Output

Representation of one of the outputs of an Op's computation.

An Output is a symbolic handle to one of the outputs of an Op. It does not hold the values of that op's output, but instead provides a means of computing those values in a TensorFlow Session.

This class has two primary purposes:

An Output can be passed as input to another Op. This builds a dataflow connection between ops, which enables TensorFlow to execute an entire Graph that represents a large, multi-step computation. 2. After the graph has been launched in a Session, the value of an Output can be computed by passing it to Session.run. 3. Output.evaluate can also be used to compute the value of an Output If no session is provided, then the default session is used.

In the following example, c, d, and e are symbolic Output objects, whereas result is a Scala array that stores a concrete value:

val c = constant(Array(Array(1.0, 2.0), Array(3.0, 4.0)))
val d = constant(Array(Array(1.0, 1.0), Array(0.0, 1.0)))
val e = matmul(c, d)
val result = e.evaluate() // 'result' now holds the result of the matrix multiplication.

Linear Supertypes

Serializable, Serializable, Product, Equals, OutputLike, OutputConvertible, AnyRef, Any

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 apply(firstIndexer: core.Indexer, otherIndexers: core.Indexer*): Output

Creates an op that slices this op according to the provided indexers.
Creates an op that slices this op according to the provided indexers.
More details into how to construct and use indexers are provided in the Indexer documentation.
firstIndexer
First indexer to use.
otherIndexers
Rest of the indexers to use.
returns
Created op.
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def consumers: Array[Input]

Consumers of this op output (i.e., ops that use this op output as one of their inputs).
Consumers of this op output (i.e., ops that use this op output as one of their inputs).

Definition Classes
Output → OutputLike
def dataType: types.DataType

Data type of this op output.
Data type of this op output.

Definition Classes
Output → OutputLike
def device: String

Device on which this op output will be placed.
Device on which this op output will be placed.

Definition Classes
Output → OutputLike
final def eq(arg0: AnyRef): Boolean

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

Definition Classes
Output → Equals → 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 graph: core.Graph

Graph where the op belongs.
Graph where the op belongs.

Definition Classes
Output → OutputLike
def hashCode(): Int

Definition Classes
Output → AnyRef → Any
val index: Int

Output index.
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
def name: String

Name of this op output.
Name of this op output. This is simply set to "<op.name>:<index>".

Definition Classes
Output → OutputLike
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val op: Op

Op whose output this class represents.
Op whose output this class represents.

Definition Classes
Output → OutputLike
def rank: Int

Rank of the tensor that this op output represents.
def setShape(shape: core.Shape): Unit

Sets the shape of this op output to the provided shape.
Sets the shape of this op output to the provided shape.
This method can be useful in cases when shape inference fails, but the shape of the op output is known by the user of the library.
shape
Shape to use.
def shape: core.Shape

Shape of the tensor that this op output represents.
def size: Long

Size of the tensor that this op output represents.
def slice(firstIndexer: core.Indexer, otherIndexers: core.Indexer*): Output

Creates an op that slices this op according to the provided indexers.
Creates an op that slices this op according to the provided indexers.
More details into how to construct and use indexers are provided in the Indexer documentation.
firstIndexer
First indexer to use.
otherIndexers
Rest of the indexers to use.
returns
Created op.
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toOutput: Output

Returns the Output that this OutputLike object represents.
Returns the Output that this OutputLike object represents.

Definition Classes
Output → OutputLike → OutputConvertible
def toOutputIndexedSlices(optimize: Boolean = true): OutputIndexedSlices

Returns an OutputIndexedSlices that has the same value as this OutputLike.
Returns an OutputIndexedSlices that has the same value as this OutputLike.
optimize
Boolean flag indicating whether to optimize this conversion by using a constant op with the shape of this tensor at graph creation time (instead of execution time), if known.
returns
OutputIndexedSlices that has the same value as this OutputLike.

Definition Classes
Output → OutputLike
def toString(): String

Definition Classes
Output → AnyRef → Any
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 Docs: object Output | package ops

final case class Output extends OutputLike with Product with Serializable

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

final def ==(arg0: Any): Boolean

def apply(firstIndexer: core.Indexer, otherIndexers: core.Indexer*): Output

final def asInstanceOf[T0]: T0

def clone(): AnyRef

def consumers: Array[Input]

def dataType: types.DataType

def device: String

final def eq(arg0: AnyRef): Boolean

def equals(that: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def graph: core.Graph

def hashCode(): Int

val index: Int

final def isInstanceOf[T0]: Boolean

def name: String

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val op: Op

def rank: Int

def setShape(shape: core.Shape): Unit

def shape: core.Shape

def size: Long

def slice(firstIndexer: core.Indexer, otherIndexers: core.Indexer*): Output

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

def toOutput: Output

def toOutputIndexedSlices(optimize: Boolean = true): OutputIndexedSlices

def toString(): String

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from OutputLike

Inherited from OutputConvertible

Inherited from AnyRef

Inherited from Any

Ungrouped