SimpleAttention

Instance Constructors

new SimpleAttention(memory: Output, memorySequenceLengths: Output = null, checkInnerDimensionsDefined: Boolean = true, scoreMaskValue: Output = Float.NegativeInfinity, name: String = "SimpleAttention")

Abstract Value Members

abstract def score(query: Output, state: Output): Output

Computes an alignment score for query.
Computes an alignment score for query.
query
Query tensor.
state
Current attention mechanism state (defaults to the previous alignment tensor). The data type of this tensor matches that of values and its shape is [batchSize, alignmentSize], where alignmentSize is the memory's maximum time.
returns
Score tensor.

Attributes
protected
Definition Classes
Attention

Concrete Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def alignment(query: Output, previousState: Output): (Output, Output)

Computes an alignment tensor given the provided query and previous alignment tensor.
Computes an alignment tensor given the provided query and previous alignment tensor.
The previous alignment tensor is important for attention mechanisms that use the previous alignment to calculate the attention at the next time step, such as monotonic attention mechanisms.
TODO: Figure out how to generalize the "next state" functionality.
query
Query tensor.
previousState
Previous alignment tensor.
returns
Tuple containing the alignment tensor and the next attention state.

Definition Classes
SimpleAttention → Attention
lazy val alignmentSize: Output

Definition Classes
Attention
final def asInstanceOf[T0]: T0

Definition Classes
Any
lazy val batchSize: Output

Definition Classes
Attention
val checkInnerDimensionsDefined: Boolean

Definition Classes
SimpleAttention → Attention
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
lazy val dataType: types.DataType

Definition Classes
Attention
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def hashCode(): Int

Definition Classes
AnyRef → Any
lazy val initialAlignment: Output

Initial alignment value.
Initial alignment value.
This is important for attention mechanisms that use the previous alignment to calculate the alignment at the next time step (e.g., monotonic attention).
The default behavior is to return a tensor of all zeros.

Definition Classes
Attention
def initialState: Output

Initial state value.
Initial state value.
This is important for attention mechanisms that use the previous alignment to calculate the alignment at the next time step (e.g., monotonic attention).
The default behavior is to return the same output as initialAlignment.

Definition Classes
SimpleAttention → Attention
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
lazy val keys: Output

Definition Classes
Attention
val memory: Output

Attributes
protected
Definition Classes
SimpleAttention → Attention
val memorySequenceLengths: Output

Attributes
protected
Definition Classes
SimpleAttention → Attention
val name: String

Definition Classes
SimpleAttention → Attention
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
def probability(score: Output, state: Output): Output

Computes alignment probabilities for score.
Computes alignment probabilities for score.
score
Alignment score tensor.
state
Current attention mechanism state (defaults to the previous alignment tensor). The data type of this tensor matches that of values and its shape is [batchSize, alignmentSize], where alignmentSize is the memory's maximum time.
returns
Alignment probabilities tensor.

Attributes
protected
Definition Classes
Attention
val scoreMaskValue: Output

Definition Classes
SimpleAttention → Attention
def stateSize: core.Shape

Definition Classes
SimpleAttention → Attention
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
lazy val values: Output

Definition Classes
Attention
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

Related Doc: package attention

abstract class SimpleAttention extends Attention[Output, core.Shape]

Instance Constructors

new SimpleAttention(memory: Output, memorySequenceLengths: Output = null, checkInnerDimensionsDefined: Boolean = true, scoreMaskValue: Output = Float.NegativeInfinity, name: String = "SimpleAttention")

Abstract Value Members

abstract def score(query: Output, state: Output): Output

Concrete Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def alignment(query: Output, previousState: Output): (Output, Output)

lazy val alignmentSize: Output

final def asInstanceOf[T0]: T0

lazy val batchSize: Output

val checkInnerDimensionsDefined: Boolean

def clone(): AnyRef

lazy val dataType: types.DataType

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

lazy val initialAlignment: Output

def initialState: Output

final def isInstanceOf[T0]: Boolean

lazy val keys: Output

val memory: Output

val memorySequenceLengths: Output

val name: String

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

def probability(score: Output, state: Output): Output

val scoreMaskValue: Output

def stateSize: core.Shape

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

def toString(): String

lazy val values: Output

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Attention[Output, core.Shape]

Inherited from AnyRef

Inherited from Any

Ungrouped