object tf extends API with API
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Type Members
- sealed trait Combiner extends AnyRef
- Definition Classes
- Embedding
- sealed trait PartitionStrategy extends AnyRef
- Definition Classes
- Embedding
- case class ConstantPadding[V](value: Option[tensors.Tensor[V]] = None)(implicit evidence$48: core.types.TF[V]) extends PaddingMode with Product with Serializable
- Definition Classes
- Manipulation
- sealed trait PaddingMode extends AnyRef
- Definition Classes
- Manipulation
- type AbortedException = jni.AbortedException
- Definition Classes
- API
- type AlreadyExistsException = jni.AlreadyExistsException
- Definition Classes
- API
- type Attention[T, State, StateShape] = ops.rnn.attention.Attention[T, State, StateShape]
- Definition Classes
- API
- type AttentionWrapperCell[AttentionDataType, CellState, AttentionState, CellStateShape, AttentionStateShape] = ops.rnn.attention.AttentionWrapperCell[AttentionDataType, CellState, AttentionState, CellStateShape, AttentionStateShape]
- Definition Classes
- API
- type BahdanauAttention[T] = ops.rnn.attention.BahdanauAttention[T]
- Definition Classes
- API
- type BasicLSTMCell[T] = ops.rnn.cell.BasicLSTMCell[T]
- Definition Classes
- API
- type BasicRNNCell[T] = ops.rnn.cell.BasicRNNCell[T]
- Definition Classes
- API
- type BasicTuple[T] = Tuple[ops.Output[T], ops.Output[T]]
- Definition Classes
- API
- type CancelledException = jni.CancelledException
- Definition Classes
- API
- type CheckpointNotFoundException = core.exception.CheckpointNotFoundException
- Definition Classes
- API
- type DataLossException = jni.DataLossException
- Definition Classes
- API
- type DeadlineExceededException = jni.DeadlineExceededException
- Definition Classes
- API
- type DeviceSpecification = core.DeviceSpecification
- Definition Classes
- API
- type DeviceWrapper[Out, State, OutShape, StateShape] = ops.rnn.cell.DeviceWrapper[Out, State, OutShape, StateShape]
- Definition Classes
- API
- type DropoutWrapper[Out, State, OutShape, StateShape] = ops.rnn.cell.DropoutWrapper[Out, State, OutShape, StateShape]
- Definition Classes
- API
- type FailedPreconditionException = jni.FailedPreconditionException
- Definition Classes
- API
- type GRUCell[T] = ops.rnn.cell.GRUCell[T]
- Definition Classes
- API
- type GraphMismatchException = core.exception.GraphMismatchException
- Definition Classes
- API
- type HashTable[K, V] = ops.lookup.HashTable[K, V]
- Definition Classes
- API
- type IDLookupTableWithHashBuckets[K] = ops.lookup.IDLookupTableWithHashBuckets[K]
- Definition Classes
- API
- type IllegalNameException = core.exception.IllegalNameException
- Definition Classes
- API
- type InternalException = jni.InternalException
- Definition Classes
- API
- type InvalidArgumentException = jni.InvalidArgumentException
- Definition Classes
- API
- type InvalidDataTypeException = core.exception.InvalidDataTypeException
- Definition Classes
- API
- type InvalidDeviceException = core.exception.InvalidDeviceException
- Definition Classes
- API
- type InvalidIndexerException = core.exception.InvalidIndexerException
- Definition Classes
- API
- type InvalidShapeException = core.exception.InvalidShapeException
- Definition Classes
- API
- type LSTMCell[T] = ops.rnn.cell.LSTMCell[T]
- Definition Classes
- API
- type LSTMState[T] = ops.rnn.cell.LSTMState[T]
- Definition Classes
- API
- type LSTMTuple[T] = Tuple[ops.Output[T], LSTMState[T]]
- Definition Classes
- API
- type LookupTable[K, V] = ops.lookup.LookupTable[K, V]
- Definition Classes
- API
- type LookupTableInitializer[K, V] = ops.lookup.LookupTableInitializer[K, V]
- Definition Classes
- API
- type LookupTableTensorInitializer[K, V] = ops.lookup.LookupTableTensorInitializer[K, V]
- Definition Classes
- API
- type LookupTableTextFileInitializer[K, V] = ops.lookup.LookupTableTextFileInitializer[K, V]
- Definition Classes
- API
- type LuongAttention[T] = ops.rnn.attention.LuongAttention[T]
- Definition Classes
- API
- type NotFoundException = jni.NotFoundException
- Definition Classes
- API
- type OpBuilderUsedException = core.exception.OpBuilderUsedException
- Definition Classes
- API
- type OpCreationContext = GraphConstructionScope
- Definition Classes
- API
- type OpSpecification = ops.OpSpecification
- Definition Classes
- API
- type OutOfRangeException = jni.OutOfRangeException
- Definition Classes
- API
- type PermissionDeniedException = jni.PermissionDeniedException
- Definition Classes
- API
- type RNNCell[Out, State, OutShape, StateShape] = ops.rnn.cell.RNNCell[Out, State, OutShape, StateShape]
- Definition Classes
- API
- type RNNTuple[Out, State] = Tuple[Out, State]
- Definition Classes
- API
- type ResidualWrapper[Out, State, OutShape, StateShape] = ops.rnn.cell.ResidualWrapper[Out, State, OutShape, StateShape]
- Definition Classes
- API
- type ResourceExhaustedException = jni.ResourceExhaustedException
- Definition Classes
- API
- type Saver = ops.variables.Saver
- Definition Classes
- API
- type ShapeMismatchException = core.exception.ShapeMismatchException
- Definition Classes
- API
- type StackedCell[Out, State, OutShape, StateShape] = ops.rnn.cell.StackedCell[Out, State, OutShape, StateShape]
- Definition Classes
- API
- type TextFileFieldExtractor[K] = ops.lookup.TextFileFieldExtractor[K]
- Definition Classes
- API
- type UnauthenticatedException = jni.UnauthenticatedException
- Definition Classes
- API
- type UnavailableException = jni.UnavailableException
- Definition Classes
- API
- type UnimplementedException = jni.UnimplementedException
- Definition Classes
- API
- type UnknownException = jni.UnknownException
- Definition Classes
- API
- type Variable[T] = ops.variables.Variable[T]
- Definition Classes
- API
- type VariableGetter = ops.variables.Variable.VariableGetter
- Definition Classes
- API
- type VariableInitializer = Initializer
- Definition Classes
- API
- type VariableLike[T] = ops.variables.VariableLike[T]
- Definition Classes
- API
- type VariableRegularizer = Regularizer
- Definition Classes
- API
- type VariableReuse = Reuse
- Definition Classes
- API
- type VariableReuseAllowed = ReuseAllowed
- Definition Classes
- API
- type VariableScope = ops.variables.VariableScope
- Definition Classes
- API
- type VariableStore = ops.variables.VariableStore
- Definition Classes
- API
Value Members
- case object DivStrategy extends PartitionStrategy with Product with Serializable
- Definition Classes
- Embedding
- case object MeanCombiner extends Combiner with Product with Serializable
- Definition Classes
- Embedding
- case object ModStrategy extends PartitionStrategy with Product with Serializable
- Definition Classes
- Embedding
- case object SumCombiner extends Combiner with Product with Serializable
- Definition Classes
- Embedding
- case object SumSqrtNCombiner extends Combiner with Product with Serializable
- Definition Classes
- Embedding
- object ReflectivePadding extends PaddingMode
- Definition Classes
- Manipulation
- object SymmetricPadding extends PaddingMode
- Definition Classes
- Manipulation
- object bitwise extends Bitwise
- Definition Classes
- Math
- 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
- val AbortedException: core.exception.AbortedException.type
- Definition Classes
- API
- val AlreadyExistsException: core.exception.AlreadyExistsException.type
- Definition Classes
- API
- val AttentionWrapperCell: ops.rnn.attention.AttentionWrapperCell.type
- Definition Classes
- API
- val BahdanauAttention: ops.rnn.attention.BahdanauAttention.type
- Definition Classes
- API
- val BasicLSTMCell: ops.rnn.cell.BasicLSTMCell.type
- Definition Classes
- API
- val BasicRNNCell: ops.rnn.cell.BasicRNNCell.type
- Definition Classes
- API
- val CancelledException: core.exception.CancelledException.type
- Definition Classes
- API
- val CheckpointNotFoundException: core.exception.CheckpointNotFoundException.type
- Definition Classes
- API
- def ConstantInitializer[T](value: ops.Output[T])(implicit arg0: core.types.TF[T]): Initializer
- Definition Classes
- API
- def ConstantInitializer[T](value: tensors.Tensor[T])(implicit arg0: core.types.TF[T]): Initializer
- Definition Classes
- API
- val CreateNewVariableOnly: CreateNewOnly.type
- Definition Classes
- API
- val DataLossException: core.exception.DataLossException.type
- Definition Classes
- API
- val DeadlineExceededException: core.exception.DeadlineExceededException.type
- Definition Classes
- API
- val DeviceWrapper: ops.rnn.cell.DeviceWrapper.type
- Definition Classes
- API
- val DropoutWrapper: ops.rnn.cell.DropoutWrapper.type
- Definition Classes
- API
- val FailedPreconditionException: core.exception.FailedPreconditionException.type
- Definition Classes
- API
- val GRUCell: ops.rnn.cell.GRUCell.type
- Definition Classes
- API
- val GlorotNormalInitializer: ops.variables.GlorotNormalInitializer.type
- Definition Classes
- API
- val GlorotUniformInitializer: ops.variables.GlorotUniformInitializer.type
- Definition Classes
- API
- val GraphMismatchException: core.exception.GraphMismatchException.type
- Definition Classes
- API
- val HashTable: ops.lookup.HashTable.type
- Definition Classes
- API
- val IDLookupTableWithHashBuckets: ops.lookup.IDLookupTableWithHashBuckets.type
- Definition Classes
- API
- val IllegalNameException: core.exception.IllegalNameException.type
- Definition Classes
- API
- val InternalException: core.exception.InternalException.type
- Definition Classes
- API
- val InvalidArgumentException: core.exception.InvalidArgumentException.type
- Definition Classes
- API
- val InvalidDataTypeException: core.exception.InvalidDataTypeException.type
- Definition Classes
- API
- val InvalidDeviceException: core.exception.InvalidDeviceException.type
- Definition Classes
- API
- val InvalidIndexerException: core.exception.InvalidIndexerException.type
- Definition Classes
- API
- val InvalidShapeException: core.exception.InvalidShapeException.type
- Definition Classes
- API
- val LSTMCell: ops.rnn.cell.LSTMCell.type
- Definition Classes
- API
- val LSTMState: ops.rnn.cell.LSTMState.type
- Definition Classes
- API
- def LSTMTuple[T](output: ops.Output[T], state: LSTMState[T]): LSTMTuple[T]
- Definition Classes
- API
- val LookupTableTensorInitializer: ops.lookup.LookupTableTensorInitializer.type
- Definition Classes
- API
- val LookupTableTextFileInitializer: ops.lookup.LookupTableTextFileInitializer.type
- Definition Classes
- API
- val LuongAttention: ops.rnn.attention.LuongAttention.type
- Definition Classes
- API
- val NotFoundException: core.exception.NotFoundException.type
- Definition Classes
- API
- val OnesInitializer: ops.variables.OnesInitializer.type
- Definition Classes
- API
- val OpBuilderUsedException: core.exception.OpBuilderUsedException.type
- Definition Classes
- API
- val OutOfRangeException: core.exception.OutOfRangeException.type
- Definition Classes
- API
- val PermissionDeniedException: core.exception.PermissionDeniedException.type
- Definition Classes
- API
- val RNNTuple: Tuple.type
- Definition Classes
- API
- val RandomNormalInitializer: ops.variables.RandomNormalInitializer.type
- Definition Classes
- API
- val RandomTruncatedNormalInitializer: ops.variables.RandomTruncatedNormalInitializer.type
- Definition Classes
- API
- val RandomUniformInitializer: ops.variables.RandomUniformInitializer.type
- Definition Classes
- API
- val ResidualWrapper: ops.rnn.cell.ResidualWrapper.type
- Definition Classes
- API
- val ResourceExhaustedException: core.exception.ResourceExhaustedException.type
- Definition Classes
- API
- val ReuseExistingVariableOnly: ReuseExistingOnly.type
- Definition Classes
- API
- val ReuseOrCreateNewVariable: ReuseOrCreateNew.type
- Definition Classes
- API
- val Saver: ops.variables.Saver.type
- Definition Classes
- API
- val ShapeMismatchException: core.exception.ShapeMismatchException.type
- Definition Classes
- API
- val StackedCell: ops.rnn.cell.StackedCell.type
- Definition Classes
- API
- val TextFileColumn: ops.lookup.TextFileColumn.type
- Definition Classes
- API
- val TextFileLineNumber: ops.lookup.TextFileLineNumber.type
- Definition Classes
- API
- val TextFileWholeLine: ops.lookup.TextFileWholeLine.type
- Definition Classes
- API
- val Timeline: core.client.Timeline.type
- Definition Classes
- API
- val UnauthenticatedException: core.exception.UnauthenticatedException.type
- Definition Classes
- API
- val UnavailableException: core.exception.UnavailableException.type
- Definition Classes
- API
- val UnimplementedException: core.exception.UnimplementedException.type
