Uses of Class
org.nd4j.autodiff.functions.DifferentialFunction

Packages that use DifferentialFunction

Package	Description
org.nd4j.autodiff.functions
org.nd4j.autodiff.samediff
org.nd4j.autodiff.samediff.serde
org.nd4j.imports.converters
org.nd4j.imports.descriptors.properties
org.nd4j.imports.descriptors.properties.adapters
org.nd4j.imports.graphmapper
org.nd4j.imports.graphmapper.onnx
org.nd4j.imports.graphmapper.tf
org.nd4j.linalg.api.ops
org.nd4j.linalg.api.ops.impl.accum
org.nd4j.linalg.api.ops.impl.accum.bp
org.nd4j.linalg.api.ops.impl.accum.distances
org.nd4j.linalg.api.ops.impl.broadcast
org.nd4j.linalg.api.ops.impl.controlflow
org.nd4j.linalg.api.ops.impl.controlflow.compat
org.nd4j.linalg.api.ops.impl.grid
org.nd4j.linalg.api.ops.impl.indexaccum
org.nd4j.linalg.api.ops.impl.layers
org.nd4j.linalg.api.ops.impl.layers.convolution
org.nd4j.linalg.api.ops.impl.layers.recurrent
org.nd4j.linalg.api.ops.impl.loss
org.nd4j.linalg.api.ops.impl.meta
org.nd4j.linalg.api.ops.impl.scalar
org.nd4j.linalg.api.ops.impl.scalar.comparison
org.nd4j.linalg.api.ops.impl.scatter
org.nd4j.linalg.api.ops.impl.shape
org.nd4j.linalg.api.ops.impl.shape.bp
org.nd4j.linalg.api.ops.impl.shape.tensorops
org.nd4j.linalg.api.ops.impl.transforms
org.nd4j.linalg.api.ops.impl.transforms.arithmetic
org.nd4j.linalg.api.ops.impl.transforms.arithmetic.bp
org.nd4j.linalg.api.ops.impl.transforms.clip
org.nd4j.linalg.api.ops.impl.transforms.comparison
org.nd4j.linalg.api.ops.impl.transforms.dtype
org.nd4j.linalg.api.ops.impl.transforms.gradient
org.nd4j.linalg.api.ops.impl.transforms.segment
org.nd4j.linalg.api.ops.impl.transforms.segment.bp
org.nd4j.linalg.api.ops.impl.transforms.temp
org.nd4j.linalg.api.ops.persistence
org.nd4j.linalg.api.ops.random
org.nd4j.linalg.api.ops.random.compat
org.nd4j.linalg.api.ops.random.custom
org.nd4j.linalg.api.ops.random.impl
org.nd4j.linalg.lossfunctions.impl

Uses of DifferentialFunction in org.nd4j.autodiff.functions

Methods in org.nd4j.autodiff.functions that return DifferentialFunction

Modifier and Type	Method and Description
DifferentialFunction	DifferentialFunction.dup() Duplicate this function

Methods in org.nd4j.autodiff.functions with parameters of type DifferentialFunction

Modifier and Type	Method and Description
long	DifferentialFunctionFactory.getReductionLength(DifferentialFunction func)

Uses of DifferentialFunction in org.nd4j.autodiff.samediff

Subclasses of DifferentialFunction in org.nd4j.autodiff.samediff

Modifier and Type	Class and Description
class	SDVariable A variable representing a component within a graph.

Methods in org.nd4j.autodiff.samediff that return DifferentialFunction

Modifier and Type	Method and Description
DifferentialFunction[]	SameDiff.functions() Get an array of differential functions that have been defined for this SameDiff instance
DifferentialFunction	SameDiff.getFunctionById(String id) Get the function by the DifferentialFunction#getOwnName()
DifferentialFunction	SameDiff.getVariableOutputFunction(String variableName) Get the differential function (if any) that this variable is the output for

Methods in org.nd4j.autodiff.samediff that return types with arguments of type DifferentialFunction

