trait Basic extends Constructors with Inplace with Manipulation with Masking
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Type Members
- case class ConstantPadding[V](value: Option[tensors.Tensor[V]] = None)(implicit evidence$48: core.types.TF[V]) extends PaddingMode with Product with Serializable
- Definition Classes
- Manipulation
- sealed trait PaddingMode extends AnyRef
- Definition Classes
- Manipulation
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def batchGather[T, I](input: Output[T], indices: Output[I], axis: Int = 1, batchDimensionCount: Int = 1, name: String = "BatchGather")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Manipulation
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidShapeException])
- def batchToSpace[T, I](input: Output[T], blockSize: Int, crops: Output[I], name: String = "BatchToSpace")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Manipulation
- def batchToSpaceND[T, I1, I2](input: Output[T], blockShape: Output[I1], crops: 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]): Output[T]
- Definition Classes
- Manipulation
- def batchToSpaceNDGradient[T, I1, I2](op: Op[(Output[T], Output[I1], Output[I2]), Output[T]], outputGradient: 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]): (Output[T], Output[I1], Output[I2])
- Attributes
- protected
- Definition Classes
- Manipulation
- def booleanMask[T](input: Output[T], mask: Output[Boolean], name: String = "BooleanMask")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Masking
- def broadcastGradientArguments[I](shape1: Output[I], shape2: Output[I], name: String = "BroadcastGradientArguments")(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): (Output[I], Output[I])
- def broadcastShapeDynamic[I](shape1: Output[I], shape2: Output[I], name: String = "BroadcastShape")(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): Output[I]
- def broadcastTo[T, I](value: Output[T], shape: Output[I], name: String = "BroadcastTo")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- def checkNumerics[T](input: Output[T], message: String = "", name: String = "CheckNumerics")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): Output[T]
- def checkNumericsGradient[T](op: Op[Output[T], Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): Output[T]
- Attributes
- protected
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- def concatenate[T](inputs: Seq[Output[T]], axis: Output[Int] = 0, name: String = "Concatenate")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Manipulation
- def concatenateGradient[T](op: Op[(Seq[Output[T]], Output[Int]), Output[T]], outputGradient: OutputLike[T])(implicit arg0: core.types.TF[T]): (Seq[OutputLike[T]], Output[Int])
- Attributes
- protected
- Definition Classes
- Manipulation
- def conjugateTransposeGradient[T, I](op: Op[(Output[T], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def constant[T](tensor: tensors.Tensor[T], shape: core.Shape = null, name: String = "Constant"): Output[T]
- Definition Classes
- Constructors
- def deepCopy[T](x: Output[T], name: String = "DeepCopy")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Inplace
- def depthToSpace[T](input: Output[T], blockSize: Int, dataFormat: CNNDataFormat = CNNDataFormat.default, name: String = "DepthToSpace")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Manipulation
- def depthToSpaceGradient[T](op: Op[Output[T], Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T]): Output[T]
- Attributes
- protected
- Definition Classes
- Manipulation
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.jni.InvalidArgumentException])
- def editDistance[T](hypothesis: SparseOutput[T], truth: SparseOutput[T], normalize: Boolean = true, name: String = "EditDistance")(implicit arg0: core.types.TF[T]): Output[Float]
- def empty[T](shape: Output[Int], initialize: Boolean = false, name: String = "Empty")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Constructors
- def emptyLike[T](input: Output[T], initialize: Boolean = false, optimize: Boolean = true, name: String = "EmptyLike")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Constructors
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- def expandDims[T, I](input: Output[T], axis: Output[I], name: String = "ExpandDims")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Manipulation
- def expandDimsGradient[T, I](op: Op[(Output[T], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def fill[T, I](dataType: core.types.DataType[T], shape: Output[I])(value: Output[T])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Constructors
- def fill[T, I](shape: Output[I])(value: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Constructors