- Definition Classes
- API
- val UnknownException: core.exception.UnknownException.type
- Definition Classes
- API
- val VariableScope: ops.variables.VariableScope.type
- Definition Classes
- API
- val VariableStore: ops.variables.VariableStore.type
- Definition Classes
- API
- val VarianceScalingInitializer: ops.variables.VarianceScalingInitializer.type
- Definition Classes
- API
- val ZerosInitializer: ops.variables.ZerosInitializer.type
- Definition Classes
- API
- def abs[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Abs")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def absGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def accumulateN[T](inputs: Seq[ops.Output[T]], shape: core.Shape = null, name: String = "AccumulateN")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[T]
- Definition Classes
- Math
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def accumulateNGradient[T](op: ops.Op[Seq[ops.Output[T]], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): Seq[ops.Output[T]]
- Attributes
- protected
- Definition Classes
- Math
- def acos[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Acos")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def acosGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def acosh[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "ACosh")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def acoshGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def add[T](x: ops.Output[T], y: ops.Output[T], name: String = "Add")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def addBias[T](value: ops.Output[T], bias: ops.Output[T], cNNDataFormat: CNNDataFormat = CNNDataFormat.default, name: String = "AddBias")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[T]
- Definition Classes
- NN
- def addBiasGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- NN
- def addBiasHessian[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def addGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def addN[T](inputs: Seq[ops.Output[T]], name: String = "AddN")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[T]
- Definition Classes
- Math
- def addNGradient[T](op: ops.Op[Seq[ops.Output[T]], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): Seq[ops.Output[T]]
- Attributes
- protected
- Definition Classes
- Math
- def all[I](input: ops.Output[Boolean], axes: ops.Output[I] = null, keepDims: Boolean = false, name: String = "All")(implicit arg0: IntDefault[I], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[Boolean]
- Definition Classes
- Math
- def angleDouble[OL[A] <: ops.OutputLike[A]](input: OL[core.types.ComplexDouble], name: String = "Angle")(implicit ev: Aux[OL, core.types.ComplexDouble]): OL[Double]
- Definition Classes
- Math
- def angleFloat[OL[A] <: ops.OutputLike[A]](input: OL[core.types.ComplexFloat], name: String = "Angle")(implicit ev: Aux[OL, core.types.ComplexFloat]): OL[Float]
- Definition Classes
- Math
- def any[I](input: ops.Output[Boolean], axes: ops.Output[I] = null, keepDims: Boolean = false, name: String = "Any")(implicit arg0: IntDefault[I], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[Boolean]
- Definition Classes
- Math
- def approximatelyEqual[T](x: ops.Output[T], y: ops.Output[T], tolerance: Float = 0.00001f, name: String = "ApproximatelyEqual")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[Boolean]
- Definition Classes
- Math
- def argmax[T, I, R](input: ops.Output[T], axes: ops.Output[I], outputDataType: core.types.DataType[R], name: String = "ArgMax")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I], arg4: core.types.TF[R]): ops.Output[R]
- Definition Classes
- Math
- def argmin[T, I, R](input: ops.Output[T], axes: ops.Output[I], outputDataType: core.types.DataType[R], name: String = "ArgMin")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I], arg4: core.types.TF[R]): ops.Output[R]
- Definition Classes
- Math
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def asin[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Asin")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def asinGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def asinh[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "ASinh")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def asinhGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def assert(condition: ops.Output[Boolean], data: Seq[ops.Output[Any]], summarize: Int = 3, name: String = "Assert"): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertAtMostNTrue(predicates: Seq[ops.Output[Boolean]], n: Int, message: ops.Output[String] = null, summarize: Int = 3, name: String = "AssertAtMostNTrue"): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertEqual[T](x: ops.Output[T], y: ops.Output[T], message: ops.Output[String] = null, data: Seq[ops.Output[Any]] = null, summarize: Int = 3, name: String = "AssertEqual")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertGreater[T](x: ops.Output[T], y: ops.Output[T], message: ops.Output[String] = null, data: Seq[ops.Output[Any]] = null, summarize: Int = 3, name: String = "AssertGreater")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertGreaterEqual[T](x: ops.Output[T], y: ops.Output[T], message: ops.Output[String] = null, data: Seq[ops.Output[Any]] = null, summarize: Int = 3, name: String = "AssertGreaterEqual")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertLess[T](x: ops.Output[T], y: ops.Output[T], message: ops.Output[String] = null, data: Seq[ops.Output[Any]] = null, summarize: Int = 3, name: String = "AssertLess")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertLessEqual[T](x: ops.Output[T], y: ops.Output[T], message: ops.Output[String] = null, data: Seq[ops.Output[Any]] = null, summarize: Int = 3, name: String = "AssertLessEqual")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertNear[T](x: ops.Output[T], y: ops.Output[T], relTolerance: ops.Output[Float] = 0.00001f, absTolerance: ops.Output[Float] = 0.00001f, message: ops.Output[String] = null, data: Seq[ops.Output[Any]] = null, summarize: Int = 3, name: String = "AssertNear")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertNegative[T](input: ops.Output[T], message: ops.Output[String] = null, data: Seq[ops.Output[Any]] = null, summarize: Int = 3, name: String = "AssertNegative")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertNonNegative[T](input: ops.Output[T], message: ops.Output[String] = null, data: Seq[ops.Output[Any]] = null, summarize: Int = 3, name: String = "AssertNonNegative")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertNonPositive[T](input: ops.Output[T], message: ops.Output[String] = null, data: Seq[ops.Output[Any]] = null, summarize: Int = 3, name: String = "AssertNonPositive")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertNoneEqual[T](x: ops.Output[T], y: ops.Output[T], message: ops.Output[String] = null, data: Seq[ops.Output[Any]] = null, summarize: Int = 3, name: String = "AssertNoneEqual")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def assertPositive[T](input: ops.Output[T], message: ops.Output[String] = null, data: Seq[ops.Output[Any]] = null, summarize: Int = 3, name: String = "AssertPositive")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Op[Seq[ops.Output[Any]], Unit]
- Definition Classes
- Checks
- def atan[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Atan")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def atan2[T](x: ops.Output[T], y: ops.Output[T], name: String = "ATan2")(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): ops.Output[T]
- Definition Classes
- Math
- def atan2Gradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def atanGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def atanh[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "ATanh")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def atanhGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def batchGather[T, I](input: ops.Output[T], indices: ops.Output[I], axis: Int = 1, batchDimensionCount: Int = 1, name: String = "BatchGather")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidShapeException])
- def batchMatmulGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def batchNormalization[T](x: ops.Output[T], mean: ops.Output[T], variance: ops.Output[T], offset: Option[ops.Output[T]] = None, scale: Option[ops.Output[T]] = None, epsilon: ops.Output[T], name: String = "BatchNormalization")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- NN
- def batchToSpace[T, I](input: ops.Output[T], blockSize: Int, crops: ops.Output[I], name: String = "BatchToSpace")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def batchToSpaceND[T, I1, I2](input: ops.Output[T], blockShape: ops.Output[I1], crops: ops.Output[I2], name: String = "BatchToSpaceND")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I1], arg2: core.types.IsIntOrLong[I1], arg3: core.types.TF[I2], arg4: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Manipulation
- def batchToSpaceNDGradient[T, I1, I2](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[I2]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I1], arg2: core.types.IsIntOrLong[I1], arg3: core.types.TF[I2], arg4: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I1], ops.Output[I2])
- Attributes
- protected
- Definition Classes
- Manipulation
- def bidirectionalDynamicRNN[Out, State, OutShape, StateShape](cellFw: ops.rnn.cell.RNNCell[Out, State, OutShape, StateShape], cellBw: ops.rnn.cell.RNNCell[Out, State, OutShape, StateShape], input: Out, initialStateFw: Option[State] = None, initialStateBw: Option[State] = None, timeMajor: Boolean = false, parallelIterations: Int = 32, swapMemory: Boolean = false, sequenceLengths: ops.Output[Int] = null, name: String = "RNN")(implicit arg0: OutputStructure[Out], arg1: OutputStructure[State], evZeroOut: Aux[Out, OutShape], evZeroState: Aux[State, StateShape]): (Tuple[Out, State], Tuple[Out, State])
- Definition Classes
- RNN
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidShapeException])
- def binCount[T](input: ops.Output[Int], dataType: core.types.DataType[T], weights: ops.Output[T] = null, minLength: ops.Output[Int] = null, maxLength: ops.Output[Int] = null, name: String = "BinCount")(implicit arg0: core.types.TF[T], arg1: core.types.IsIntOrLongOrFloatOrDouble[T]): ops.Output[T]
- Definition Classes
- Math
- def booleanMask[T](input: ops.Output[T], mask: ops.Output[Boolean], name: String = "BooleanMask")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Masking
- def broadcastGradientArguments[I](shape1: ops.Output[I], shape2: ops.Output[I], name: String = "BroadcastGradientArguments")(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): (ops.Output[I], ops.Output[I])
- Definition Classes
- Basic
- def broadcastShapeDynamic[I](shape1: ops.Output[I], shape2: ops.Output[I], name: String = "BroadcastShape")(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[I]
- Definition Classes
- Basic
- def broadcastTo[T, I](value: ops.Output[T], shape: ops.Output[I], name: String = "BroadcastTo")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Basic
- def bucketize[T](input: ops.Output[T], boundaries: Seq[Float], name: String = "Bucketize")(implicit arg0: core.types.TF[T], arg1: core.types.IsIntOrLongOrFloatOrDouble[T]): ops.Output[T]
- Definition Classes
- Math
- def callback[IT, IV, OT, OV, OD](function: (IV) => OV, input: IT, outputDataType: OD, stateful: Boolean = true, name: String = "Callback")(implicit arg0: OutputStructure[IT], evOutputToTensorI: Aux[IT, IV], evTensorToOutputO: Aux[OV, OT], evOutputToDataType: Aux[OT, OD]): OT
- Definition Classes
- Callback
- def cases[T](predicateFnPairs: Seq[(ops.Output[Boolean], () => T)], default: () => T, exclusive: Boolean = false, name: String = "Cases")(implicit evCondArgT: CondArg[T]): T
- Definition Classes
- ControlFlow
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidDataTypeException])
- def castGradient[T, R](op: ops.Op[ops.Output[T], ops.Output[R]], outputGradient: ops.Output[R])(implicit arg0: core.types.TF[R]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Cast
- def ceil[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Ceil")(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def checkNumerics[T](input: ops.Output[T], message: String = "", name: String = "CheckNumerics")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- Basic
- def checkNumericsGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Basic