Modifier and Type	Method and Description
org.nd4j.linalg.primitives.Pair<Map<SDVariable,DifferentialFunction>,List<DifferentialFunction>>	SameDiff.exec() Execute the SameDiff instance using the current state After execution, the arrays for variables can be obtained using SameDiff.getArrForVarName(String) or SDVariable.getArr()
org.nd4j.linalg.primitives.Pair<Map<SDVariable,DifferentialFunction>,List<DifferentialFunction>>	SameDiff.exec() Execute the SameDiff instance using the current state After execution, the arrays for variables can be obtained using SameDiff.getArrForVarName(String) or SDVariable.getArr()
List<DifferentialFunction>	SameDiff.exec(List<DifferentialFunction> ops) Executes the list of operations.
org.nd4j.linalg.primitives.Pair<Map<SDVariable,DifferentialFunction>,List<DifferentialFunction>>	SameDiff.exec(String functionName) Execute the specified SameDiff function instance
org.nd4j.linalg.primitives.Pair<Map<SDVariable,DifferentialFunction>,List<DifferentialFunction>>	SameDiff.exec(String functionName) Execute the specified SameDiff function instance
List<DifferentialFunction>	SameDiff.exec(String functionName, List<DifferentialFunction> cachedOps) Exec the given function given the ops
org.nd4j.linalg.primitives.Pair<Map<SDVariable,DifferentialFunction>,List<DifferentialFunction>>	SameDiff.execBackwards() Execute the gradient (backward pass) function on this graph. Constructs a backwards graph (differentiating the defined graph) if it does not already exist, and the executes the operations on that graph, calculating gradients for all variables. Note that after execBackwards() has completed, the gradient arrays for a each variable can be accessed using SDVariable.getGradient() followed by SDVariable.getArr() or by using SameDiff.getGradForVariable(String)
org.nd4j.linalg.primitives.Pair<Map<SDVariable,DifferentialFunction>,List<DifferentialFunction>>	SameDiff.execBackwards() Execute the gradient (backward pass) function on this graph. Constructs a backwards graph (differentiating the defined graph) if it does not already exist, and the executes the operations on that graph, calculating gradients for all variables. Note that after execBackwards() has completed, the gradient arrays for a each variable can be accessed using SDVariable.getGradient() followed by SDVariable.getArr() or by using SameDiff.getGradForVariable(String)
org.nd4j.linalg.primitives.Pair<Map<SDVariable,DifferentialFunction>,List<DifferentialFunction>>	SameDiff.execWithPlaceHolder(Map<String,INDArray> inputs) Creates and executes a list of operations based on the given variables passed in. SameDiff.resolveVariablesWith(Map) is called
org.nd4j.linalg.primitives.Pair<Map<SDVariable,DifferentialFunction>,List<DifferentialFunction>>	SameDiff.execWithPlaceHolder(Map<String,INDArray> inputs) Creates and executes a list of operations based on the given variables passed in. SameDiff.resolveVariablesWith(Map) is called
List<DifferentialFunction>	SameDiff.getVariableArgOfFunctions(String variableName) Return a list of differential functions (if any) that this variable is the input argument for

Methods in org.nd4j.autodiff.samediff with parameters of type DifferentialFunction

Modifier and Type	Method and Description
void	SameDiff.addArgsFor(SDVariable[] variables, DifferentialFunction function) Adds incoming arguments for the specified differential function to the graph
void	SameDiff.addArgsFor(String[] variables, DifferentialFunction function) Adds incoming arguments for the specified differential function to the graph
void	SameDiff.addOutgoingFor(SDVariable[] variables, DifferentialFunction function) Adds outgoing arguments to the graph for the specified DifferentialFunction Also checks for input arguments and updates the graph adding an appropriate edge when the full graph is declared.
void	SameDiff.addOutgoingFor(String[] varNames, DifferentialFunction function) Adds outgoing arguments to the graph for the specified DifferentialFunction Also checks for input arguments and updates the graph adding an appropriate edge when the full graph is declared.
void	SameDiff.addPropertyForFunction(DifferentialFunction functionFor, String propertyName, INDArray property) Add a property for the given function
void	SameDiff.addPropertyForFunction(DifferentialFunction functionFor, String propertyName, long property) Add a property for the given function
void	SameDiff.addPropertyToResolve(DifferentialFunction forFunction, String arrayName) Adds a property that needs to be resolve for later.
void	SameDiff.addVariableMappingForField(DifferentialFunction function, String fieldName, String varName) Adds a field name -> variable name mapping for a given function. This is used for model import where there is an unresolved variable at the time of calling any GraphMapper.importGraph(File) .
protected int	SameDiff.asFlatNode(DifferentialFunction node, com.google.flatbuffers.FlatBufferBuilder bufferBuilder, List<SDVariable> variables, Map<String,Integer> reverseMap, Map<String,Integer> forwardMap, Map<String,Integer> framesMap, AtomicInteger idCounter, Integer id)
SDVariable[]	SameDiff.generateOutputVariableForOp(DifferentialFunction function) Generate the variables based on the given input op and return the output variable names.
SDVariable[]	SameDiff.generateOutputVariableForOp(DifferentialFunction function, String baseName) Generate the variables based on the given input op and return the output variable names.
String	SameDiff.getBaseNameForFunction(DifferentialFunction function) Returns the base name for the given function if any (may return null)
String[]	SameDiff.getInputsForFunction(DifferentialFunction function) Returns the name(s) of the inputs for the given function
SDVariable[]	SameDiff.getInputVariablesForFunction(DifferentialFunction function) Get the input variable(s) for the specified differential function
String[]	SameDiff.getOutputsForFunction(DifferentialFunction function) Returns the name(s) of the outputs for the given function
SDVariable[]	SameDiff.getOutputVariablesForFunction(DifferentialFunction function) Get the output variable(s) for the specified differential function
<T> T	SameDiff.getPropertyForFunction(DifferentialFunction functionInstance, String propertyName) Get the property for a given function
String	SameDiff.getVarNameForFieldAndFunction(DifferentialFunction function, String fieldName) Get the variable name to use for resolving a given field for a given function during import time.
boolean	SameDiff.hasArgs(DifferentialFunction function) Returns true if this function already has defined arguments
boolean	SameDiff.hasPropertiesToResolve(DifferentialFunction function) Returns true if the given function has ndarray properties to resolve.
void	SameDiff.printFunction(DifferentialFunction differentialFunction) Print the given function for debugging (will not print functions)
List<String>	SameDiff.propertiesToResolveForFunction(DifferentialFunction function) Return the properties to resolve for the given function.
void	SameDiff.putFunctionForId(String id, DifferentialFunction function) Put the function for the given id
void	SameDiff.removeArgFromFunction(String varName, DifferentialFunction function) Remove an argument for a function.
void	SameDiff.setBaseNameForFunctionInstanceId(String baseName, DifferentialFunction function) Sets a base name for the function id.

