object Basic extends Basic
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final
def
!=(arg0: Any): Boolean
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final
def
##(): Int
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final
def
==(arg0: Any): Boolean
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final
def
asInstanceOf[T0]: T0
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def
batchToSpace[T, I](input: Tensor[T], blockSize: Int, crops: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Basic
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def
batchToSpaceND[T, I1, I2](input: Tensor[T], blockShape: Tensor[I1], crops: Tensor[I2])(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]): Tensor[T]
- Definition Classes
- Basic
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def
booleanMask[T](input: Tensor[T], mask: Tensor[Boolean])(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Basic
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def
checkNumerics[T](input: Tensor[T], message: String = "")(implicit arg0: core.types.TF[T], arg1: core.types.IsDecimal[T]): Tensor[T]
- Definition Classes
- Basic
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def
clone(): AnyRef
- Attributes
- protected[java.lang]
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- @native() @throws( ... )
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def
concatenate[T](inputs: Seq[Tensor[T]], axis: Tensor[Int] = 0)(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Basic
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def
depthToSpace[T](input: Tensor[T], blockSize: Int, dataFormat: CNNDataFormat = CNNDataFormat.default)(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Basic
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def
editDistance[T](hypothesis: SparseTensor[T], truth: SparseTensor[T], normalize: Boolean = true)(implicit arg0: core.types.TF[T]): Tensor[Float]
- Definition Classes
- Basic
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final
def
eq(arg0: AnyRef): Boolean
- Definition Classes
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def
equals(arg0: Any): Boolean
- Definition Classes
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def
expandDims[T, I](input: Tensor[T], axis: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Basic
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def
finalize(): Unit
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- protected[java.lang]
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def
gather[T, I1, I2](input: Tensor[T], indices: Tensor[I1], axis: Tensor[I2])(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]): Tensor[T]
- Definition Classes
- Basic
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def
gather[T, I1](input: Tensor[T], indices: Tensor[I1])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I1], arg2: core.types.IsIntOrLong[I1]): Tensor[T]
- Definition Classes
- Basic
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def
gatherND[T, I](input: Tensor[T], indices: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Basic
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final
def
getClass(): Class[_]
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- @native()
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def
hashCode(): Int
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def
indexedSlicesMask[T](input: TensorIndexedSlices[T], maskIndices: Tensor[Int])(implicit arg0: core.types.TF[T]): TensorIndexedSlices[T]
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- Basic
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- @throws( ... )
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def
invertPermutation[I](input: Tensor[I])(implicit arg0: core.types.TF[I], arg1: core.types.IsIntOrLong[I]): Tensor[I]
- Definition Classes
- Basic
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final
def
isInstanceOf[T0]: Boolean
- Definition Classes
- Any
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def
listDiff[T, I](x: Tensor[T], y: Tensor[T], indicesDataType: core.types.DataType[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Tensor[T], Tensor[I])
- Definition Classes
- Basic
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def
matrixTranspose[T](input: Tensor[T], conjugate: Boolean = false)(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Basic
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final
def
ne(arg0: AnyRef): Boolean
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final
def
notify(): Unit
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- @native()
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final
def
notifyAll(): Unit
- Definition Classes
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def
pad[T, I](input: Tensor[T], paddings: Tensor[I], mode: ops.Basic.PaddingMode = ConstantPadding(Some(Tensor(0))))(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Basic
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def
parallelStack[T](inputs: Seq[Tensor[T]])(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Basic
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def
preventGradient[T](input: Tensor[T], message: String = "")(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Basic