- def clipByAverageNorm[T](input: ops.Output[T], clipNorm: ops.Output[T], name: String = "ClipByAverageNorm")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Clip
- def clipByGlobalNorm[T](inputs: Seq[ops.OutputLike[T]], clipNorm: ops.Output[T], globalNorm: ops.Output[T] = null, name: String = "ClipByGlobalNorm")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): (Seq[ops.OutputLike[T]], ops.Output[T])
- Definition Classes
- Clip
- def clipByNorm[T, I](input: ops.Output[T], clipNorm: ops.Output[T], axes: ops.Output[I] = null, name: String = "ClipByNorm")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Clip
- def clipByValue[T](input: ops.Output[T], clipValueMin: ops.Output[T], clipValueMax: ops.Output[T], name: String = "ClipByValue")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Clip
- def clipByValueGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Clip
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- def colocateWith[R](colocationOps: Set[ops.UntypedOp], ignoreExisting: Boolean = false)(block: => R): R
- Definition Classes
- API
- def complexDouble(real: ops.Output[Double], imag: ops.Output[Double], name: String = "Complex"): ops.Output[core.types.ComplexDouble]
- Definition Classes
- Math
- def complexDoubleGradient(op: ops.Op[(ops.Output[Double], ops.Output[Double]), ops.Output[core.types.ComplexDouble]], outputGradient: ops.Output[core.types.ComplexDouble]): (ops.Output[Double], ops.Output[Double])
- Definition Classes
- Math
- def complexFloat(real: ops.Output[Float], imag: ops.Output[Float], name: String = "Complex"): ops.Output[core.types.ComplexFloat]
- Definition Classes
- Math
- def complexFloatGradient(op: ops.Op[(ops.Output[Float], ops.Output[Float]), ops.Output[core.types.ComplexFloat]], outputGradient: ops.Output[core.types.ComplexFloat]): (ops.Output[Float], ops.Output[Float])
- Definition Classes
- Math
- def concatenate[T](inputs: Seq[ops.Output[T]], axis: ops.Output[Int] = 0, name: String = "Concatenate")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Manipulation
- def concatenateGradient[T](op: ops.Op[(Seq[ops.Output[T]], ops.Output[Int]), ops.Output[T]], outputGradient: ops.OutputLike[T])(implicit arg0: core.types.TF[T]): (Seq[ops.OutputLike[T]], ops.Output[Int])
- Attributes
- protected
- Definition Classes
- Manipulation
- def cond[T](predicate: ops.Output[Boolean], trueFn: () => T, falseFn: () => T, name: String = "Cond")(implicit evCondArgT: CondArg[T]): T
- Definition Classes
- ControlFlow
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidDataTypeException])
- def conjugate[T, OL[A] <: ops.OutputLike[A]](input: OL[T], name: String = "Conjugate")(implicit arg0: core.types.TF[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def conjugateGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def conjugateTransposeGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def constant[T](tensor: tensors.Tensor[T], shape: core.Shape = null, name: String = "Constant"): ops.Output[T]
- Definition Classes
- Constructors
- def conv2D[T](input: ops.Output[T], filter: ops.Output[T], stride1: Long, stride2: Long, padding: ConvPaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, dilations: (Int, Int, Int, Int) = (1, 1, 1, 1), useCuDNNOnGPU: Boolean = true, name: String = "Conv2D")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- NN
- def conv2DBackpropFilter[T](input: ops.Output[T], filterSizes: ops.Output[Int], outputGradient: ops.Output[T], stride1: Long, stride2: Long, padding: ConvPaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, dilations: (Int, Int, Int, Int) = (1, 1, 1, 1), useCuDNNOnGPU: Boolean = true, name: String = "Conv2DBackpropFilter")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- NN
- def conv2DBackpropInput[T](inputSizes: ops.Output[Int], filter: ops.Output[T], outputGradient: ops.Output[T], stride1: Long, stride2: Long, padding: ConvPaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, dilations: (Int, Int, Int, Int) = (1, 1, 1, 1), useCuDNNOnGPU: Boolean = true, name: String = "Conv2DBackpropInput")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- NN
- def conv2DGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- NN
- def cos[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Cos")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def cosGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def cosh[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Cosh")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def coshGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def countNonZero[T, I](input: ops.Output[T], axes: ops.Output[I] = null, keepDims: Boolean = false, name: String = "CountNonZero")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[Long]
- Definition Classes
- Math
- def countNonZeroSparse[T, OL[A] <: ops.OutputLike[A]](input: OL[T], name: String = "CountNonZero")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[Long]
- Definition Classes
- Math
- def createWith[R](graph: Graph = null, nameScope: String = null, device: String = "", deviceFunction: Option[(OpSpecification) => String] = None, colocationOps: Set[ops.UntypedOp] = null, controlDependencies: Set[ops.UntypedOp] = null, attributes: Map[String, Any] = null, container: String = null)(block: => R): R
- Definition Classes
- API
- def crelu[T](input: ops.Output[T], axis: ops.Output[Int] = -1, name: String = "CReLU")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): ops.Output[T]
- Definition Classes
- NN
- def cross[T](a: ops.Output[T], b: ops.Output[T], name: String = "Cross")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): ops.Output[T]
- Definition Classes
- Math
- def crossGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def cumprod[T, I](input: ops.Output[T], axis: ops.Output[I], exclusive: Boolean = false, reverse: Boolean = false, name: String = "Cumprod")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def cumprodGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Math
- def cumsum[T, I](input: ops.Output[T], axis: ops.Output[I], exclusive: Boolean = false, reverse: Boolean = false, name: String = "Cumsum")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def cumsumGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Math
- def currentAttributes: Map[String, Any]
- Definition Classes
- API
- def currentColocationOps: Set[ops.UntypedOp]
- Definition Classes
- API
- def currentContainer: String
- Definition Classes
- API
- def currentControlDependencies: Set[ops.UntypedOp]
- Definition Classes
- API
- def currentDevice: String
- Definition Classes
- API
- def currentDeviceFunction: (OpSpecification) => String
- Definition Classes
- API
- def currentGraph: Graph
- Definition Classes
- API
- def currentGraphRandomSeed(opSeed: Option[Int] = None): (Option[Int], Option[Int])
- Definition Classes
- API
- def currentNameScope: String
- Definition Classes
- API
- def currentVariableGetters: Seq[VariableGetter]
- Definition Classes
- API
- def currentVariableScope: VariableScope
- Definition Classes
- API
- def currentVariableStore: VariableStore
- Definition Classes
- API
- def decodeBase64(input: ops.Output[String], name: String = "DecodeBase64"): ops.Output[String]
- Definition Classes
- Text
- def decodeCSV[T](records: ops.Output[String], recordDefaults: Seq[ops.Output[T]], dataTypes: Seq[core.types.DataType[T]], delimiter: String = ",", useQuoteDelimiters: Boolean = true, name: String = "DecodeCSV")(implicit arg0: core.types.TF[T]): Seq[ops.Output[T]]
- Definition Classes
- Parsing
- def decodeJSONExample(jsonExamples: ops.Output[String], name: String = "DecodeJSONExample"): ops.Output[String]
- Definition Classes
- Parsing
- def decodeRaw[T](bytes: ops.Output[String], littleEndian: Boolean = true, name: String = "DecodeRaw")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Parsing
- def decodeTensor[T](data: ops.Output[String], name: String = "DecodeTensor")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Parsing
- def deepCopy[T](x: ops.Output[T], name: String = "DeepCopy")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Inplace
- def depthToSpace[T](input: ops.Output[T], blockSize: Int, dataFormat: CNNDataFormat = CNNDataFormat.default, name: String = "DepthToSpace")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Manipulation
- def depthToSpaceGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Manipulation
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.jni.InvalidArgumentException])
- def device[R](device: String = "", deviceFunction: Option[(OpSpecification) => String] = None)(block: => R): R
- Definition Classes
- API
- def diag[T](diagonal: ops.Output[T], name: String = "Diag")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def diagGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def diagPart[T](input: ops.Output[T], name: String = "DiagPart")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def diagPartGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def digamma[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Digamma")(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def digammaGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): ops.Output[T]
- Definition Classes
- Math
- def divide[T](x: ops.Output[T], y: ops.Output[T], name: String = "Divide")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def divideGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def dropout[T, I](input: ops.Output[T], keepProbability: Float, scaleOutput: Boolean = true, noiseShape: ops.Output[I] = null, seed: Option[Int] = None, name: String = "Dropout")(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- NN
- Annotations
- @throws(scala.this.throws.<init>$default$1[IllegalArgumentException])
- def dynamicDropout[T, I](input: ops.Output[T], keepProbability: ops.Output[T], scaleOutput: Boolean = true, noiseShape: ops.Output[I] = null, seed: Option[Int] = None, name: String = "Dropout")(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- NN
- def dynamicPartition[T](data: ops.Output[T], partitions: ops.Output[Int], numberOfPartitions: Int, name: String = "DynamicPartition")(implicit arg0: core.types.TF[T]): Seq[ops.Output[T]]
- Definition Classes
- DataFlow
- def dynamicPartitionGradient[T](op: ops.Op[(ops.Output[T], ops.Output[Int]), Seq[ops.Output[T]]], outputGradient: Seq[ops.Output[T]])(implicit arg0: core.types.TF[T]): (ops.Output[T], ops.Output[Int])
- Attributes
- protected
- Definition Classes
- DataFlow
- def dynamicRNN[Out, State, OutShape, StateShape](cell: ops.rnn.cell.RNNCell[Out, State, OutShape, StateShape], input: Out, initialState: Option[State] = None, timeMajor: Boolean = false, parallelIterations: Int = 32, swapMemory: Boolean = false, sequenceLengths: ops.Output[Int] = null, name: String = "RNN")(implicit arg0: OutputStructure[Out], arg1: OutputStructure[State], evZeroOut: Aux[Out, OutShape], evZeroState: Aux[State, StateShape]): Tuple[Out, State]
- Definition Classes
- RNN
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidShapeException]) @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def dynamicStitch[T](indices: Seq[ops.Output[Int]], data: Seq[ops.Output[T]], name: String = "DynamicStitch")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- DataFlow
- def dynamicStitchGradient[T](op: ops.Op[(Seq[ops.Output[Int]], Seq[ops.Output[T]]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T]): (Seq[ops.Output[Int]], Seq[ops.Output[T]])
- Attributes
- protected
- Definition Classes
- DataFlow
- def editDistance[T](hypothesis: ops.SparseOutput[T], truth: ops.SparseOutput[T], normalize: Boolean = true, name: String = "EditDistance")(implicit arg0: core.types.TF[T]): ops.Output[Float]
- Definition Classes
- Basic
- def elu[T, OL[A] <: ops.OutputLike[A]](input: OL[T], name: String = "ELU")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- NN
- def eluGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def eluHessian[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- NN
- def embeddingLookup[T, I](parameters: EmbeddingMap[T], ids: ops.Output[I], partitionStrategy: PartitionStrategy = ModStrategy, transformFn: (ops.Output[T]) => ops.Output[T] = null, maxNorm: ops.Output[T] = null, name: String = "EmbeddingLookup")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Embedding
- def empty[T](shape: ops.Output[Int], initialize: Boolean = false, name: String = "Empty")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Constructors
- def emptyLike[T](input: ops.Output[T], initialize: Boolean = false, optimize: Boolean = true, name: String = "EmptyLike")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Constructors