- def fillGradient[T, I](op: Op[(Output[I], Output[T]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[I], Output[T])
- Attributes
- protected
- Definition Classes
- Constructors
- def gather[T, I1, I2](input: Output[T], indices: Output[I1], axis: 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]): Output[T]
- Definition Classes
- Manipulation
- def gatherGradient[T, I1, I2](op: Op[(Output[T], Output[I1], Output[I2]), Output[T]], outputGradient: 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]): (OutputLike[T], Output[I1], Output[I2])
- Attributes
- protected
- Definition Classes
- Manipulation
- def gatherND[T, I](input: Output[T], indices: Output[I], name: String = "GatherND")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Manipulation
- def gatherNDGradient[T, I](op: Op[(Output[T], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (OutputLike[T], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def guaranteeConstant[T](input: Output[T], name: String = "GuaranteeConstant"): Output[T]
- Definition Classes
- Constructors
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def identity[T, OL[A] <: OutputLike[A]](input: OL[T], name: String = "Identity")(implicit arg0: core.types.TF[T]): OL[T]
- Definition Classes
- Manipulation
- def immutableConstant[T](shape: core.Shape, memoryRegionName: String, name: String = "ImmutableConstant")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Constructors
- def indexedSlicesMask[T](input: OutputIndexedSlices[T], maskIndices: Output[Int], name: String = "IndexedSlicesMask")(implicit arg0: core.types.TF[T]): OutputIndexedSlices[T]
- Definition Classes
- Masking
- def inplaceAdd[T](x: Output[T], i: Option[Output[Int]], v: Output[T], name: String = "InplaceAdd")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Inplace
- def inplaceSubtract[T](x: Output[T], i: Option[Output[Int]], v: Output[T], name: String = "InplaceSubtract")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Inplace
- def inplaceUpdate[T](x: Output[T], i: Option[Output[Int]], v: Output[T], name: String = "InplaceUpdate")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Inplace
- def invertPermutation[I](input: Output[I], name: String = "InvertPermutation")(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): Output[I]
- Definition Classes
- Manipulation
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def listDiff[T, I](x: Output[T], y: 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]): (Output[T], Output[I])
- Definition Classes
- Masking
- def matrixTranspose[T](input: Output[T], conjugate: Boolean = false, name: String = "MatrixTranspose")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Manipulation
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.api.core.exception.InvalidShapeException])
- def meshGrid[T](inputs: Seq[Output[T]], useCartesianIndexing: Boolean = true, name: String = "MeshGrid")(implicit arg0: core.types.TF[T], arg1: core.types.IsNotQuantized[T]): Seq[Output[T]]
- def mirrorPadGradient[T, I](op: Op[(Output[T], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def mirrorPadHessian[T, I](op: Op[(Output[T], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- 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: Output[I], depth: Output[Int], onValue: Output[T] = null, offValue: 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]): Output[T]
- def ones[T, I](dataType: core.types.DataType[T], shape: Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Constructors
- def ones[T](dataType: core.types.DataType[T], shape: Output[Int]): Output[T]
- Definition Classes
- Constructors
- def ones[T, I](shape: Output[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Constructors
- def ones[T](shape: Output[Int])(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Constructors
- def onesLike[T](input: Output[T], optimize: Boolean = true, name: String = "OnesLike"): Output[T]
- Definition Classes
- Constructors
- def pad[T, I](input: Output[T], paddings: Output[I], mode: 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]): Output[T]
- Definition Classes
- Manipulation
- def padGradient[T, I](op: Op[(Output[T], Output[I], Output[T]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I], Output[T])
- Attributes
- protected
- Definition Classes
- Manipulation
- def parallelStack[T](inputs: Seq[Output[T]], name: String = "ParallelStack")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Manipulation
- def placeholder[T](shape: core.Shape = null, name: String = "Placeholder")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Constructors
- def placeholderWithDefault[T](default: Output[T], shape: core.Shape, name: String = "PlaceholderWithDefault")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Constructors
