Modifier and Type | Interface and Description |
---|---|
interface |
BroadcastOp
A broad cast op is one where a scalar
or less rank array
is broadcast to fill
a bigg er array.
|
interface |
GridOp
MetaOp is special op, that contains multiple ops
|
interface |
IndexAccumulation
An index accumulation is an operation that returns an index within
a NDArray.
Examples of IndexAccumulation operations include finding the index of the minimim value, index of the maximum value, index of the first element equal to value y, index of the maximum pair-wise difference between two NDArrays X and Y etc. Index accumulation is similar to ReduceOp in that both are
accumulation/reduction operations, however index accumulation returns
an integer corresponding to an index, rather than a real (or complex)
value.Index accumulation operations generally have 3 inputs: x -> the origin ndarray y -> the pairwise ndarray (frequently null/not applicable) n -> the number of times to accumulate Note that IndexAccumulation op implementations should be stateless (other than the final result and x/y/n arguments) and hence threadsafe, such that they may be parallelized using the update, combineSubResults and set/getFinalResults methods. |
interface |
LossFunction
A loss function for computing
the delta between two arrays
|
interface |
MetaOp
MetaOp is special op, that contains multiple ops
|
interface |
RandomOp |
interface |
ReduceBoolOp
ReduceLong take any type in, and return BOOL type
|
interface |
ReduceFloatOp
ReduceLong take any type in, and return FLOATING-POINT type
|
interface |
ReduceLongOp
ReduceLong take any type in, and return LONG type
|
interface |
ReduceOp
An accumulation is an op that given:
x -> the origin ndarray y -> the pairwise ndarray n -> the number of times to accumulate Of note here in the extra arguments. |
interface |
ReduceSameOp
ReduceLong take any type in, and return same type
|
interface |
ScalarOp
Applies a scalar
along a bigger input array.
|
interface |
TransformBoolOp
Strict transforms take any type in, and return BOOL type
|
interface |
TransformFloatOp
Strict transforms take any type in, and return FLOATING-POINT type
|
interface |
TransformOp
Transform operation:
stores the result in an ndarray
|
interface |
TransformSameOp
Strict transforms take any type in, and return same type
|
interface |
TransformStrictOp
Strict transforms take floating-point type in, and return same type
|
Modifier and Type | Class and Description |
---|---|
class |
BaseBroadcastBoolOp |
class |
BaseBroadcastOp |
class |
BaseIndexAccumulation
Index based reduction algo
|
class |
BaseOp
Base op.
|
class |
BaseReduceBoolOp |
class |
BaseReduceFloatOp |
class |
BaseReduceLongOp |
class |
BaseReduceOp
Base class for accumulation, initiates the initial entry
with respect to the child class.
|
class |
BaseReduceSameOp |
class |
BaseScalarBoolOp
Base scalar boolean operation
|
class |
BaseScalarOp
Base scalar operation
|
class |
BaseTransformAnyOp |
class |
BaseTransformBoolOp |
class |
BaseTransformFloatOp |
class |
BaseTransformOp
A base op for basic getters and setters
|
class |
BaseTransformSameOp |
class |
BaseTransformStrictOp |
Modifier and Type | Method and Description |
---|---|
Op |
MetaOp.getFirstOp() |
Op |
MetaOp.getSecondOp() |
Modifier and Type | Method and Description |
---|---|
static Op.Type |
BaseOp.getOpType(Op op) |
Modifier and Type | Method and Description |
---|---|
Op |
DefaultOpExecutioner.execAndReturn(Op op) |
Op |
OpExecutioner.execAndReturn(Op op)
Execute and return a result
ndarray from the given op
|
Modifier and Type | Method and Description |
---|---|
protected void |
DefaultOpExecutioner.checkForCompression(Op op) |
static void |
OpExecutionerUtil.checkForInf(Op op,
OpContext oc) |
static void |
OpExecutionerUtil.checkForNaN(Op op,
OpContext oc) |
protected void |
DefaultOpExecutioner.checkForWorkspaces(Op op,
OpContext oc) |
abstract INDArray |
DefaultOpExecutioner.exec(Op op) |
INDArray |
OpExecutioner.exec(Op op)
Execute the operation
|
abstract INDArray |
DefaultOpExecutioner.exec(Op op,
OpContext opContext) |
INDArray |
OpExecutioner.exec(Op op,
OpContext opContext)
Execute the operation
|
Op |
DefaultOpExecutioner.execAndReturn(Op op) |
Op |
OpExecutioner.execAndReturn(Op op)
Execute and return a result
ndarray from the given op
|
INDArray |
DefaultOpExecutioner.getX(Op op,
OpContext oc) |
INDArray |
DefaultOpExecutioner.getY(Op op,
OpContext oc) |
INDArray |
DefaultOpExecutioner.getZ(Op op,
OpContext oc) |
protected void |
DefaultOpExecutioner.interceptIntDataType(Op op)
This method checks if any Op operand has data opType of INT, and throws exception if any.