- def encodeBase64(input: ops.Output[String], pad: Boolean = false, name: String = "EncodeBase64"): ops.Output[String]
- Definition Classes
- Text
- def encodeTensor[T](tensor: ops.Output[T], name: String = "EncodeTensor")(implicit arg0: core.types.TF[T]): ops.Output[String]
- Definition Classes
- Parsing
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equal[T](x: ops.Output[T], y: ops.Output[T], name: String = "Equal")(implicit arg0: core.types.TF[T]): ops.Output[Boolean]
- Definition Classes
- Math
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- def erf[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Erf")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def erfGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def erfc[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Erfc")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def erfcGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def exp[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Exp")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def expGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def expandDims[T, I](input: ops.Output[T], axis: ops.Output[I], name: String = "ExpandDims")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def expandDimsGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def expm1[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Expm1")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def expm1Gradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def fill[T, I](dataType: core.types.DataType[T], shape: ops.Output[I])(value: ops.Output[T])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Constructors
- def fill[T, I](shape: ops.Output[I])(value: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Constructors
- def fillGradient[T, I](op: ops.Op[(ops.Output[I], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[I], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Constructors
- def floor[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Floor")(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def floorMod[T](x: ops.Output[T], y: ops.Output[T], name: String = "FloorMod")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def fusedBatchNormalization[T](x: ops.Output[T], scale: ops.Output[Float], offset: ops.Output[Float], mean: Option[ops.Output[Float]] = None, variance: Option[ops.Output[Float]] = None, epsilon: Float = 0.0001f, dataFormat: CNNDataFormat = NWCFormat, isTraining: Boolean = true, name: String = "FusedBatchNormalization")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): (ops.Output[T], ops.Output[Float], ops.Output[Float], ops.Output[Float], ops.Output[Float])
- Definition Classes
- NN
- Annotations
- @throws(scala.this.throws.<init>$default$1[IllegalArgumentException])
- def fusedBatchNormalizationGradient[T](op: ops.Op[(ops.Output[T], ops.Output[Float], ops.Output[Float], ops.Output[Float], ops.Output[Float]), (ops.Output[T], ops.Output[Float], ops.Output[Float], ops.Output[Float], ops.Output[Float])], outputGradient: (ops.Output[T], ops.Output[Float], ops.Output[Float], ops.Output[Float], ops.Output[Float]))(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): (ops.Output[T], ops.Output[Float], ops.Output[Float], ops.Output[Float], ops.Output[Float])
- Attributes
- protected
- Definition Classes
- NN
- def gather[T, I1, I2](input: ops.Output[T], indices: ops.Output[I1], axis: ops.Output[I2] = null, name: String = "Gather")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I1], arg2: core.types.IsIntOrLong[I1], arg3: IntDefault[I2], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Manipulation
- def gatherDropNegatives[T, I](parameters: ops.Output[T], indices: ops.Output[I], zeroClippedIndices: ops.Output[I] = null, isPositive: ops.Output[Boolean] = null)(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I], ops.Output[Boolean])
- Attributes
- protected
- Definition Classes
- Math
- def gatherGradient[T, I1, I2](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[I2]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I1], arg2: core.types.IsIntOrLong[I1], arg3: core.types.TF[I2], arg4: core.types.IsIntOrLong[I2]): (ops.OutputLike[T], ops.Output[I1], ops.Output[I2])
- Attributes
- protected
- Definition Classes
- Manipulation
- def gatherND[T, I](input: ops.Output[T], indices: ops.Output[I], name: String = "GatherND")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def gatherNDGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.OutputLike[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def globalNorm[T](inputs: Seq[ops.OutputLike[T]], name: String = "GlobalNorm")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- Clip
- def globalVariablesInitializer(name: String = "GlobalVariablesInitializer"): ops.UntypedOp
- Definition Classes
- API
- val gradients: Gradients.type
- Definition Classes
- API
- def greater[T](x: ops.Output[T], y: ops.Output[T], name: String = "Greater")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[Boolean]
- Definition Classes
- Math
- def greaterEqual[T](x: ops.Output[T], y: ops.Output[T], name: String = "GreaterEqual")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[Boolean]
- Definition Classes
- Math
- def group(inputs: Set[ops.UntypedOp], name: String = "Group"): ops.Op[Unit, Unit]
- Definition Classes
- ControlFlow
- def guaranteeConstant[T](input: ops.Output[T], name: String = "GuaranteeConstant"): ops.Output[T]
- Definition Classes
- Constructors
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def identity[T, OL[A] <: ops.OutputLike[A]](input: OL[T], name: String = "Identity")(implicit arg0: core.types.TF[T]): OL[T]
- Definition Classes
- Manipulation
- def igamma[T](a: ops.Output[T], x: ops.Output[T], name: String = "Igamma")(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): ops.Output[T]
- Definition Classes
- Math
- def igammaGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def igammac[T](a: ops.Output[T], x: ops.Output[T], name: String = "Igammac")(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): ops.Output[T]
- Definition Classes
- Math
- def igammacGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def imagDouble[OL[A] <: ops.OutputLike[A]](input: OL[core.types.ComplexDouble], name: String = "Imag")(implicit ev: Aux[OL, core.types.ComplexDouble]): OL[Double]
- Definition Classes
- Math
- def imagDoubleGradient(op: ops.Op[ops.Output[core.types.ComplexDouble], ops.Output[Double]], outputGradient: ops.Output[Double]): ops.Output[core.types.ComplexDouble]
- Attributes
- protected
- Definition Classes
- Math
- def imagFloat[OL[A] <: ops.OutputLike[A]](input: OL[core.types.ComplexFloat], name: String = "Imag")(implicit ev: Aux[OL, core.types.ComplexFloat]): OL[Float]
- Definition Classes
- Math
- def imagFloatGradient(op: ops.Op[ops.Output[core.types.ComplexFloat], ops.Output[Float]], outputGradient: ops.Output[Float]): ops.Output[core.types.ComplexFloat]
- Attributes
- protected
- Definition Classes
- Math
- def immutableConstant[T](shape: core.Shape, memoryRegionName: String, name: String = "ImmutableConstant")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Constructors
- def inTopK[I](predictions: ops.Output[Float], targets: ops.Output[I], k: ops.Output[I], name: String = "InTopK")(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[Boolean]
- Definition Classes
- NN
- def incompleteBeta[T](a: ops.Output[T], b: ops.Output[T], x: ops.Output[T], name: String = "IncompleteBeta")(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): ops.Output[T]
- Definition Classes
- Math
- def incompleteBetaGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): (ops.Output[T], ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def indexTableFromFile[K](filename: String, keysDataType: core.types.DataType[K], delimiter: String = "\t", vocabularySize: Int = -1, defaultValue: Long = -1L, numOOVBuckets: Int = 0, hashSpecification: HashSpecification = FAST_HASH, name: String = "IndexTableFromFile")(implicit arg0: core.types.TF[K], arg1: core.types.IsStringOrInteger[K]): ops.lookup.LookupTable[K, Long]
- Definition Classes
- Lookup
- def indexedSlicesMask[T](input: ops.OutputIndexedSlices[T], maskIndices: ops.Output[Int], name: String = "IndexedSlicesMask")(implicit arg0: core.types.TF[T]): ops.OutputIndexedSlices[T]
- Definition Classes
- Masking
- def initializationScope[R](block: => R): R
- Definition Classes
- API
- def inplaceAdd[T](x: ops.Output[T], i: Option[ops.Output[Int]], v: ops.Output[T], name: String = "InplaceAdd")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Inplace
- def inplaceSubtract[T](x: ops.Output[T], i: Option[ops.Output[Int]], v: ops.Output[T], name: String = "InplaceSubtract")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Inplace
- def inplaceUpdate[T](x: ops.Output[T], i: Option[ops.Output[Int]], v: ops.Output[T], name: String = "InplaceUpdate")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Inplace
- def invertPermutation[I](input: ops.Output[I], name: String = "InvertPermutation")(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[I]
- Definition Classes
- Manipulation
- def isFinite[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "IsFinite")(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[OL, T]): OL[Boolean]
- Definition Classes
- Math
- def isInf[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "IsInf")(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[OL, T]): OL[Boolean]
- Definition Classes
- Math
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def isNaN[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "IsNaN")(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[OL, T]): OL[Boolean]
- Definition Classes
- Math
- def l2Loss[T](input: ops.Output[T], name: String = "L2Loss")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- NN
- def l2LossGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def l2Normalize[T, I](x: ops.Output[T], axes: ops.Output[I], epsilon: Float = 1e-12f, name: String = "L2Normalize")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- NN
- def less[T](x: ops.Output[T], y: ops.Output[T], name: String = "Less")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[Boolean]
- Definition Classes
- Math
- def lessEqual[T](x: ops.Output[T], y: ops.Output[T], name: String = "LessEqual")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[Boolean]
- Definition Classes
- Math
- def linear[T](x: ops.Output[T], weights: ops.Output[T], bias: ops.Output[T] = null, name: String = "Linear")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- NN
- def linspace[T, I](start: ops.Output[T], stop: ops.Output[T], numberOfValues: ops.Output[I], name: String = "LinSpace")(implicit arg0: core.types.TF[T], arg1: core.types.IsTruncatedHalfOrFloatOrDouble[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def listDiff[T, I](x: ops.Output[T], y: ops.Output[T], indicesDataType: core.types.DataType[I], name: String = "ListDiff")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Definition Classes
- Masking
- def localResources: Set[ResourceWrapper]
- Definition Classes
- Resources
- def localResponseNormalization[T](input: ops.Output[T], depthRadius: Int = 5, bias: Float = 1.0f, alpha: Float = 1.0f, beta: Float = 0.5f, name: String = "LocalResponseNormalization")(implicit arg0: core.types.TF[T], arg1: core.types.IsTruncatedHalfOrHalfOrFloat[T]): ops.Output[T]
- Definition Classes
- NN
- def localVariable[T](name: String, shape: core.Shape = null, initializer: VariableInitializer = null, regularizer: VariableRegularizer = null, reuse: Reuse = ReuseOrCreateNew, collections: Set[Key[Variable[Any]]] = Set.empty, cachingDevice: (ops.OpSpecification) => String = null)(implicit arg0: core.types.TF[T]): Variable[T]
- Definition Classes
- API
- def localVariablesInitializer(name: String = "LocalVariablesInitializer"): ops.UntypedOp
- Definition Classes
- API
- def log[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Log")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def log1p[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Log1p")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def log1pGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def logGamma[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "LogGamma")(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def logGammaGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def logGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def logPoissonLoss[T](logPredictions: ops.Output[T], targets: ops.Output[T], computeFullLoss: Boolean = false, name: String = "LogPoissonLoss")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- NN
