which need gradient computation.

Returns the state variables which need gradient computation.

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Inherited from:
GenericModule
def productElementNames: Iterator[String]

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Inherited from:
Product
def productIterator: Iterator[Any]

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Inherited from:
Product
final def zeroGrad(): Unit

Attributes

Inherited from:
GenericModule

Concrete fields

override val state: Seq[(Constant, PTag)]

List of optimizable, or non-optimizable, but stateful parameters

List of optimizable, or non-optimizable, but stateful parameters

Stateful means that the state is carried over the repeated forward calls.

Attributes