|
String |
DefaultOpExecutioner.opInfoString(Op op,
Optional<int[]> dimensions)
Get the information about the op in a String representation, for throwing more useful exceptions (mainly for debugging)
|
long |
DefaultOpExecutioner.profilingConfigurableHookIn(Op op,
DataBuffer... tadBuffers) |
void |
DefaultOpExecutioner.profilingConfigurableHookOut(Op op,
OpContext oc,
long timeStart) |
long |
DefaultOpExecutioner.profilingHookIn(Op op,
DataBuffer... tadBuffers)
Deprecated.
|
void |
DefaultOpExecutioner.profilingHookOut(Op op,
OpContext oc,
long timeStart)
Deprecated.
|
void |
DefaultOpExecutioner.setX(INDArray x,
Op op,
OpContext oc) |
void |
DefaultOpExecutioner.setY(INDArray y,
Op op,
OpContext oc) |
void |
DefaultOpExecutioner.setZ(INDArray z,
Op op,
OpContext oc) |
static void |
DefaultOpExecutioner.validateDataType(DataType expectedType,
Op op)
Validate the data types
for the given operation
|
Constructor and Description |
---|
GridPointers(Op op,
int... dimensions) |
OpDescriptor(Op op) |
Modifier and Type | Class and Description |
---|---|
class |
BroadcastAddOp |
class |
BroadcastAMax
Broadcast Abs Max comparison op
|
class |
BroadcastAMin
Broadcast Abs Min comparison op
|
class |
BroadcastCopyOp |
class |
BroadcastDivOp |
class |
BroadcastGradientArgs |
class |
BroadcastMax
Broadcast Max comparison op
|
class |
BroadcastMin
Broadcast Min comparison op
|
class |
BroadcastMulOp |
class |
BroadcastRDivOp
Broadcast reverse divide
|
class |
BroadcastRSubOp |
class |
BroadcastSubOp |
Modifier and Type | Class and Description |
---|---|
class |
BroadcastEqualTo |
class |
BroadcastGreaterThan |
class |
BroadcastGreaterThanOrEqual |
class |
BroadcastLessThan |
class |
BroadcastLessThanOrEqual |
class |
BroadcastNotEqual |
Modifier and Type | Class and Description |
---|---|
class |
BaseGridOp |
class |
FreeGridOp
Simple GridOp that operates on arbitrary number of Ops, that have no relations between them.
|
Constructor and Description |
---|
BaseGridOp(Op... ops) |
FreeGridOp(Op... ops) |
Constructor and Description |
---|
BaseGridOp(List<Op> ops) |
FreeGridOp(List<Op> ops) |
Modifier and Type | Class and Description |
---|---|
class |
FirstIndex
Calculate the index
of max value over a vector
|
class |
IAMax
Calculate the index of the max absolute value over a vector
|
class |
IAMin
Calculate the index of the max absolute value over a vector
|
class |
IMax
Calculate the index
of max value over a vector
|
class |
IMin
Calculate the index of min value over a vector
|
class |
LastIndex
Calculate the index
of max value over a vector
|
Modifier and Type | Class and Description |
---|---|
class |
BaseMetaOp |
class |
InvertedPredicateMetaOp
This MetaOp covers case, when Op A and Op B are both using linear memory access
You're NOT supposed to directly call this op.
|
class |
PostulateMetaOp
You're NOT supposed to directly call this op.
|
class |
PredicateMetaOp
This MetaOp covers case, when Op A and Op B are both using linear memory access
You're NOT supposed to directly call this op.