- def logSigmoid[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "LogSigmoid")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def logSoftmax[T](logits: ops.Output[T], axis: Int = -1, name: String = "LogSoftmax")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- NN
- def logSoftmaxGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def logSumExp[T, I](input: ops.Output[T], axes: ops.Output[I] = null, keepDims: Boolean = false, name: String = "LogSumExp")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def logicalAnd(x: ops.Output[Boolean], y: ops.Output[Boolean], name: String = "LogicalAnd"): ops.Output[Boolean]
- Definition Classes
- Math
- def logicalNot(x: ops.Output[Boolean], name: String = "LogicalNot"): ops.Output[Boolean]
- Definition Classes
- Math
- def logicalOr(x: ops.Output[Boolean], y: ops.Output[Boolean], name: String = "LogicalOr"): ops.Output[Boolean]
- Definition Classes
- Math
- def logicalXOr(x: ops.Output[Boolean], y: ops.Output[Boolean], name: String = "LogicalXOr"): ops.Output[Boolean]
- Definition Classes
- Math
- def lrn[T](input: ops.Output[T], depthRadius: Int = 5, bias: Float = 1.0f, alpha: Float = 1.0f, beta: Float = 0.5f, name: String = "LRN")(implicit arg0: core.types.TF[T], arg1: core.types.IsTruncatedHalfOrHalfOrFloat[T]): ops.Output[T]
- Definition Classes
- NN
- def lrnGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsTruncatedHalfOrHalfOrFloat[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def magnitudeDouble[OL[A] <: ops.OutputLike[A]](x: OL[core.types.ComplexDouble], name: String = "Magnitude")(implicit ev: Aux[OL, core.types.ComplexDouble]): OL[Double]
- Definition Classes
- Math
- def magnitudeDoubleGradient(op: ops.Op[ops.Output[core.types.ComplexDouble], ops.Output[Double]], outputGradient: ops.Output[Double]): ops.Output[core.types.ComplexDouble]
- Attributes
- protected
- Definition Classes
- Math
- def magnitudeFloat[OL[A] <: ops.OutputLike[A]](x: OL[core.types.ComplexFloat], name: String = "Magnitude")(implicit ev: Aux[OL, core.types.ComplexFloat]): OL[Float]
- Definition Classes
- Math
- def magnitudeFloatGradient(op: ops.Op[ops.Output[core.types.ComplexFloat], ops.Output[Float]], outputGradient: ops.Output[Float]): ops.Output[core.types.ComplexFloat]
- Attributes
- protected
- Definition Classes
- Math
- def matmul[T](a: ops.Output[T], b: ops.Output[T], transposeA: Boolean = false, transposeB: Boolean = false, conjugateA: Boolean = false, conjugateB: Boolean = false, aIsSparse: Boolean = false, bIsSparse: Boolean = false, name: String = "MatMul")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def matmulGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def matrixBandPart[T, I](input: ops.Output[T], numSubDiagonals: ops.Output[I], numSuperDiagonals: ops.Output[I], name: String = "MatrixBandPart")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def matrixBandPartGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Math
- def matrixDiag[T](diagonal: ops.Output[T], name: String = "MatrixDiag")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Math
- def matrixDiagGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def matrixDiagPart[T](input: ops.Output[T], name: String = "MatrixDiagPart")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Math
- def matrixDiagPartGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def matrixSetDiag[T](input: ops.Output[T], diagonal: ops.Output[T], name: String = "MatrixSetDiag")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Math
- def matrixSetDiagGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def matrixTranspose[T](input: ops.Output[T], conjugate: Boolean = false, name: String = "MatrixTranspose")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Manipulation
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidShapeException])
- def max[T, I](input: ops.Output[T], axes: ops.Output[I] = null, keepDims: Boolean = false, name: String = "Max")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def maxPool[T](input: ops.Output[T], windowSize: ops.Output[Int], strides: ops.Output[Int], padding: ConvPaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, name: String = "MaxPool")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[T]
- Definition Classes
- NN
- def maxPoolGrad[T](originalInput: ops.Output[T], originalOutput: ops.Output[T], outputGradient: ops.Output[T], windowSize: ops.Output[Int], strides: ops.Output[Int], padding: ConvPaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, name: String = "MaxPoolGrad")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[T]
- Definition Classes
- NN
- def maxPoolGradGrad[T](originalInput: ops.Output[T], originalOutput: ops.Output[T], outputGradient: ops.Output[T], windowSize: ops.Output[Int], strides: ops.Output[Int], padding: ConvPaddingMode, dataFormat: CNNDataFormat = CNNDataFormat.default, name: String = "MaxPoolGradGrad")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[T]
- Definition Classes
- NN
- def maxPoolGradient[T](op: ops.Op[(ops.Output[T], ops.Output[Int], ops.Output[Int]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): (ops.Output[T], ops.Output[Int], ops.Output[Int])
- Attributes
- protected
- Definition Classes
- NN
- def maxPoolHessian[T](op: ops.Op[(ops.Output[T], ops.Output[T], ops.Output[T], ops.Output[Int], ops.Output[Int]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): (ops.Output[T], ops.Output[T], ops.Output[T], ops.Output[Int], ops.Output[Int])
- Attributes
- protected
- Definition Classes
- NN
- def maxPoolHessianGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T], ops.Output[T], ops.Output[Int], ops.Output[Int]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): (ops.Output[T], ops.Output[T], ops.Output[T], ops.Output[Int], ops.Output[Int])
- Attributes
- protected
- Definition Classes
- NN
- def maximum[T](x: ops.Output[T], y: ops.Output[T], name: String = "Maximum")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def maximumGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def mean[T, I](input: ops.Output[T], axes: ops.Output[I] = null, keepDims: Boolean = false, name: String = "Mean")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def meanGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Math
- def meshGrid[T](inputs: Seq[ops.Output[T]], useCartesianIndexing: Boolean = true, name: String = "MeshGrid")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Seq[ops.Output[T]]
- Definition Classes
- Basic
- def metricVariablesInitializer(name: String = "MetricVariablesInitializer"): ops.UntypedOp
- Definition Classes
- API
- def min[T, I](input: ops.Output[T], axes: ops.Output[I] = null, keepDims: Boolean = false, name: String = "Min")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def minOrMaxGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Math
- def minimum[T](x: ops.Output[T], y: ops.Output[T], name: String = "Minimum")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def minimumGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def mirrorPadGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def mirrorPadHessian[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def mod[T](x: ops.Output[T], y: ops.Output[T], name: String = "Mod")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def modelVariablesInitializer(name: String = "ModelVariablesInitializer"): ops.UntypedOp
- Definition Classes
- API
- def moments[T](input: ops.Output[T], axes: Seq[Int], weights: ops.Output[T] = null, keepDims: Boolean = false, name: String = "Moments")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Definition Classes
- Statistics
- def momentsFromSufficientStatistics[T](counts: ops.Output[T], meanSS: ops.Output[T], varSS: ops.Output[T], shift: ops.Output[T] = null, name: String = "MomentsFromSufficientStatistics")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Definition Classes
- Statistics
- def multiply[T](x: ops.Output[T], y: ops.Output[T], name: String = "Multiply")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def multiplyGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def nameScope[R](nameScope: String)(block: => R): R
- Definition Classes
- API
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def negate[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Negate")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def negateGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def newStack(maxSize: ops.Output[Int], elementType: core.types.DataType[Any], stackName: String = "", name: String = "NewStack"): ops.Output[core.types.Resource]
- Definition Classes
- DataFlow
- def noOp(name: String = "NoOp"): ops.Op[Unit, Unit]
- Definition Classes
- ControlFlow
- def notEqual[T](x: ops.Output[T], y: ops.Output[T], name: String = "NotEqual")(implicit arg0: core.types.TF[T]): ops.Output[Boolean]
- Definition Classes
- Math
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def oneHot[T, I](indices: ops.Output[I], depth: ops.Output[Int], onValue: ops.Output[T] = null, offValue: ops.Output[T] = null, axis: Int = -1, name: String = "OneHot")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLongOrUByte[I]): ops.Output[T]
- Definition Classes
- Basic
- def ones[T, I](dataType: core.types.DataType[T], shape: ops.Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Constructors
- def ones[T](dataType: core.types.DataType[T], shape: ops.Output[Int]): ops.Output[T]
- Definition Classes
- Constructors
- def ones[T, I](shape: ops.Output[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Constructors
- def ones[T](shape: ops.Output[Int])(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Constructors
- def onesLike[T](input: ops.Output[T], optimize: Boolean = true, name: String = "OnesLike"): ops.Output[T]
- Definition Classes
- Constructors
- def pad[T, I](input: ops.Output[T], paddings: ops.Output[I], mode: ops.basic.Manipulation.PaddingMode = Manipulation.ConstantPadding(Some(Tensor(0).reshape(Shape()))), name: String = "Pad")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def padGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Manipulation
- def parallelStack[T](inputs: Seq[ops.Output[T]], name: String = "ParallelStack")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Manipulation
- def parseExample[T, R](serialized: ops.Output[String], features: T, debugNames: ops.Output[String] = Tensor.fill[String](Shape())("").toOutput, name: String = "ParseExample")(implicit ev: Aux[T, R]): R
- Definition Classes
- Parsing
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def parseSingleExample[T, R](serialized: ops.Output[String], features: T, name: String = "ParseSingleExample")(implicit ev: Aux[T, R]): R
- Definition Classes
- Parsing
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def placeholder[T](shape: core.Shape = null, name: String = "Placeholder")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Constructors
- def placeholderWithDefault[T](default: ops.Output[T], shape: core.Shape, name: String = "PlaceholderWithDefault")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Constructors
- def polygamma[T](n: ops.Output[T], x: ops.Output[T], name: String = "Polygamma")(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): ops.Output[T]
- Definition Classes
- Math
- def polygammaGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def pow[T](x: ops.Output[T], y: ops.Output[T], name: String = "Pow")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def powGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def preventGradient[T](input: ops.Output[T], message: String = "", name: String = "PreventGradient")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Basic
- def preventGradientGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradients: ops.Output[T])(implicit arg0: core.types.TF[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Basic
- Annotations
- @throws(scala.this.throws.<init>$default$1[IllegalArgumentException])
- def print[T, OL[A] <: ops.OutputLike[A]](input: OL[T], data: Seq[ops.Output[Any]], message: String = "", firstN: Int = -1, summarize: Int = 3, name: String = "Print")(implicit arg0: core.types.TF[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Logging
- def printGradient[T](op: ops.Op[(ops.Output[T], Seq[ops.Output[Any]]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T]): (ops.Output[T], Seq[ops.Output[Any]])
- Attributes
- protected