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def
rank[T <: TensorLike[_]](input: T): Tensor[Int]
- Definition Classes
- Basic
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def
requiredSpaceToBatchPaddingsAndCrops(inputShape: Tensor[Int], blockShape: Tensor[Int], basePaddings: Tensor[Int] = null): (Tensor[Int], Tensor[Int])
- Definition Classes
- Basic
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- @throws( ... )
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def
reshape[T, I](input: Tensor[T], shape: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Basic
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def
reverse[T, I](input: Tensor[T], axes: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Basic
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def
reverseSequence[T, I](input: Tensor[T], sequenceLengths: Tensor[I], sequenceAxis: Int, batchAxis: Int = 0)(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Basic
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def
scatterND[T, I](indices: Tensor[I], updates: Tensor[T], shape: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Basic
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def
sequenceMask[T](lengths: Tensor[T], maxLength: Tensor[T] = null)(implicit arg0: core.types.TF[T], arg1: core.types.IsIntOrUInt[T]): Tensor[Boolean]
- Definition Classes
- Basic
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- @throws( ... )
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def
shape[T <: TensorLike[_]](input: T): Tensor[Int]
- Definition Classes
- Basic
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def
shapeN(inputs: Seq[Tensor[_]]): Seq[Tensor[Int]]
- Definition Classes
- Basic
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def
size[T <: TensorLike[_]](input: T): Tensor[Long]
- Definition Classes
- Basic
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def
spaceToBatch[T, I](input: Tensor[T], blockSize: Int, paddings: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Basic
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def
spaceToBatchND[T, I1, I2](input: Tensor[T], blockShape: Tensor[I1], paddings: Tensor[I2])(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]): Tensor[T]
- Definition Classes
- Basic
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def
spaceToDepth[T](input: Tensor[T], blockSize: Int, dataFormat: CNNDataFormat = CNNDataFormat.default)(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Basic
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def
split[T, I](input: Tensor[T], splitSizes: Tensor[I], axis: Tensor[Int] = 0)(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Seq[Tensor[T]]
- Definition Classes
- Basic
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def
splitEvenly[T](input: Tensor[T], numSplits: Int, axis: Tensor[Int] = 0)(implicit arg0: core.types.TF[T]): Seq[Tensor[T]]
- Definition Classes
- Basic
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def
squeeze[T](input: Tensor[T], axes: Seq[Int] = null)(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Basic
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def
stack[T](inputs: Seq[Tensor[T]], axis: Int = 0)(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Basic
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def
stopGradient[T](input: Tensor[T])(implicit arg0: core.types.TF[T]): Tensor[T]
- Definition Classes
- Basic
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final
def
synchronized[T0](arg0: ⇒ T0): T0
- Definition Classes
- AnyRef
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def
tile[T, I](input: Tensor[T], multiples: Tensor[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Basic
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def
toString(): String
- Definition Classes
- AnyRef → Any
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def
transpose[T, I](input: Tensor[T], permutation: Tensor[I] = null, conjugate: Boolean = false)(implicit arg0: core.types.TF[T], arg1: IntDefault[I], arg2: core.types.TF[I], arg3: core.types.IsIntOrLong[I]): Tensor[T]
- Definition Classes
- Basic
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def
unique[T, I](input: Tensor[T], indicesDataType: core.types.DataType[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Tensor[T], Tensor[I])
- Definition Classes
- Basic
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def
uniqueWithCounts[T, I](input: Tensor[T], indicesDataType: core.types.DataType[I])(implicit arg0: core.types.TF[T], arg1: core.types.TF[I], arg2: core.types.IsIntOrLong[I]): (Tensor[T], Tensor[I], Tensor[I])
- Definition Classes
- Basic
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def
unstack[T](input: Tensor[T], number: Int = -1, axis: Int = 0)(implicit arg0: core.types.TF[T]): Seq[Tensor[T]]
- Definition Classes
- Basic
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final
def
wait(): Unit
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final
def
wait(arg0: Long, arg1: Int): Unit
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final
def
wait(arg0: Long): Unit
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def
where[T](input: Tensor[T])(implicit arg0: core.types.TF[T], arg1: core.types.IsBooleanOrNumeric[T]): Tensor[Long]
- Definition Classes
- Basic