implicit class BasicOps[T] extends AnyRef
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Instance Constructors
- new BasicOps(output: ops.Output[T])
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 batchToSpace[I](blockSize: Int, crops: ops.Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- def batchToSpaceND[I1, I2](blockShape: ops.Output[I1], crops: ops.Output[I2])(implicit arg0: core.types.TF[I1], arg1: core.types.IsIntOrLong[I1], arg2: core.types.TF[I2], arg3: core.types.IsIntOrLong[I2]): ops.Output[T]
- def booleanMask(mask: ops.Output[Boolean]): ops.Output[T]
- def broadcastTo[I](shape: ops.Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- def checkNumerics(message: String = "")(implicit ev: core.types.IsDecimal[T]): ops.Output[T]
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- def depthToSpace(blockSize: Int, dataFormat: CNNDataFormat = CNNDataFormat.default): ops.Output[T]
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- implicit val evTTF: core.types.TF[T]
- Attributes
- protected
- def expandDims(axis: ops.Output[Int]): ops.Output[T]
- def gather[I](indices: ops.Output[I], axis: ops.Output[I] = null)(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- def gatherND[I](indices: ops.Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def identity: ops.Output[T]
- def invertPermutation(implicit ev: core.types.IsIntOrLong[T]): ops.Output[T]
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def listDiff[I](other: ops.Output[T], indicesDataType: core.types.DataType[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): (ops.Output[T], ops.Output[I])
- def listDiff(other: ops.Output[T]): (ops.Output[T], ops.Output[Int])
- def matrixTranspose(conjugate: Boolean = false): ops.Output[T]
- 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[R](depth: ops.Output[Int], onValue: ops.Output[R] = null, offValue: ops.Output[R] = null, axis: Int = -1)(implicit arg0: core.types.TF[R], ev: core.types.IsIntOrLongOrUByte[T]): ops.Output[R]
- val output: ops.Output[T]
- def pad[I](paddings: ops.Output[I], mode: ops.basic.Manipulation.PaddingMode = ConstantPadding(Some(Tensor.zeros[Int](Shape()))))(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- def preventGradient(message: String = ""): ops.Output[T]
- def reshape[I](shape: ops.Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- def reverse[I](axes: ops.Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- def reverseSequence[I](sequenceLengths: ops.Output[I], sequenceAxis: Int, batchAxis: Int = 0)(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- def sequenceMask(maxLength: ops.Output[T] = null)(implicit ev: core.types.IsIntOrUInt[T]): ops.Output[Boolean]
- def spaceToBatch[I](blockSize: Int, paddings: ops.Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- def spaceToBatchND[I1, I2](blockShape: ops.Output[I1], paddings: ops.Output[I2])(implicit arg0: core.types.TF[I1], arg1: core.types.IsIntOrLong[I1], arg2: core.types.TF[I2], arg3: core.types.IsIntOrLong[I2]): ops.Output[T]
- def spaceToDepth(blockSize: Int, dataFormat: CNNDataFormat = CNNDataFormat.default): ops.Output[T]
- def split[I](splitSizes: ops.Output[I], axis: ops.Output[Int] = Output.constant[Int](Tensor.zeros[Int](Shape())))(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): Seq[ops.Output[T]]
- def splitEvenly(numSplits: Int, axis: ops.Output[Int] = Output.constant[Int](Tensor.zeros[Int](Shape()))): Seq[ops.Output[T]]
- def squeeze(axes: Seq[Int] = null): ops.Output[T]
- def stopGradient(): ops.Output[T]
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def tile[I](multiples: ops.Output[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): ops.Output[T]
- def toString(): String
- Definition Classes
- AnyRef → Any
- def transpose[I](permutation: ops.Output[I] = null, conjugate: Boolean = false)(implicit arg0: IntDefault[I], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): ops.Output[T]
- def unique[I1, I2](axis: ops.Output[I1], indicesDataType: core.types.DataType[I2])(implicit arg0: core.types.TF[I1], arg1: core.types.IsIntOrLong[I1], arg2: core.types.TF[I2], arg3: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I2])
- def unique[I1](axis: ops.Output[I1])(implicit arg0: core.types.TF[I1], arg1: core.types.IsIntOrLong[I1]): (ops.Output[T], ops.Output[Int])
- def uniqueWithCounts[I1, I2](axis: ops.Output[I1], indicesDataType: core.types.DataType[I2])(implicit arg0: core.types.TF[I1], arg1: core.types.IsIntOrLong[I1], arg2: core.types.TF[I2], arg3: core.types.IsIntOrLong[I2]): (ops.Output[T], ops.Output[I2], ops.Output[I2])
- def uniqueWithCounts[I1](axis: ops.Output[I1])(implicit arg0: core.types.TF[I1], arg1: core.types.IsIntOrLong[I1]): (ops.Output[T], ops.Output[Int], ops.Output[Int])
- def unstack(number: Int = -1, axis: Int = 0): Seq[ops.Output[T]]
- 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(implicit ev: core.types.IsBooleanOrNumeric[T]): ops.Output[Long]