Method parameters in org.nd4j.autodiff.samediff with type arguments of type DifferentialFunction

Modifier and Type	Method and Description
List<DifferentialFunction>	SameDiff.exec(List<DifferentialFunction> ops) Executes the list of operations.
List<DifferentialFunction>	SameDiff.exec(String functionName, List<DifferentialFunction> cachedOps) Exec the given function given the ops
INDArray	SameDiff.execAndEndResult(List<DifferentialFunction> ops) Execute the specified ops and return the output of the last one
List<SDVariable>	SameDiff.getVariablesAssociatedWithFunctions(List<DifferentialFunction> functions) Get the SDVariable associated with each function based on the outputVariables() ()}

Uses of DifferentialFunction in org.nd4j.autodiff.samediff.serde

Methods in org.nd4j.autodiff.samediff.serde that return DifferentialFunction

Modifier and Type	Method and Description
static DifferentialFunction	FlatBuffersMapper.fromFlatNode(FlatNode fn)

Uses of DifferentialFunction in org.nd4j.imports.converters

Methods in org.nd4j.imports.converters that return DifferentialFunction

Modifier and Type	Method and Description
DifferentialFunction	DifferentialFunctionClassHolder.getInstance(String name)
DifferentialFunction	DifferentialFunctionClassHolder.getOpWithOnnxName(String onnxName)
DifferentialFunction	DifferentialFunctionClassHolder.getOpWithTensorflowName(String tensorflowName) Get the

Methods in org.nd4j.imports.converters that return types with arguments of type DifferentialFunction

Modifier and Type	Method and Description
Map<String,DifferentialFunction>	DifferentialFunctionClassHolder.getTensorFlowNames()

Methods in org.nd4j.imports.converters with parameters of type DifferentialFunction

Modifier and Type	Method and Description
Map<String,Field>	DifferentialFunctionClassHolder.getFieldsForFunction(DifferentialFunction function) Get the fields for a given DifferentialFunction

Uses of DifferentialFunction in org.nd4j.imports.descriptors.properties

Methods in org.nd4j.imports.descriptors.properties with parameters of type DifferentialFunction

Modifier and Type	Method and Description
void	AttributeAdapter.mapAttributeFor(Object inputAttributeValue, Field fieldFor, DifferentialFunction on) Map the attribute using the specified field on the specified function on adapting the given input type to the type of the field for the specified function.

Uses of DifferentialFunction in org.nd4j.imports.descriptors.properties.adapters

Methods in org.nd4j.imports.descriptors.properties.adapters with parameters of type DifferentialFunction

Modifier and Type	Method and Description
void	ConditionalFieldValueIntIndexArrayAdapter.mapAttributeFor(Object inputAttributeValue, Field fieldFor, DifferentialFunction on)
void	DataTypeAdapter.mapAttributeFor(Object inputAttributeValue, Field fieldFor, DifferentialFunction on)
void	SizeThresholdIntArrayIntIndexAdpater.mapAttributeFor(Object inputAttributeValue, Field fieldFor, DifferentialFunction on)
void	ConditionalFieldValueNDArrayShapeAdapter.mapAttributeFor(Object inputAttributeValue, Field fieldFor, DifferentialFunction on)
void	NDArrayShapeAdapter.mapAttributeFor(Object inputAttributeValue, Field fieldFor, DifferentialFunction on)
void	IntArrayIntIndexAdpater.mapAttributeFor(Object inputAttributeValue, Field fieldFor, DifferentialFunction on)
void	StringNotEqualsAdapter.mapAttributeFor(Object inputAttributeValue, Field fieldFor, DifferentialFunction on)
void	BooleanAdapter.mapAttributeFor(Object inputAttributeValue, Field fieldFor, DifferentialFunction on)
void	StringEqualsAdapter.mapAttributeFor(Object inputAttributeValue, Field fieldFor, DifferentialFunction on)

Uses of DifferentialFunction in org.nd4j.imports.graphmapper

Methods in org.nd4j.imports.graphmapper that return DifferentialFunction

Modifier and Type	Method and Description
DifferentialFunction	GraphMapper.getMappedOp(String name) Get the mapped op name for a given op relative to the type of node being mapped.