|
class |
ReduceMetaOp
This is special case PredicateOp, with opB being only either ReduceOp, Variance or Reduce3 op
|
Modifier and Type | Method and Description |
---|---|
Op |
BaseMetaOp.getFirstOp() |
Op |
BaseMetaOp.getSecondOp() |
Constructor and Description |
---|
BaseMetaOp(Op opA,
Op opB) |
InvertedPredicateMetaOp(Op opA,
Op opB) |
PredicateMetaOp(Op opA,
Op opB) |
Modifier and Type | Class and Description |
---|---|
class |
All
Boolean AND accumulation
|
class |
Any
Boolean AND pairwise transform
|
class |
IsInf
IsInf function
|
class |
IsNaN
IsInf function
|
Modifier and Type | Class and Description |
---|---|
class |
AMean
Calculate the absolute mean of the given vector
|
class |
Entropy
Entropy Op - returns the entropy (information gain, or uncertainty of a random variable).
|
class |
LogEntropy
Log Entropy Op - returns the log entropy (information gain, or uncertainty of a random variable).
|
class |
Mean
Calculate the mean of the vector
|
class |
Norm1
Sum of absolute values
|
class |
Norm2
Sum of squared values (real)
Sum of squared complex modulus (complex)
|
class |
NormMax
The max absolute value
|
class |
ShannonEntropy
Non-normalized Shannon Entropy Op - returns the entropy (information gain, or uncertainty of a random variable).
|
class |
SquaredNorm
Squared norm (sum_i x_i^2) reduction operation
|
Modifier and Type | Class and Description |
---|---|
class |
CountNonZero
Count the number of non-zero elements
|
class |
CountZero
Count the number of zero elements
|
class |
MatchCondition
This operation returns number of elements matching specified condition
|
Modifier and Type | Class and Description |
---|---|
class |
AMax
Calculate the absolute max over a vector
|
class |
AMin
Calculate the absolute minimum over a vector
|
class |
ASum
Absolute sum the components
|
class |
Max
Calculate the max over an array
|
class |
Min
Calculate the min over an array
|
class |
Prod
Prod the components
|
class |
Sum
Sum the components
|
Modifier and Type | Class and Description |
---|---|
class |
BaseReduce3Op
Manhattan distance
|
class |
CosineDistance
Cosine distance
Note that you need to initialize
a scaling constant equal to the norm2 of the
vector
|
class |
CosineSimilarity
Cosine similarity
Note that you need to initialize
a scaling constant equal to the norm2 of the
vector
|
class |
Dot
Dot product.
|
class |
EqualsWithEps
Operation for fast INDArrays equality checks
|
class |
EuclideanDistance
Euclidean distance
|
class |
HammingDistance
Hamming distance (simple)
|
class |
JaccardDistance
Jaccard distance (dissimilarity)
|
class |
ManhattanDistance
Manhattan distance
|
Modifier and Type | Class and Description |
---|---|
class |
LeakyReLU
Leaky Rectified linear unit.
|
class |
LogX
Log on arbitrary base op
|
class |
Pow
Pow function
|
class |
PowDerivative
Pow derivative
z = n * x ^ (n-1)
|
class |
RectifiedLinear
Rectified linear units
|
class |
Relu6
Rectified linear unit 6, i.e.
|
class |
ReplaceNans
Element-wise "Replace NaN" implementation as Op
|
class |
ScalarAdd
Scalar addition
|
class |
ScalarDivision
Scalar division
|
class |
ScalarFMod
Scalar floating-point remainder (fmod aka 'floormod')
|
class |
ScalarMax
Scalar max operation.
|
class |
ScalarMin
Scalar max operation.
|
class |
ScalarMultiplication
Scalar multiplication
|
class |
ScalarRemainder
Scalar floating-point remainder
|
class |
ScalarReverseDivision
Scalar reverse division
|
class |
ScalarReverseSubtraction
Scalar reverse subtraction
|
class |
ScalarSet
Scalar max operation.
|
class |
ScalarSubtraction
Scalar subtraction
|
class |
Step
Unit step function.
|
Modifier and Type | Class and Description |
---|---|
class |
ScalarAnd
Return a binary (0 or 1)
when greater than a number
|
class |
ScalarEps
Return a binary (0 or 1) when greater than a number
|
class |
ScalarEquals
Return a binary (0 or 1) when greater than a number
|
class |
ScalarGreaterThan
Return a binary (0 or 1) when greater than a number
|
class |
ScalarGreaterThanOrEqual
Return a binary (0 or 1) when greater than or equal to a number
|
class |
ScalarLessThan
Return a binary (0 or 1) when less than a number
|
class |
ScalarLessThanOrEqual
Return a binary (0 or 1) when less than
or equal to a number
|
class |
ScalarNot
Return a binary (0 or 1)
when greater than a number
|
class |
ScalarNotEquals
Return a binary (0 or 1)
when greater than a number
|
class |
ScalarOr
Return a binary (0 or 1)
when greater than a number
|
class |
ScalarSetValue
Scalar value set operation.