- Definition Classes
- Logging
- def prod[T, I](input: ops.Output[T], axes: ops.Output[I] = null, keepDims: Boolean = false, name: String = "Prod")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def prodGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Definition Classes
- Math
- def randomNormal[T, I](shape: ops.Output[I], mean: ops.Output[T] = null, standardDeviation: ops.Output[T] = null, seed: Option[Int] = None, name: String = "RandomNormal")(implicit arg0: FloatDefault[T], arg1: core.types.TF[T], arg2: core.types.IsHalfOrFloatOrDouble[T], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Random
- def randomShuffle[T](value: ops.Output[T], seed: Option[Int] = None, name: String = "RandomShuffle")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Random
- def randomTruncatedNormal[T, I](shape: ops.Output[I], mean: ops.Output[T] = null, standardDeviation: ops.Output[T] = null, seed: Option[Int] = None, name: String = "RandomTruncatedNormal")(implicit arg0: FloatDefault[T], arg1: core.types.TF[T], arg2: core.types.IsHalfOrFloatOrDouble[T], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Random
- def randomUniform[T, I](shape: ops.Output[I], minValue: ops.Output[T] = null, maxValue: ops.Output[T] = null, seed: Option[Int] = None, name: String = "RandomUniform")(implicit arg0: FloatDefault[T], arg1: core.types.TF[T], arg2: core.types.IsIntOrLongOrHalfOrFloatOrDouble[T], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Random
- def range[T](start: ops.Output[T], limit: ops.Output[T], delta: ops.Output[T] = null, name: String = "Range")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[T]
- Definition Classes
- Math
- def rank[T, OL[A] <: ops.OutputLike[A]](input: OL[T], optimize: Boolean = true, name: String = "Rank")(implicit arg0: core.types.TF[T]): ops.Output[Int]
- Definition Classes
- Manipulation
- def realDivide[T](x: ops.Output[T], y: ops.Output[T], name: String = "RealDivide")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def realDivideGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def realDouble[OL[A] <: ops.OutputLike[A]](input: OL[core.types.ComplexDouble], name: String = "Real")(implicit ev: Aux[OL, core.types.ComplexDouble]): OL[Double]
- Definition Classes
- Math
- def realDoubleGradient(op: ops.Op[ops.Output[core.types.ComplexDouble], ops.Output[Double]], outputGradient: ops.Output[Double]): ops.Output[core.types.ComplexDouble]
- Attributes
- protected
- Definition Classes
- Math
- def realFloat[OL[A] <: ops.OutputLike[A]](input: OL[core.types.ComplexFloat], name: String = "Real")(implicit ev: Aux[OL, core.types.ComplexFloat]): OL[Float]
- Definition Classes
- Math
- def realFloatGradient(op: ops.Op[ops.Output[core.types.ComplexFloat], ops.Output[Float]], outputGradient: ops.Output[Float]): ops.Output[core.types.ComplexFloat]
- Attributes
- protected
- Definition Classes
- Math
- def reciprocal[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Reciprocal")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def reciprocalGradient[T](op: ops.Op[ops.OutputLike[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.OutputLike[T]
- Attributes
- protected
- Definition Classes
- Math
- def reciprocalHessian[T](op: ops.Op[(ops.Output[T], ops.OutputLike[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.OutputLike[T])
- Attributes
- protected
- Definition Classes
- Math
- def reductionAxes[T, I, OL[A] <: ops.OutputLike[A]](tensor: OL[T], axes: ops.Output[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[I]
- Attributes
- protected
- Definition Classes
- Math
- def regexReplace(input: ops.Output[String], pattern: ops.Output[String], rewrite: ops.Output[String], replaceGlobal: Boolean = true, name: String = "RegexReplace"): ops.Output[String]
- Definition Classes
- Text
- def relu[T](input: ops.Output[T], alpha: Float = 0.0f, name: String = "ReLU")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): ops.Output[T]
- Definition Classes
- NN
- def relu6[T, OL[A] <: ops.OutputLike[A]](input: OL[T], name: String = "ReLU6")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- NN
- def relu6Gradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def relu6Hessian[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- NN
- def reluGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def reluHessian[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- NN
- def requiredSpaceToBatchPaddingsAndCrops(inputShape: ops.Output[Int], blockShape: ops.Output[Int], basePaddings: ops.Output[Int] = null, name: String = "RequiredSpaceToBatchPaddings"): (ops.Output[Int], ops.Output[Int])
- Definition Classes
- Manipulation
- def reshape[T, I](input: ops.Output[T], shape: ops.Output[I], name: String = "Reshape")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def reshapeGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def reshapeToInput[T](input: ops.Output[T], gradient: ops.Output[T])(implicit arg0: core.types.TF[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Manipulation
- def reverse[T, I](input: ops.Output[T], axes: ops.Output[I], name: String = "Reverse")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def reverseGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def reverseSequence[T, I](input: ops.Output[T], sequenceLengths: ops.Output[I], sequenceAxis: Int, batchAxis: Int = 0, name: String = "ReverseSequence")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def reverseSequenceGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def round[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Round")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def roundInt[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "RoundInt")(implicit arg0: core.types.TF[T], arg1: core.types.IsHalfOrFloatOrDouble[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def rsqrt[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Rqsrt")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def rsqrtGradient[T](op: ops.Op[ops.OutputLike[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.OutputLike[T]
- Attributes
- protected
- Definition Classes
- Math
- def rsqrtHessian[T](op: ops.Op[(ops.Output[T], ops.OutputLike[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.OutputLike[T])
- Attributes
- protected
- Definition Classes
- Math
- def safeShapeDiv(x: ops.Output[Int], y: ops.Output[Int]): ops.Output[Int]
- Attributes
- protected
- Definition Classes
- Math
- def saver(saveables: Set[Saveable] = null, reshape: Boolean = false, sharded: Boolean = false, maxToKeep: Int = 5, keepCheckpointEveryNHours: Float = 10000.0f, restoreSequentially: Boolean = false, filename: String = "model", builder: SaverDefBuilder = DefaultSaverDefBuilder, allowEmpty: Boolean = false, writerVersion: WriterVersion = V2, saveRelativePaths: Boolean = false, padGlobalStep: Boolean = false, name: String = "Saver"): Saver
- Definition Classes
- API
- def scalarMul[T, OL[A] <: ops.OutputLike[A]](scalar: ops.Output[T], tensor: OL[T], name: String = "ScalarMul")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def scatterND[T, I](indices: ops.Output[I], updates: ops.Output[T], shape: ops.Output[I], name: String = "ScatterND")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def scatterNDGradient[T, I](op: ops.Op[(ops.Output[I], ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[I], ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def segmentMax[T, I](data: ops.Output[T], segmentIndices: ops.Output[I], name: String = "SegmentMax")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def segmentMean[T, I](data: ops.Output[T], segmentIndices: ops.Output[I], name: String = "SegmentMean")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def segmentMeanGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Math
- def segmentMin[T, I](data: ops.Output[T], segmentIndices: ops.Output[I], name: String = "SegmentMin")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def segmentMinOrMaxGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Math
- def segmentProd[T, I](data: ops.Output[T], segmentIndices: ops.Output[I], name: String = "SegmentProd")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def segmentSum[T, I](data: ops.Output[T], segmentIndices: ops.Output[I], name: String = "SegmentSum")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def segmentSumGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Math
- def select[T](condition: ops.Output[Boolean], x: ops.Output[T], y: ops.Output[T], name: String = "Select")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Math
- def selectGradient[T](op: ops.Op[(ops.Output[Boolean], ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T]): (ops.Output[Boolean], ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def selu[T, OL[A] <: ops.OutputLike[A]](input: OL[T], name: String = "SELU")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- NN
- def seluGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def seluHessian[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- NN
- def sequenceLoss[T, L](logits: ops.Output[T], labels: ops.Output[L], lossFn: (ops.Output[T], ops.Output[L]) => ops.Output[T], weights: ops.Output[T] = null, averageAcrossTimeSteps: Boolean = true, averageAcrossBatch: Boolean = true, name: String = "SequenceLoss")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T], arg2: core.types.TF[L]): ops.Output[T]
- Definition Classes
- NN
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidShapeException])
- def sequenceMask[T](lengths: ops.Output[T], maxLength: ops.Output[T] = null, name: String = "SequenceMask")(implicit arg0: core.types.TF[T], arg1: core.types.IsIntOrUInt[T]): ops.Output[Boolean]
- Definition Classes
- Masking
- Annotations
- @throws(scala.this.throws.<init>$default$1[IllegalArgumentException])
- def setCurrentGraphRandomSeed(value: Int): Unit
- Definition Classes
- API
- def setDifference[A, B, T](a: A, b: B, aMinusB: Boolean = true, validateIndices: Boolean = true, name: String = "SetDifference")(implicit ev: Aux[A, B, T], evSupported: core.types.TF[T]): ops.SparseOutput[T]
- Definition Classes
- Sets
- def setIntersection[A, B, T](a: A, b: B, validateIndices: Boolean = true, name: String = "SetIntersection")(implicit ev: Aux[A, B, T], evSupported: core.types.TF[T]): ops.SparseOutput[T]
- Definition Classes
- Sets
- def setSize[T](input: ops.SparseOutput[T], validateIndices: Boolean = true, name: String = "SetSize")(implicit arg0: core.types.TF[T], arg1: core.types.IsIntOrUInt[T]): ops.Output[Int]
- Definition Classes
- Sets
- def setUnion[A, B, T](a: A, b: B, validateIndices: Boolean = true, name: String = "SetUnion")(implicit ev: Aux[A, B, T], evSupported: core.types.TF[T]): ops.SparseOutput[T]
- Definition Classes
- Sets
- def shape[T, OL[A] <: ops.OutputLike[A]](input: OL[T], optimize: Boolean = true, name: String = "Shape")(implicit arg0: core.types.TF[T]): ops.Output[Int]
- Definition Classes
- Manipulation
- def shapeFullySpecifiedAndEqual[T](x: ops.Output[T], y: ops.Output[T], gradient: ops.Output[T])(implicit arg0: core.types.TF[T]): Boolean
- Attributes
- protected
- Definition Classes
- Math
- def shapeN[T, I](inputs: Seq[ops.Output[T]], dataType: core.types.DataType[I])(implicit arg0: core.types.TF[T], arg1: core.types.IsIntOrLong[I]): Seq[ops.Output[I]]
- Definition Classes
- Manipulation
- def shapeN[T, I](inputs: Seq[ops.Output[T]])(implicit arg0: core.types.TF[T], arg1: IntDefault[I], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Seq[ops.Output[I]]
- Definition Classes
- Manipulation
- def sharedResources: Set[ResourceWrapper]
- Definition Classes
- Resources
- def sigmoid[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Sigmoid")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def sigmoidCrossEntropy[T](logits: ops.Output[T], labels: ops.Output[T], weights: ops.Output[T] = null, name: String = "SigmoidCrossEntropy")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- NN
- def sigmoidGradient[T](op: ops.Op[ops.OutputLike[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.OutputLike[T]
- Attributes
- protected
- Definition Classes
- Math
- def sigmoidHessian[T](op: ops.Op[(ops.Output[T], ops.OutputLike[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.OutputLike[T])
- Attributes
- protected
- Definition Classes
- Math