Methods in org.nd4j.imports.graphmapper with parameters of type DifferentialFunction

Modifier and Type	Method and Description
String	GraphMapper.getTargetMappingForOp(DifferentialFunction function, NODE_TYPE node) Get the target mapping key (usually based on the node name) for the given function
void	BaseGraphMapper.mapProperties(DifferentialFunction on, NODE_TYPE node, GRAPH_TYPE graph, SameDiff sameDiff, Map<String,Map<String,PropertyMapping>> propertyMappings)
void	GraphMapper.mapProperties(DifferentialFunction on, NODE_TYPE node, GRAPH_TYPE graph, SameDiff sameDiff, Map<String,Map<String,PropertyMapping>> propertyMappings)
void	GraphMapper.mapProperty(String name, DifferentialFunction on, NODE_TYPE node, GRAPH_TYPE graph, SameDiff sameDiff, Map<String,Map<String,PropertyMapping>> propertyMappingsForFunction)

Uses of DifferentialFunction in org.nd4j.imports.graphmapper.onnx

Methods in org.nd4j.imports.graphmapper.onnx that return DifferentialFunction

Modifier and Type	Method and Description
DifferentialFunction	OnnxGraphMapper.getMappedOp(String name)

Methods in org.nd4j.imports.graphmapper.onnx with parameters of type DifferentialFunction

Modifier and Type	Method and Description
String	OnnxGraphMapper.getTargetMappingForOp(DifferentialFunction function, OnnxProto3.NodeProto node)
void	OnnxGraphMapper.initFunctionFromProperties(String mappedTfName, DifferentialFunction on, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.NodeProto node, OnnxProto3.GraphProto graph) Init a function's attributes
void	OnnxGraphMapper.mapProperty(String name, DifferentialFunction on, OnnxProto3.NodeProto node, OnnxProto3.GraphProto graph, SameDiff sameDiff, Map<String,Map<String,PropertyMapping>> propertyMappingsForFunction)

Uses of DifferentialFunction in org.nd4j.imports.graphmapper.tf

Methods in org.nd4j.imports.graphmapper.tf that return DifferentialFunction

Modifier and Type	Method and Description
DifferentialFunction	TFGraphMapper.getMappedOp(String name)

Methods in org.nd4j.imports.graphmapper.tf with parameters of type DifferentialFunction

Modifier and Type	Method and Description
String	TFGraphMapper.getTargetMappingForOp(DifferentialFunction function, NodeDef node)
void	TFGraphMapper.initFunctionFromProperties(DifferentialFunction on, Map<String,AttrValue> attributesForNode, NodeDef node, GraphDef graph) Calls TFGraphMapper.initFunctionFromProperties(DifferentialFunction, Map, NodeDef, GraphDef) using tensorflowName()
void	TFGraphMapper.initFunctionFromProperties(String mappedTfName, DifferentialFunction on, Map<String,AttrValue> attributesForNode, NodeDef node, GraphDef graph) Init a function's attributes
void	TFGraphMapper.mapProperty(String name, DifferentialFunction on, NodeDef node, GraphDef graph, SameDiff sameDiff, Map<String,Map<String,PropertyMapping>> propertyMappingsForFunction)

Uses of DifferentialFunction in org.nd4j.linalg.api.ops

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops

Modifier and Type	Class and Description
class	BaseAccumulation Base class for accumulation, initiates the initial entry with respect to the child class.
class	BaseBroadcastOp
class	BaseGradientOp A gradient op always makes the following assumptions: there is always a y (beacuse of backpropagating or using the chain rule) and that it is special exec (for now) This op opType sis meant to be used to build derivative operations.
class	BaseIndexAccumulation Index based reduction algo
class	BaseModule Abstract base class for Module that handles Dynamic ops and handles nesting.
class	BaseOp Base op.
class	BaseScalarOp Base scalar operation
class	BaseTransformOp A base op for basic getters and setters
class	DefaultOpConverter
class	DynamicCustomOp Basic implementation for CustomOp
class	NoOp
class	ShapeOp Shape manipulation ops

Methods in org.nd4j.linalg.api.ops with parameters of type DifferentialFunction

Modifier and Type	Method and Description
DynamicCustomOp.DynamicCustomOpsBuilder	DynamicCustomOp.SameDiffBuilder.addInputs(DifferentialFunction... inputs)
DynamicCustomOp.DynamicCustomOpsBuilder	DynamicCustomOp.SameDiffBuilder.addOutputs(DifferentialFunction... outputs)

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.accum

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.accum

Modifier and Type	Class and Description
class	All Boolean AND accumulation
class	AMax Calculate the absolute max over a vector
class	AMean Calculate the absolute mean of the given vector
class	AMin Calculate the absolute minimum over a vector
class	Any Boolean AND pairwise transform
class	ArgMax
class	ArgMin ArgMin function
class	ASum Absolute sum the components
class	BaseReduction
class	BatchMmul Batched matrix multiplication.
class	Bias Calculate a bias
class	CountNonZero Count the number of non-zero elements
class	CountZero Count the number of zero elements
class	CumProd
class	CumSum Cumulative sum operation, optionally along dimension.
class	Dot Dot product
class	Entropy Entropy Op - returns the entropy (information gain, or uncertainty of a random variable).
class	EqualsWithEps Operation for fast INDArrays equality checks
class	LogEntropy Log Entropy Op - returns the log entropy (information gain, or uncertainty of a random variable).
class	LogSumExp LogSumExp - this op returns https://en.wikipedia.org/wiki/LogSumExp
class	MatchCondition This operation returns number of elements matching specified condition
class	Max Calculate the max over an array
class	Mean Calculate the mean of the vector
class	Min Calculate the min over an array
class	Mmul Matrix multiplication/dot product
class	Moments
class	Norm1 Sum of absolute values
class	Norm2 Sum of squared values (real) Sum of squared complex modulus (complex)
class	NormalizeMoments
class	NormMax The max absolute value
class	Prod Prod the components
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
class	StandardDeviation Standard deviation (sqrt of variance)
class	SufficientStatistics Sufficient statistics: returns 3 or 4 output arrays: If shift is not provided: count, sum of elements, sum of squares If shift is provided: count, sum of elements, sum of squares, shift
class	Sum Sum the components
class	TensorMmul TensorMmul
class	Variance Variance with bias correction.
class	ZeroFraction Compute the fraction of zero elements