|
class |
ScalarXor
Return a binary (0 or 1)
when greater than a number
|
Modifier and Type | Class and Description |
---|---|
class |
StandardDeviation
Standard deviation (sqrt of variance)
|
class |
Variance
Variance with bias correction.
|
Modifier and Type | Class and Description |
---|---|
class |
MaxOut
Max out activation:
https://arxiv.org/pdf/1302.4389.pdf
|
Modifier and Type | Class and Description |
---|---|
class |
Assign
Identity function
|
Modifier and Type | Class and Description |
---|---|
class |
BooleanNot
Boolean NOT transform
|
class |
IsFinite
IsFinite function
|
class |
MatchConditionTransform
Match condition transform
|
Modifier and Type | Class and Description |
---|---|
class |
CompareAndReplace
Element-wise Compare-and-Replace implementation as Op
Basically this op does the same as Compare-and-Set, but op.X is checked against Condition instead
|
class |
CompareAndSet
Element-wise Compare-and-set implementation as Op
Please check javadoc to specific constructors, for detail information.
|
class |
Eps
Bit mask over the ndarrays as to whether
the components are equal or not
|
Modifier and Type | Class and Description |
---|---|
class |
RSqrt
RSqrt function
|
class |
Sqrt
Sqrt function
|
Modifier and Type | Class and Description |
---|---|
class |
CubeDerivative
Deprecated.
Use
CubeBp |
class |
HardSigmoidDerivative
Deprecated.
Use
HardSigmoidBp |
class |
HardTanhDerivative
Deprecated.
Use
HardTanhBp |
class |
LeakyReLUDerivative
Leaky ReLU derivative.
|
class |
RationalTanhDerivative
Deprecated.
Use
RationalTanhBp |
class |
RectifiedTanhDerivative
Deprecated.
Use
RectifiedTanhBp |
class |
SELUDerivative
Deprecated.
Use
SeluBp |
class |
SoftSignDerivative
Deprecated.
Use
SoftSignBp |
Modifier and Type | Class and Description |
---|---|
class |
BinaryMinimalRelativeError |
class |
BinaryRelativeError |
class |
RelativeError |
class |
Set
Set
|
Modifier and Type | Class and Description |
---|---|
class |
Axpy
Level 1 blas op Axpy as libnd4j native op
|
class |
CopyOp
Copy operation
|
class |
FModOp
Floating-point mod
|
class |
PowPairwise
Pairwise version of PoW
|
class |
RemainderOp
Floating-point remainder operation
|
Modifier and Type | Class and Description |
---|---|
class |
And
Boolean AND pairwise transform
|
class |
Not
Boolean AND pairwise transform
|
class |
Or
Boolean OR pairwise transform
|
class |
Xor
Boolean XOR pairwise transform
|
Modifier and Type | Class and Description |
---|---|
class |
Abs
Abs elementwise function
|
class |
Ceil
Ceiling elementwise function
|
class |
Cube
Cube (x^3) elementwise function
|
class |
Floor
Floor elementwise function
|
class |
Negative
Negative function
|
class |
OneMinus
1 - input
|
class |
Reciprocal
Created by susaneraly on 3/28/18.
|
class |
Round
Rounding function
|
class |
Sign
Signum function
|
class |
Square
Square function (x ^ 2)
|
class |
TimesOneMinus
If x is input: output is x*(1-x)
|
Modifier and Type | Class and Description |
---|---|
class |
ACos
Log elementwise function
|
class |
ACosh
ACosh elementwise function
|
class |
ASin
Arcsin elementwise function
|
class |
ASinh
Arcsin elementwise function
|
class |
ATan
Arc Tangent elementwise function
|
class |
ATanh
tan elementwise function
|
class |
Cos
Cosine elementwise function
|
class |
Cosh
Cosine Hyperbolic elementwise function
|
class |
Erf
Gaussian error function (erf) function, which is defined as
|
class |
Erfc
Complementary Gaussian error function (erfc), defined as
|
class |
Exp
Element-wise exponential function
|
class |
Expm1
Element-wise exponential function minus 1, i.e.