- def sign[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Sign")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def signGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def sin[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Sin")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def sinGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def sinh[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Sinh")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def sinhGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def size[T, OL[A] <: ops.OutputLike[A]](input: OL[T], optimize: Boolean = true, name: String = "Size")(implicit arg0: core.types.TF[T]): ops.Output[Long]
- Definition Classes
- Manipulation
- def slice[T, I](input: ops.Output[T], begin: ops.Output[I], size: ops.Output[I], name: String = "Slice")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def sliceGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def softmax[T](logits: ops.Output[T], axis: Int = -1, name: String = "Softmax")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- NN
- def softmaxCrossEntropy[T](logits: ops.Output[T], labels: ops.Output[T], axis: Int = -1, name: String = "SoftmaxCrossEntropy")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Definition Classes
- NN
- def softmaxCrossEntropyGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), (ops.Output[T], ops.Output[T])], outputGradient: (ops.Output[T], ops.Output[T]))(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- NN
- def softmaxGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def softmaxHelper[T](logits: ops.Output[T], opType: String, axis: Int = -1, name: String = "Softmax")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def softplus[T, OL[A] <: ops.OutputLike[A]](input: OL[T], name: String = "Softplus")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- NN
- def softplusGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def softplusHessian[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- NN
- def softsign[T, OL[A] <: ops.OutputLike[A]](input: OL[T], name: String = "Softsign")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- NN
- def softsignGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- NN
- def spaceToBatch[T, I](input: ops.Output[T], blockSize: Int, paddings: ops.Output[I], name: String = "SpaceToBatch")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def spaceToBatchND[T, I1, I2](input: ops.Output[T], blockShape: ops.Output[I1], paddings: ops.Output[I2], name: String = "SpaceToBatchND")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I1], arg2: core.types.IsIntOrLong[I1], arg3: core.types.TF[I2], arg4: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Manipulation
- def spaceToBatchNDGradient[T, I1, I2](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[I2]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I1], arg2: core.types.IsIntOrLong[I1], arg3: core.types.TF[I2], arg4: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I1], ops.Output[I2])
- Attributes
- protected
- Definition Classes
- Manipulation
- def spaceToDepth[T](input: ops.Output[T], blockSize: Int, dataFormat: CNNDataFormat = CNNDataFormat.default, name: String = "SpaceToDepth")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Manipulation
- def spaceToDepthGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Manipulation
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.jni.InvalidArgumentException])
- def sparseEmbeddingLookup[T, I](parameters: EmbeddingMap[T], sparseIds: ops.SparseOutput[I], sparseWeights: ops.SparseOutput[T] = null, partitionStrategy: PartitionStrategy = ModStrategy, combiner: Combiner = SumSqrtNCombiner, maxNorm: ops.Output[T] = null, name: String = "SparseEmbeddingLookup")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Embedding
- def sparseMatmulGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def sparsePlaceholder[T](shape: core.Shape = null, name: String = "SparsePlaceholder")(implicit arg0: core.types.TF[T]): ops.SparseOutput[T]
- Definition Classes
- Constructors
- def sparseSegmentMean[T, I1, I2](data: ops.Output[T], indices: ops.Output[I1], segmentIndices: ops.Output[Int], numSegments: ops.Output[I2] = null, name: String = "SparseSegmentMean")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: IntDefault[I2], arg5: core.types.TF[I2], arg6: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Math
- def sparseSegmentMeanGradient[T, I1](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[Int]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1]): (ops.Output[T], ops.Output[I1], ops.Output[Int])
- Attributes
- protected
- Definition Classes
- Math
- def sparseSegmentMeanWithNumSegmentsGradient[T, I1, I2](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[Int], ops.Output[I2]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I1], ops.Output[Int], ops.Output[I2])
- Attributes
- protected
- Definition Classes
- Math
- def sparseSegmentSum[T, I1, I2](data: ops.Output[T], indices: ops.Output[I1], segmentIndices: ops.Output[Int], numSegments: ops.Output[I2] = null, name: String = "SparseSegmentSum")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: IntDefault[I2], arg5: core.types.TF[I2], arg6: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Math
- def sparseSegmentSumGradient[T, I1](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[Int]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1]): (ops.Output[T], ops.Output[I1], ops.Output[Int])
- Attributes
- protected
- Definition Classes
- Math
- def sparseSegmentSumSqrtN[T, I1, I2](data: ops.Output[T], indices: ops.Output[I1], segmentIndices: ops.Output[Int], numSegments: ops.Output[I2] = null, name: String = "SparseSegmentSumSqrtN")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: IntDefault[I2], arg5: core.types.TF[I2], arg6: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Math
- def sparseSegmentSumSqrtNGradient[T, I1](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[Int]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1]): (ops.Output[T], ops.Output[I1], ops.Output[Int])
- Attributes
- protected
- Definition Classes
- Math
- def sparseSegmentSumSqrtNWithNumSegmentsGradient[T, I1, I2](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[Int], ops.Output[I2]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I1], ops.Output[Int], ops.Output[I2])
- Attributes
- protected
- Definition Classes
- Math
- def sparseSegmentSumWithNumSegmentsGradient[T, I1, I2](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[Int], ops.Output[I2]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I1], ops.Output[Int], ops.Output[I2])
- Attributes
- protected
- Definition Classes
- Math
- def sparseSoftmaxCrossEntropy[T, I](logits: ops.Output[T], labels: ops.Output[I], axis: Int = -1, name: String = "SparseSoftmaxCrossEntropy")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- NN
- def sparseSoftmaxCrossEntropyGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), (ops.Output[T], ops.Output[T])], outputGradient: (ops.Output[T], ops.Output[T]))(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- NN
- def split[T, I](input: ops.Output[T], splitSizes: ops.Output[I], axis: ops.Output[Int] = 0, name: String = "Split")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Seq[ops.Output[T]]
- Definition Classes
- Manipulation
- def splitEvenly[T](input: ops.Output[T], numSplits: Int, axis: ops.Output[Int] = 0, name: String = "Split")(implicit arg0: core.types.TF[T]): Seq[ops.Output[T]]
- Definition Classes
- Manipulation
- def splitEvenlyGradient[T](op: ops.Op[(ops.Output[Int], ops.Output[T]), Seq[ops.Output[T]]], outputGradient: Seq[ops.Output[T]])(implicit arg0: core.types.TF[T]): (ops.Output[Int], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Manipulation
- def splitGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I], ops.Output[Int]), Seq[ops.Output[T]]], outputGradient: Seq[ops.Output[T]])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I], ops.Output[Int])
- Attributes
- protected
- Definition Classes
- Manipulation
- def sqrt[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Sqrt")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def sqrtGradient[T](op: ops.Op[ops.OutputLike[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.OutputLike[T]
- Attributes
- protected
- Definition Classes
- Math
- def sqrtHessian[T](op: ops.Op[(ops.Output[T], ops.OutputLike[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.OutputLike[T])
- Attributes
- protected
- Definition Classes
- Math
- def square[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Reciprocal")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def squareGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def squaredDifference[T](x: ops.Output[T], y: ops.Output[T], name: String = "SquaredDifference")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def squaredDifferenceGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def squeeze[T](input: ops.Output[T], axes: Seq[Int] = null, name: String = "Squeeze")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Manipulation
- def squeezeGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Manipulation
- def stack[T](inputs: Seq[ops.Output[T]], axis: Int = 0, name: String = "Stack")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Manipulation
- def stackClose(stackHandle: ops.Output[core.types.Resource], name: String = "StackClose"): ops.Op[ops.Output[core.types.Resource], Unit]
- Definition Classes
- DataFlow
- def stackGradient[T](op: ops.Op[Seq[ops.Output[T]], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T]): Seq[ops.Output[T]]
- Attributes
- protected
- Definition Classes
- Manipulation
- def stackPop[T](stackHandle: ops.Output[core.types.Resource], elementType: core.types.DataType[T], name: String = "StackPop")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- DataFlow
- def stackPush[T](stackHandle: ops.Output[core.types.Resource], element: ops.Output[T], swapMemory: Boolean = false, name: String = "StackPush")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- DataFlow
- def stopGradient[T](input: ops.Output[T], name: String = "StopGradient")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Basic
- def stridedSlice[T, I](input: ops.Output[T], begin: ops.Output[I], end: ops.Output[I], strides: ops.Output[I] = null, beginMask: Long = 0, endMask: Long = 0, ellipsisMask: Long = 0, newAxisMask: Long = 0, shrinkAxisMask: Long = 0, name: String = "StridedSlice")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def stridedSliceGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I], ops.Output[I], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I], ops.Output[I], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def stridedSliceHessian[T, I](op: ops.Op[(ops.Output[I], ops.Output[I], ops.Output[I], ops.Output[I], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[I], ops.Output[I], ops.Output[I], ops.Output[I], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Manipulation
- def stringJoin(inputs: Seq[ops.Output[String]], separator: String = "", name: String = "StringJoin"): ops.Output[String]
- Definition Classes
- Text
- def stringSplit(input: ops.Output[String], delimiter: ops.Output[String] = Tensor.fill[String](Shape())(" ").toOutput, skipEmpty: Boolean = true, name: String = "StringSplit"): ops.SparseOutput[String]
- Definition Classes
- Text
- def stringToHashBucketFast(input: ops.Output[String], numBuckets: Int, name: String = "StringToHashBucketFast"): ops.Output[Long]
- Definition Classes
- Text
- def stringToHashBucketStrong(input: ops.Output[String], numBuckets: Int, key1: Long, key2: Long, name: String = "StringToHashBucketStrong"): ops.Output[Long]
- Definition Classes
- Text
- def stringToNumber[T](data: ops.Output[String], name: String = "StringToNumber")(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Parsing
- def subtract[T](x: ops.Output[T], y: ops.Output[T], name: String = "Subtract")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def subtractGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- def sufficientStatistics[T, I](input: ops.Output[T], axes: ops.Output[I], shift: ops.Output[T] = null, keepDims: Boolean = false, name: String = "SufficientStatistics")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[T], ops.Output[T], ops.Output[T])
- Definition Classes
- Statistics
- def sum[T, I](input: ops.Output[T], axes: ops.Output[I] = null, keepDims: Boolean = false, name: String = "Sum")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: IntDefault[I], arg3: core.types.TF[I], arg4: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Math
- def sumGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Math