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.accum.bp

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.accum.bp

Modifier and Type	Class and Description
class	BaseReductionBp
class	CumProdBp Backprop op for cumulative product operation
class	CumSumBp Backprop op for cumulative sum operation
class	DotBp Backprop op for Dot pairwise reduction operation
class	MaxBp Backprop op for Max reduction operation
class	MeanBp Backprop op for Mean reduction operation
class	MinBp Backprop op for Min reduction operation
class	Norm1Bp Backprop op for Norm1 reduction operation
class	Norm2Bp Backprop op for Norm2 reduction operation
class	NormMaxBp Backprop op for Norm Max reduction operation
class	ProdBp Backprop op for Product reduction operation
class	SquaredNormBp Backprop op for squared norm (sum_i x_i^2) reduction operation
class	StandardDeviationBp Backprop op for standard deviation reduction operation
class	SumBp Backprop op for Sum reduction operation
class	VarianceBp Backprop op for variance reduction operation

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.accum.distances

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.accum.distances

Modifier and Type	Class and Description
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	EuclideanDistance Euclidean distance
class	HammingDistance Hamming distance (simple)
class	JaccardDistance Jaccard distance (dissimilarity)
class	ManhattanDistance Manhattan distance

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.broadcast

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.broadcast

Modifier and Type	Class and Description
class	BiasAdd Bias addition gradient operation.
class	BiasAddGrad
class	BroadcastAddOp
class	BroadcastAMax Broadcast Abs Max comparison op
class	BroadcastAMin Broadcast Abs Min comparison op
class	BroadcastCopyOp
class	BroadcastDivOp
class	BroadcastEqualTo
class	BroadcastGradientArgs
class	BroadcastGreaterThan
class	BroadcastGreaterThanOrEqual
class	BroadcastLessThan
class	BroadcastLessThanOrEqual
class	BroadcastMax Broadcast Max comparison op
class	BroadcastMin Broadcast Min comparison op
class	BroadcastMulOp
class	BroadcastNotEqual
class	BroadcastRDivOp Broadcast reverse divide
class	BroadcastRSubOp
class	BroadcastSubOp
class	BroadcastTo BroadcastTo op: given 2 input arrays, content X and shape Y, broadcast X to the shape specified by the content of Y.

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.controlflow

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.controlflow

Modifier and Type	Class and Description
class	If Equivalent to tensorflow's conditional op.
class	IfDerivative
class	Select
class	Where
class	WhereNumpy
class	While Equivalent to tensorflow's while loop Takes in: loopVars loop body condition runs loop till condition is false.
class	WhileDerivative While loop derivative

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.controlflow.compat

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.controlflow.compat

Modifier and Type	Class and Description
class	BaseCompatOp
class	Enter
class	Exit
class	LoopCond
class	Merge
class	NextIteration
class	StopGradient
class	Switch

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.grid

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.grid

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.

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.indexaccum

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.indexaccum

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

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.layers

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.layers

Modifier and Type	Class and Description
class	Linear Linear: a * bT

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.layers.convolution

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.layers.convolution

Modifier and Type	Class and Description
class	AvgPooling2D Average Pooling2D operation
class	AvgPooling3D Average Pooling3D operation
class	BatchNorm BatchNorm operation
class	BatchNormDerivative BatchNormDerivative operation
class	Col2Im Col2Im operation.
class	Conv1D Conv2D operation
class	Conv2D Conv2D operation
class	Conv2DDerivative Conv2DDerivative operation
class	Conv3D Conv3D operation
class	Conv3DDerivative Conv3DDerivative operation
class	DeConv2D DeConv2D operation
class	DeConv2DDerivative DeConv2DDerivative operation
class	DeConv2DTF DeConv2D operation, TF-wrapper
class	DepthToSpace Inverse operation to SpaceToDepth.
class	DepthwiseConv2D Depthwise Conv2D operation
class	FullConv3D FullConv3D operation
class	FullConv3DDerivative FullConv3DDerivative operation
class	Im2col Im2col operation
class	Im2colBp Im2col operation
class	LegacyPooling2D Deprecated. Note: This operation will be removed in a future release
class	LocalResponseNormalization LocalResponseNormalization operation
class	LocalResponseNormalizationDerivative LocalResponseNormalizationDerivative operation
class	MaxPooling2D Max Pooling2D operation
class	MaxPooling3D Max Pooling3D operation
class	Pooling2D Pooling2D operation
class	Pooling2DDerivative Pooling2DDerivative operation
class	Pooling3D Pooling3D operation
class	Pooling3DDerivative Pooling3DDerivative operation
class	SConv2D Separable convolution 2D operation
class	SConv2DDerivative SConv2DDerivative operation
class	SpaceToDepth This operation takes 4D array in, in either NCHW or NHWC format, and moves data from spatial dimensions (HW) to channels (C) for given blockSize
class	Upsampling2d Upsampling operation
class	Upsampling2dDerivative UpsamplingDerivative operation