- def preventGradient[T](input: Output[T], message: String = "", name: String = "PreventGradient")(implicit arg0: core.types.TF[T]): Output[T]
- def preventGradientGradient[T](op: Op[Output[T], Output[T]], outputGradients: Output[T])(implicit arg0: core.types.TF[T]): Output[T]
- Attributes
- protected
- Annotations
- @throws(scala.this.throws.<init>$default$1[IllegalArgumentException])
- def rank[T, OL[A] <: OutputLike[A]](input: OL[T], optimize: Boolean = true, name: String = "Rank")(implicit arg0: core.types.TF[T]): Output[Int]
- Definition Classes
- Manipulation
- def requiredSpaceToBatchPaddingsAndCrops(inputShape: Output[Int], blockShape: Output[Int], basePaddings: Output[Int] = null, name: String = "RequiredSpaceToBatchPaddings"): (Output[Int], Output[Int])
- Definition Classes
- Manipulation
- def reshape[T, I](input: Output[T], shape: Output[I], name: String = "Reshape")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Manipulation
- def reshapeGradient[T, I](op: Op[(Output[T], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def reshapeToInput[T](input: Output[T], gradient: Output[T])(implicit arg0: core.types.TF[T]): Output[T]
- Attributes
- protected
- Definition Classes
- Manipulation
- def reverse[T, I](input: Output[T], axes: Output[I], name: String = "Reverse")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Manipulation
- def reverseGradient[T, I](op: Op[(Output[T], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def reverseSequence[T, I](input: Output[T], sequenceLengths: 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]): Output[T]
- Definition Classes
- Manipulation
- def reverseSequenceGradient[T, I](op: Op[(Output[T], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def scatterND[T, I](indices: Output[I], updates: Output[T], shape: Output[I], name: String = "ScatterND")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Manipulation
- def scatterNDGradient[T, I](op: Op[(Output[I], Output[T], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[I], Output[T], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def sequenceMask[T](lengths: Output[T], maxLength: Output[T] = null, name: String = "SequenceMask")(implicit arg0: core.types.TF[T], arg1: core.types.IsIntOrUInt[T]): Output[Boolean]
- Definition Classes
- Masking
- Annotations
- @throws(scala.this.throws.<init>$default$1[IllegalArgumentException])
- def shape[T, OL[A] <: OutputLike[A]](input: OL[T], optimize: Boolean = true, name: String = "Shape")(implicit arg0: core.types.TF[T]): Output[Int]
- Definition Classes
- Manipulation
- def shapeN[T, I](inputs: Seq[Output[T]], dataType: core.types.DataType[I])(implicit arg0: core.types.TF[T], arg1: core.types.IsIntOrLong[I]): Seq[Output[I]]
- Definition Classes
- Manipulation
- def shapeN[T, I](inputs: Seq[Output[T]])(implicit arg0: core.types.TF[T], arg1: IntDefault[I], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Seq[Output[I]]
- Definition Classes
- Manipulation
- def size[T, OL[A] <: OutputLike[A]](input: OL[T], optimize: Boolean = true, name: String = "Size")(implicit arg0: core.types.TF[T]): Output[Long]
- Definition Classes
- Manipulation
- def slice[T, I](input: Output[T], begin: Output[I], size: Output[I], name: String = "Slice")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Manipulation
- def sliceGradient[T, I](op: Op[(Output[T], Output[I], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def spaceToBatch[T, I](input: Output[T], blockSize: Int, paddings: Output[I], name: String = "SpaceToBatch")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Manipulation
- def spaceToBatchND[T, I1, I2](input: Output[T], blockShape: Output[I1], paddings: 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]): Output[T]
- Definition Classes
- Manipulation
- def spaceToBatchNDGradient[T, I1, I2](op: Op[(Output[T], Output[I1], Output[I2]), Output[T]], outputGradient: 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]): (Output[T], Output[I1], Output[I2])
- Attributes
- protected
- Definition Classes
- Manipulation
- def spaceToDepth[T](input: Output[T], blockSize: Int, dataFormat: CNNDataFormat = CNNDataFormat.default, name: String = "SpaceToDepth")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Manipulation
- def spaceToDepthGradient[T](op: Op[Output[T], Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T]): Output[T]
- Attributes
- protected
- Definition Classes
- Manipulation
- Annotations
- @throws(scala.this.throws.<init>$default$1[org.platanios.tensorflow.jni.InvalidArgumentException])
- def sparsePlaceholder[T](shape: core.Shape = null, name: String = "SparsePlaceholder")(implicit arg0: core.types.TF[T]): SparseOutput[T]
- Definition Classes