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def tableInitializers: Set[ops.UntypedOp]
- Definition Classes
- Lookup
- def tan[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Tan")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def tanGradient[T](op: ops.Op[ops.Output[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def tanh[T, OL[A] <: ops.OutputLike[A]](x: OL[T], name: String = "Tanh")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], ev: Aux[OL, T]): OL[T]
- Definition Classes
- Math
- def tanhGradient[T](op: ops.Op[ops.OutputLike[T], ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.OutputLike[T]
- Attributes
- protected
- Definition Classes
- Math
- def tanhHessian[T](op: ops.Op[(ops.Output[T], ops.OutputLike[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], ops.OutputLike[T])
- Attributes
- protected
- Definition Classes
- Math
- def tensorDot[T](a: ops.Output[T], b: ops.Output[T], axesA: Seq[Int], axesB: Seq[Int], name: String)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def tensorDot[T](a: ops.Output[T], b: ops.Output[T], axesA: Seq[Int], axesB: Seq[Int])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def tensorDot[T](a: ops.Output[T], b: ops.Output[T], numAxes: Int, name: String)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def tensorDot[T](a: ops.Output[T], b: ops.Output[T], numAxes: Int)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def tensorDotDynamic[T](a: ops.Output[T], b: ops.Output[T], axesA: ops.Output[Int], axesB: ops.Output[Int], name: String = "TensorDot")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def tensorDotDynamic[T](a: ops.Output[T], b: ops.Output[T], axesA: ops.Output[Int], axesB: ops.Output[Int])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def tensorDotDynamic[T](a: ops.Output[T], b: ops.Output[T], numAxes: ops.Output[Int], name: String)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def tensorDotDynamic[T](a: ops.Output[T], b: ops.Output[T], numAxes: ops.Output[Int])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidArgumentException])
- def tile[T, I](input: ops.Output[T], multiples: ops.Output[I], name: String = "Tile")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def tileGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.OutputLike[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def timestamp(name: String = "Timestamp"): ops.Output[Double]
- Definition Classes
- Logging
- def toString(): String
- Definition Classes
- AnyRef → Any
- def topK[T](input: ops.Output[T], k: ops.Output[Int], sorted: Boolean = true, name: String = "TopK")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): (ops.Output[T], ops.Output[Int])
- Definition Classes
- NN
- def topKGradient[T](op: ops.Op[(ops.Output[T], ops.Output[Int]), (ops.Output[T], ops.Output[Int])], outputGradient: (ops.Output[T], ops.Output[Int]))(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T]): (ops.Output[T], ops.Output[Int])
- Attributes
- protected
- Definition Classes
- NN
- def trace[T](input: ops.Output[T], name: String = "Trace")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[T]
- Definition Classes
- Math
- def trainableVariablesInitializer(name: String = "TrainableVariablesInitializer"): ops.UntypedOp
- Definition Classes
- API
- def transpose[T, I](input: ops.Output[T], permutation: ops.Output[I] = null, conjugate: Boolean = false, name: String = "Transpose")(implicit arg0: core.types.TF[T], arg1: IntDefault[I], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Manipulation
- def transposeConjugateToAdjoint[T](tensor: ops.Output[T], transpose: Boolean, conj: Boolean)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], Boolean)
- Attributes
- protected
- Definition Classes
- Math
- def transposeConjugateToTranspose[T](tensor: ops.Output[T], transpose: Boolean, conj: Boolean)(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): (ops.Output[T], Boolean)
- Attributes
- protected
- Definition Classes
- Math
- def transposeGradient[T, I](op: ops.Op[(ops.Output[T], ops.Output[I]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def truncateDivide[T](x: ops.Output[T], y: ops.Output[T], name: String = "TruncateDivide")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def truncateMod[T](x: ops.Output[T], y: ops.Output[T], name: String = "TruncateMod")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- def tuple[T, OL[A] <: ops.OutputLike[A]](inputs: Seq[OL[T]], controlInputs: Set[ops.UntypedOp] = Set.empty, name: String = "Tuple")(implicit arg0: core.types.TF[T]): Seq[OL[T]]
- Definition Classes
- ControlFlow
- def unique[T, I1, I2](input: ops.Output[T], axis: ops.Output[I1], indicesDataType: core.types.DataType[I2], name: String = "Unique")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I1], arg2: core.types.IsIntOrLong[I1], arg3: core.types.TF[I2], arg4: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I2])
- Definition Classes
- Basic
- def uniqueWithCounts[T, I1, I2](input: ops.Output[T], axis: ops.Output[I1], indicesDataType: core.types.DataType[I2], name: String = "UniqueWithCounts")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I1], arg2: core.types.IsIntOrLong[I1], arg3: core.types.TF[I2], arg4: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I2], ops.Output[I2])
- Definition Classes
- Basic
- def unsortedSegmentMax[T, I1, I2](data: ops.Output[T], segmentIndices: ops.Output[I1], segmentsNumber: ops.Output[I2], name: String = "UnsortedSegmentMax")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Math
- def unsortedSegmentMean[T, I1, I2](data: ops.Output[T], segmentIndices: ops.Output[I1], segmentsNumber: ops.Output[I2], name: String = "UnsortedSegmentMean")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Math
- def unsortedSegmentMin[T, I1, I2](data: ops.Output[T], segmentIndices: ops.Output[I1], segmentsNumber: ops.Output[I2], name: String = "UnsortedSegmentMin")(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Math
- def unsortedSegmentMinOrMaxGradient[T, I1, I2](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[I2]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsReal[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I1], ops.Output[I2])
- Attributes
- protected
- Definition Classes
- Math
- def unsortedSegmentN[T, I1, I2](data: ops.Output[T], segmentIndices: ops.Output[I1], segmentsNumber: ops.Output[I2], name: String = "UnsortedSegmentN")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Math
- def unsortedSegmentProd[T, I1, I2](data: ops.Output[T], segmentIndices: ops.Output[I1], segmentsNumber: ops.Output[I2], name: String = "UnsortedSegmentProd")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Math
- def unsortedSegmentProdGradient[T, I1, I2](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[I2]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I1], ops.Output[I2])
- Attributes
- protected
- Definition Classes
- Math
- def unsortedSegmentSqrtN[T, I1, I2](data: ops.Output[T], segmentIndices: ops.Output[I1], segmentsNumber: ops.Output[I2], name: String = "UnsortedSegmentSqrtN")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Math
- def unsortedSegmentSum[T, I1, I2](data: ops.Output[T], segmentIndices: ops.Output[I1], segmentsNumber: ops.Output[I2], name: String = "UnsortedSegmentSum")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): ops.Output[T]
- Definition Classes
- Math
- def unsortedSegmentSumGradient[T, I1, I2](op: ops.Op[(ops.Output[T], ops.Output[I1], ops.Output[I2]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T], arg2: core.types.TF[I1], arg3: core.types.IsIntOrLong[I1], arg4: core.types.TF[I2], arg5: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I1], ops.Output[I2])
- Attributes
- protected
- Definition Classes
- Math
- def unstack[T](input: ops.Output[T], number: Int = -1, axis: Int = 0, name: String = "Unstack")(implicit arg0: core.types.TF[T]): Seq[ops.Output[T]]
- Definition Classes
- Manipulation
- Annotations
- @throws(scala.this.throws.<init>$default$1[IndexOutOfBoundsException]) @throws(scala.this.throws.<init>$default$1[IllegalArgumentException])
- def unstackGradient[T](op: ops.Op[ops.Output[T], Seq[ops.Output[T]]], outputGradient: Seq[ops.Output[T]])(implicit arg0: core.types.TF[T]): ops.Output[T]
- Attributes
- protected
- Definition Classes
- Manipulation
- def updatedVariableScope[R](variableScope: VariableScope = VariableScope.current, reuse: VariableReuse = ReuseOrCreateNewVariable, initializer: VariableInitializer = null, regularizer: VariableRegularizer = null, cachingDevice: (ops.OpSpecification) => String = null, underlyingGetter: VariableGetter = null, isPure: Boolean = false)(block: => R): R
- Definition Classes
- API
- def variable[T](name: String, shape: core.Shape = null, initializer: VariableInitializer = null, regularizer: VariableRegularizer = null, trainable: Boolean = true, reuse: Reuse = ReuseOrCreateNew, collections: Set[Key[Variable[Any]]] = Set.empty, cachingDevice: (ops.OpSpecification) => String = null)(implicit arg0: core.types.TF[T]): Variable[T]
- Definition Classes
- API
- def variableGetter[R](getter: VariableGetter)(block: => R): R
- Definition Classes
- API
- def variableScope[R](name: String, reuse: VariableReuse = ReuseOrCreateNewVariable, initializer: VariableInitializer = null, regularizer: VariableRegularizer = null, cachingDevice: (ops.OpSpecification) => String = null, underlyingGetter: VariableGetter = null, isDefaultName: Boolean = false, isPure: Boolean = false)(block: => R): R
- Definition Classes
- API
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- def where[T](input: ops.Output[T], name: String = "Where")(implicit arg0: core.types.TF[T], arg1: core.types.IsBooleanOrNumeric[T]): ops.Output[Long]
- Definition Classes
- Masking
- def whileLoop[T, S](predicateFn: (T) => ops.Output[Boolean], bodyFn: (T) => T, loopVariables: T, shapeInvariants: Option[S] = None, parallelIterations: Int = 10, enableBackPropagation: Boolean = true, swapMemory: Boolean = false, maximumIterations: ops.Output[Int] = null, name: String = "WhileLoop")(implicit evOutputToShape: Aux[T, S]): T
- Definition Classes
- ControlFlow
- def zeros[T, I](dataType: core.types.DataType[T], shape: ops.Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Constructors
- def zeros[T](dataType: core.types.DataType[T], shape: ops.Output[Int]): ops.Output[T]
- Definition Classes
- Constructors
- def zeros[T, I](shape: ops.Output[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- Definition Classes
- Constructors
- def zeros[T](shape: ops.Output[Int])(implicit arg0: core.types.TF[T]): ops.Output[T]
- Definition Classes
- Constructors
- def zerosFraction[T](input: ops.Output[T], name: String = "ZerosFraction")(implicit arg0: core.types.TF[T], arg1: core.types.IsNumeric[T]): ops.Output[Float]
- Definition Classes
- Math
- def zerosLike[T](input: ops.Output[T], optimize: Boolean = true, name: String = "ZerosLike"): ops.Output[T]
- Definition Classes
- Constructors
- def zeta[T](x: ops.Output[T], q: ops.Output[T], name: String = "Zeta")(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): ops.Output[T]
- Definition Classes
- Math
- def zetaGradient[T](op: ops.Op[(ops.Output[T], ops.Output[T]), ops.Output[T]], outputGradient: ops.Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsFloatOrDouble[T]): (ops.Output[T], ops.Output[T])
- Attributes
- protected
- Definition Classes
- Math
- object data extends API
- Definition Classes
- API
- object image extends Image
- Definition Classes
- API
- object io extends Files
- Definition Classes
- API
- object learn extends API
- object metrics extends API
- Definition Classes
- API
- object sparse extends Sparse
- Definition Classes
- API
- object summary extends Summary
- Definition Classes
- API
- object train extends API
- Definition Classes
- API
Deprecated Value Members
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable]) @Deprecated @deprecated
- Deprecated
(Since version ) see corresponding Javadoc for more information.
- def floorDivide[T](x: ops.Output[T], y: ops.Output[T], name: String = "FloorDivide")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): ops.Output[T]
- Definition Classes
- Math
- Annotations
- @deprecated
- Deprecated
(Since version 0.1) Use
truncateDivide
instead.
- def stringToHashBucket(input: ops.Output[String], numBuckets: Int, name: String = "StringToHashBucket"): ops.Output[Long]
- Definition Classes
- Text
- Annotations
- @deprecated
- Deprecated
(Since version 0.1.0) It is recommended to use
stringToHashBucketFast
orstringToHashBucketStrong
.