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.layers.recurrent

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.layers.recurrent

Modifier and Type	Class and Description
class	GRUCell GRU cell for RNNs
class	LSTMCell LSTM cell
class	SRU Simple recurrent unit
class	SRUCell A simple recurrent unit cell.

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.loss

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.loss

Modifier and Type	Class and Description
class	AbsoluteDifferenceLoss Absolute difference loss
class	BaseLoss
class	CosineDistanceLoss Cosine distance loss
class	HingeLoss Hinge loss
class	HuberLoss Huber loss
class	L2Loss L2 loss op wrapper
class	LogLoss Binary log loss, or cross entropy loss: -1/numExamples * sum_i (labels[i] * log(predictions[i] + epsilon) + (1-labels[i]) * log(1-predictions[i] + epsilon))
class	MeanPairwiseSquaredErrorLoss Absolute difference loss
class	MeanSquaredErrorLoss Mean squared error loss
class	SigmoidCrossEntropyLoss Sigmoid cross entropy loss with logits
class	SoftmaxCrossEntropyLoss Softmax cross entropy loss
class	SoftmaxCrossEntropyWithLogitsLoss Softmax cross entropy loss with Logits
class	SparseSoftmaxCrossEntropyLossWithLogits Sparse softmax cross entropy loss with logits.
class	WeightedCrossEntropyLoss Weighted cross entropy loss with logits

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.meta

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.meta

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 Accumulation, Variance or Reduce3 op

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.scalar

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.scalar

Modifier and Type	Class and Description
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

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.scalar.comparison

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.scalar.comparison

Modifier and Type	Class and Description
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	ScalarNotEquals Return a binary (0 or 1) when greater than a number
class	ScalarSetValue Scalar value set operation.

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.scatter

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.scatter

Modifier and Type	Class and Description
class	ScatterAdd Created by farizrahman4u on 3/23/18.
class	ScatterDiv Created by farizrahman4u on 3/23/18.
class	ScatterMax
class	ScatterMin
class	ScatterMul Created by farizrahman4u on 3/23/18.
class	ScatterNd Scatter ND operation
class	ScatterNdAdd Scatter ND add operation
class	ScatterNdSub Scatter ND subtract operation
class	ScatterNdUpdate Scatter ND add operation
class	ScatterSub Created by farizrahman4u on 3/23/18.
class	ScatterUpdate Scatter update op

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.shape

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.shape

Modifier and Type	Class and Description
class	ApplyGradientDescent Reshape function
class	Broadcast Broadcast function
class	BroadcastDynamicShape Broadcast dynamic shape function
class	Concat
class	ConfusionMatrix
class	Cross Pairwise cross-product of two tensors of the same shape.
class	Diag Computes a diagonal matrix of shape (n, n) from a vector of length n.
class	DiagPart Return the diagonal part of a tensor.
class	ExpandDims ExpandDims function
class	Eye Computes a batch of identity matrices of shape (numRows, numCols), returns a single tensor.
class	Gather Gather op
class	GatherNd GatherND op
class	MergeAvg
class	MergeMax
class	MergeSum
class	MeshGrid
class	OneHot Created by susaneraly on 3/14/18.
class	OnesLike OnesLike function - gives an output array with all values/entries being 1, with the same shape as the input.
class	ParallelStack Stacks n input tensors of same shape to tensor of rank n + 1.
class	Permute Permute function
class	Rank Rank function
class	Repeat Repeat function
class	Reshape Reshape function
class	RollAxis Transpose function
class	SequenceMask Created by farizrahman4u on 3/28/18.
class	Shape Returns the shape of the input array.
class	ShapeN Returns the shape of N input array as as N output arrays
class	Size Returns the size of the input as a rank 0 array
class	SizeAt Returns the size of the input along given dimension as a rank 0 array
class	Slice Slice function
class	Split Split op
class	SplitV SplitV op
class	Squeeze
class	Stack Stack operation.
class	StridedSlice Strided Slice function
class	Tile Tile function
class	Transpose Transpose function
class	Unstack Unstack op conversion
class	ZerosLike Reshape function

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.shape.bp

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.shape.bp

Modifier and Type	Class and Description
class	ConcatBp Backprop op for concat
class	SliceBp Slice backprop function
class	StridedSliceBp Strided Slice backprop function
class	TileBp Tile backprop function