- Constructors
- def split[T, I](input: Output[T], splitSizes: Output[I], axis: Output[Int] = 0, name: String = "Split")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Seq[Output[T]]
- Definition Classes
- Manipulation
- def splitEvenly[T](input: Output[T], numSplits: Int, axis: Output[Int] = 0, name: String = "Split")(implicit arg0: core.types.TF[T]): Seq[Output[T]]
- Definition Classes
- Manipulation
- def splitEvenlyGradient[T](op: Op[(Output[Int], Output[T]), Seq[Output[T]]], outputGradient: Seq[Output[T]])(implicit arg0: core.types.TF[T]): (Output[Int], Output[T])
- Attributes
- protected
- Definition Classes
- Manipulation
- def splitGradient[T, I](op: Op[(Output[T], Output[I], Output[Int]), Seq[Output[T]]], outputGradient: Seq[Output[T]])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I], Output[Int])
- Attributes
- protected
- Definition Classes
- Manipulation
- def squeeze[T](input: Output[T], axes: Seq[Int] = null, name: String = "Squeeze")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Manipulation
- def squeezeGradient[T](op: Op[Output[T], Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T]): Output[T]
- Attributes
- protected
- Definition Classes
- Manipulation
- def stack[T](inputs: Seq[Output[T]], axis: Int = 0, name: String = "Stack")(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Manipulation
- def stackGradient[T](op: Op[Seq[Output[T]], Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T]): Seq[Output[T]]
- Attributes
- protected
- Definition Classes
- Manipulation
- def stopGradient[T](input: Output[T], name: String = "StopGradient")(implicit arg0: core.types.TF[T]): Output[T]
- def stridedSlice[T, I](input: Output[T], begin: Output[I], end: Output[I], strides: 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]): Output[T]
- Definition Classes
- Manipulation
- def stridedSliceGradient[T, I](op: Op[(Output[T], Output[I], Output[I], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I], Output[I], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def stridedSliceHessian[T, I](op: Op[(Output[I], Output[I], Output[I], Output[I], Output[T]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[I], Output[I], Output[I], Output[I], Output[T])
- Attributes
- protected
- Definition Classes
- Manipulation
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def tile[T, I](input: Output[T], multiples: Output[I], name: String = "Tile")(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Manipulation
- def tileGradient[T, I](op: Op[(Output[T], Output[I]), Output[T]], outputGradient: OutputLike[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def toString(): String
- Definition Classes
- AnyRef → Any
- def transpose[T, I](input: Output[T], permutation: 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]): Output[T]
- Definition Classes
- Manipulation
- def transposeGradient[T, I](op: Op[(Output[T], Output[I]), Output[T]], outputGradient: Output[T])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Output[T], Output[I])
- Attributes
- protected
- Definition Classes
- Manipulation
- def unique[T, I1, I2](input: Output[T], axis: 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]): (Output[T], Output[I2])
- def uniqueWithCounts[T, I1, I2](input: Output[T], axis: 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]): (Output[T], Output[I2], Output[I2])
- def unstack[T](input: Output[T], number: Int = -1, axis: Int = 0, name: String = "Unstack")(implicit arg0: core.types.TF[T]): Seq[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: Op[Output[T], Seq[Output[T]]], outputGradient: Seq[Output[T]])(implicit arg0: core.types.TF[T]): Output[T]
- Attributes
- protected
- Definition Classes
- Manipulation
- 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: Output[T], name: String = "Where")(implicit arg0: core.types.TF[T], arg1: core.types.IsBooleanOrNumeric[T]): Output[Long]
- Definition Classes
- Masking
- def zeros[T, I](dataType: core.types.DataType[T], shape: Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Constructors
- def zeros[T](dataType: core.types.DataType[T], shape: Output[Int]): Output[T]
- Definition Classes
- Constructors
- def zeros[T, I](shape: Output[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Output[T]
- Definition Classes
- Constructors
- def zeros[T](shape: Output[Int])(implicit arg0: core.types.TF[T]): Output[T]
- Definition Classes
- Constructors
- def zerosLike[T](input: Output[T], optimize: Boolean = true, name: String = "ZerosLike"): Output[T]
- Definition Classes
- Constructors
- object ReflectivePadding extends PaddingMode
- Definition Classes
- Manipulation
- object SymmetricPadding extends PaddingMode
- Definition Classes
- Manipulation