|
class |
GELU
GELU activation function - Gaussian Error Linear Units
For more details, see Gaussian Error Linear Units (GELUs) - https://arxiv.org/abs/1606.08415 Note: This op implements both the sigmoid and tanh-based approximations; to use the sigmoid approximation (recommended) use precise=false; otherwise, use precise = true for the slower but marginally more accurate tanh version. |
class |
GELUDerivative
GELU derivative
|
class |
HardSigmoid
HardSigmoid function
|
class |
HardTanh
Hard tanh elementwise function
|
class |
Log
Log elementwise function
|
class |
Log1p
Log1p function
|
class |
LogSigmoid
LogSigmoid function
|
class |
Mish
Mish activation function
|
class |
MishDerivative
Mish derivative
|
class |
PreciseGELU
GELU activation function - Gaussian Error Linear Units
For more details, see Gaussian Error Linear Units (GELUs) - https://arxiv.org/abs/1606.08415 Note: This op implements both the sigmoid and tanh-based approximations; to use the sigmoid approximation (recommended) use precise=false; otherwise, use precise = true for the slower but marginally more accurate tanh version. |
class |
PreciseGELUDerivative
GELU derivative
|
class |
RationalTanh
Rational Tanh Approximation elementwise function, as described at https://github.com/deeplearning4j/libnd4j/issues/351
|
class |
RectifiedTanh
RectifiedTanh
Essentially max(0, tanh(x))
|
class |
Rint
Rint function
|
class |
SELU
SELU activation function
|
class |
SetRange
Set range to a particular set of values
|
class |
Sigmoid
Sigmoid function
|
class |
SigmoidDerivative
Deprecated.
|
class |
Sin
Log elementwise function
|
class |
Sinh
Sinh function
|
class |
SoftPlus |
class |
SoftSign
Softsign element-wise activation function.
|
class |
Stabilize
Stabilization function, forces values to be within a range
|
class |
Swish
Swish function
|
class |
SwishDerivative
Swish derivative
|
class |
Tan
Tanh elementwise function
|
class |
TanDerivative
Tan Derivative elementwise function
|
class |
Tanh
Tanh elementwise function
|
class |
TanhDerivative
Deprecated.
Use
TanhDerivative . |
Modifier and Type | Class and Description |
---|---|
class |
BaseRandomOp |
Modifier and Type | Class and Description |
---|---|
class |
AlphaDropOut
AlphaDropOut implementation as Op
|
class |
BernoulliDistribution
BernoulliDistribution implementation
|
class |
BinomialDistribution
This Op generates binomial distribution
|
class |
BinomialDistributionEx
This Op generates binomial distribution
|
class |
Choice
This Op implements numpy.choice method
It fills Z from source, following probabilities for each source element
|
class |
DropOut
DropOut implementation as Op
|
class |
DropOutInverted
Inverted DropOut implementation as Op
|
class |
GaussianDistribution
This Op generates normal distribution over provided mean and stddev
|
class |
Linspace
Linspace/arange Op implementation, generates from..to distribution within Z
|
class |
LogNormalDistribution
This Op generates log-normal distribution over provided mean and stddev
|
class |
ProbablisticMerge |
class |
TruncatedNormalDistribution
This Op generates truncated normal distribution over provided mean and stddev
|
class |
UniformDistribution |
Modifier and Type | Method and Description |
---|---|
static INDArray |
Nd4j.exec(Op op)
Execute the operation and return the result
|
static INDArray |
Nd4j.exec(Op op,
OpContext context) |
Modifier and Type | Method and Description |
---|---|
protected String |
OpProfiler.getOpClass(Op op)
This method returns op class opName
|
void |
OpProfiler.OpProfilerListener.invoke(Op op) |
void |
OpProfiler.processOpCall(Op op)
This method tracks op calls
|
void |
OpProfiler.processOpCall(Op op,
DataBuffer... tadBuffers) |
void |
OpProfiler.processStackCall(Op op,
long timeStart)
This method builds
|
void |
OpProfiler.timeOpCall(Op op,
long startTime) |
Modifier and Type | Method and Description |
---|---|
void |
StringAggregator.putTime(String key,
Op op,
long timeSpent) |
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