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.shape.tensorops

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.shape.tensorops

Modifier and Type	Class and Description
class	BaseTensorOp
class	TensorArrayConcatV3
class	TensorArrayGatherV3
class	TensorArrayReadV3
class	TensorArrayScatterV3
class	TensorArrayV3
class	TensorArrayWriteV3
class	TensorSizeV3

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms

Modifier and Type	Class and Description
class	Abs Abs elementwise function
class	ACos Log elementwise function
class	ACosh ACosh elementwise function
class	And Boolean AND pairwise transform
class	Angle Angle op for tensorflow import Given ND4J currently only supports real arrays; hence by definition this always outputs 0
class	ASin Arcsin elementwise function
class	ASinh Arcsin elementwise function
class	Assign Assign op: x = y, with broadcast as required
class	ATan Arc Tangent elementwise function
class	ATan2 Arc Tangent elementwise function
class	ATanh tan elementwise function
class	BaseDynamicTransformOp
class	BatchToSpace N-dimensional batch to space operation.
class	BinaryMinimalRelativeError
class	BinaryRelativeError
class	BinCount BinCount: counts the number of times each value appears in an integer array.
class	Ceil Ceiling elementwise function
class	Constant
class	Cos Cosine elementwise function
class	Cosh Cosine Hyperbolic elementwise function
class	Cube Cube (x^3) elementwise function
class	Dilation2D Dilation2D op wrapper
class	DynamicPartition Transforms a given input tensor into numPartitions partitions, as indicated by the indices in "partitions".
class	DynamicStitch Transforms a given input tensor into numPartitions partitions, as indicated by the indices in "partitions".
class	ELU ELU: Exponential Linear Unit (alpha=1.0) Introduced in paper: Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arn?? Clevert, Thomas Unterthiner, Sepp Hochreiter (2015) http://arxiv.org/abs/1511.07289
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	Fill Fill an array of given "shape" with the provided "value", e.g.
class	Floor Floor elementwise function
class	HardSigmoid HardSigmoid function
class	HardTanh Hard tanh elementwise function
class	Histogram
class	HistogramFixedWidth Histogram fixed with op
class	Identity Identity function
class	InTopK In Top K op
class	InvertPermutation Inverse of index permutation.
class	IsFinite IsFinite function
class	IsInf IsInf function
class	IsMax [1, 2, 3, 1] -> [0, 0, 1, 0]
class	IsNaN IsNaN function
class	LeakyReLU Leaky Rectified linear unit.
class	LegacyDropOut DropOut implementation as Op PLEASE NOTE: This is legacy DropOut implementation, please consider using op with the same opName from randomOps
class	LegacyDropOutInverted Inverted DropOut implementation as Op PLEASE NOTE: This is legacy DropOutInverted implementation, please consider using op with the same opName from randomOps
class	Log Log elementwise function
class	Log1p Log1p function
class	LogicalAnd
class	LogicalOr
class	LogicalXor
class	LogSigmoid LogSigmoid function
class	LogSigmoidDerivative LogSigmoid derivative
class	LogSoftMax Log(softmax(X))
class	LogX Log on arbitrary base op
class	MatchConditionTransform Absolute sum the components
class	MatrixDeterminant Matrix Determinant op Given input with shape [..., N, N] output the determinant for each sub-matrix.
class	MatrixDiag
class	MatrixDiagPart
class	MatrixInverse Matrix Inverse Function
class	MatrixSetDiag
class	MaxOut Max out activation: http://arxiv.org/pdf/1302.4389.pdf
class	MirrorPad
class	Negative Negative function
class	Not Boolean AND pairwise transform
class	OldAtan2Op atan2 operation
class	OldIdentity Identity function
class	OldReverse OldReverse op
class	OldSoftMax Soft max function row_maxes is a row vector (max for each row) row_maxes = rowmaxes(input) diff = exp(input - max) / diff.rowSums() Outputs a probability distribution.
class	OneMinus 1 - input
class	Or Boolean OR pairwise transform
class	Pad Pad op
class	ParallelConcat
class	Pow Pow function
class	PowDerivative Pow derivative z = n * x ^ (n-1)
class	RationalTanh Rational Tanh Approximation elementwise function, as described at https://github.com/deeplearning4j/libnd4j/issues/351
class	Reciprocal Created by susaneraly on 3/28/18.
class	RectifedLinear Rectified linear units
class	RectifiedTanh RectifiedTanh Essentially max(0, tanh(x))
class	RelativeError
class	Relu6 Rectified linear unit 6, i.e.
class	ReluLayer Composed op: relu((X, W) + b)
class	ReplaceNans Element-wise "Replace NaN" implementation as Op
class	Reverse
class	ReverseSequence Created by farizrahman4u on 3/16/18.
class	ReverseV2 This is compatibility op for ReverseV2
class	Rint Rint function
class	Round Rounding function
class	RSqrt RSqrt function
class	SELU SELU activation function
class	Set Set
class	SetRange Set range to a particular set of values
class	Sigmoid Sigmoid function
class	SigmoidDerivative Sigmoid derivative
class	Sign Signum function
class	Sin Log elementwise function
class	Sinh Sinh function
class	SoftMax Soft max function row_maxes is a row vector (max for each row) row_maxes = rowmaxes(input) diff = exp(input - max) / diff.rowSums() Outputs a probability distribution.
class	SoftPlus
class	SoftSign Softsign element-wise activation function.
class	SpaceToBatch N-dimensional space to batch operation.
class	Sqrt Sqrt function
class	Square Square function (x ^ 2)
class	Stabilize Stabilization function, forces values to be within a range
class	Step Unit step function.
class	Svd SVD - singular value decomposition
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 Tanh derivative
class	TimesOneMinus If x is input: output is x*(1-x)
class	TopK Top K op
class	Trace Matrix trace operation
class	Unique
class	UniqueWithCounts
class	Xor Boolean XOR pairwise transform
class	XwPlusB Composed op: mmul (X, W) + b
class	Zeta Element-wise Zeta function.

Methods in org.nd4j.linalg.api.ops.impl.transforms that return DifferentialFunction

Modifier and Type	Method and Description
DifferentialFunction	Constant.dup()

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.arithmetic

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.arithmetic

Modifier and Type	Class and Description
class	AddOp Addition operation
class	Axpy Level 1 blas op Axpy as libnd4j native op
class	CopyOp Copy operation
class	DivOp Division operation
class	FloorDivOp Truncated division operation
class	FloorModOp Floor mod
class	FModOp Floating-point mod
class	MergeAddOp Addition operation for n operands, called "mergeadd" in libnd4j
class	MulOp Multiplication operation
class	OldAddOp Add operation for two operands
class	OldDivOp Division operation
class	OldFloorDivOp Truncated division operation
class	OldFModOp Floating point remainder
class	OldMulOp Multiplication operation
class	OldRDivOp OldReverse Division operation
class	OldSubOp Division operation
class	RDivOp OldReverse Division operation
class	RealDivOp RealDivision operation
class	RemainderOp Floating-point remainder operation
class	RSubOp Reverse subtraction operation
class	SquaredDifferenceOp Squared difference operation, i.e.
class	SubOp Subtraction operation
class	TruncateDivOp Truncated division operation

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.arithmetic.bp

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.arithmetic.bp

Modifier and Type	Class and Description
class	AddBpOp Addition backprop operation.
class	BaseArithmeticBackpropOp Base arithmetic backprop operation
class	DivBpOp Division backprop operation.
class	FloorDivBpOp Floor div backprop operation.
class	FloorModBpOp Floor div backprop operation.
class	MulBpOp Division backprop operation.
class	RDivBpOp Division backprop operation.
class	RSubBpOp Division backprop operation.
class	SquaredDifferenceBpOp Backprop op for squared difference operation, i.e.
class	SubBpOp Division backprop operation.

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.clip

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.clip

Modifier and Type	Class and Description
class	ClipByNorm
class	ClipByNormBp
class	ClipByValue

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.comparison

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.comparison

Modifier and Type	Class and Description
class	Choose This op allows us to (based on the passed in condition) to return the element fulfilling the condition.
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
class	EqualTo Bit mask over the ndarrays as to whether the components are equal or not
class	GreaterThan Bit mask over the ndarrays as to whether the components are greater than or not
class	GreaterThanOrEqual Bit mask over the ndarrays as to whether the components are greater than or equal or not
class	IsNonDecreasing This op takes 1 n-dimensional array as input, and returns true if for every adjacent pair we have x[i] <= x[i+1].
class	IsNumericTensor This op takes 1 n-dimensional array as input, and returns true if input is a numeric array.
class	IsStrictlyIncreasing This op takes 1 n-dimensional array as input, and returns true if for every adjacent pair we have x[i] < x[i+1].
class	LessThan Bit mask over the ndarrays as to whether the components are less than or not
class	LessThanOrEqual Bit mask over the ndarrays as to whether the components are less than or equal or not
class	ListDiff
class	NotEqualTo Not equal to function: Bit mask over whether 2 elements are not equal or not
class	OldEqualTo Bit mask over the ndarrays as to whether the components are equal or not
class	OldGreaterThan Bit mask over the ndarrays as to whether the components are greater than or not
class	OldGreaterThanOrEqual Bit mask over the ndarrays as to whether the components are greater than or equal or not
class	OldLessThan Bit mask over the ndarrays as to whether the components are less than or not
class	OldLessThanOrEqual Bit mask over the ndarrays as to whether the components are less than or equal or not
class	OldMax Max function
class	OldMin Min function
class	OldNotEqualTo Not equal to function: Bit mask over whether 2 elements are not equal or not

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.dtype

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.dtype

Modifier and Type	Class and Description
class	Cast Cast op wrapper.

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.gradient

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.gradient

Modifier and Type	Class and Description
class	CubeDerivative Cube derivative, e.g.
class	DynamicPartitionBp Backprop operation for dynamic partition
class	ELUDerivative Derivative of ELU: Exponential Linear Unit (alpha=1.0) Introduced in paper: Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arn?? Clevert, Thomas Unterthiner, Sepp Hochreiter (2015) http://arxiv.org/abs/1511.07289
class	GradientBackwardsMarker
class	HardSigmoidDerivative HardSigmoid derivative
class	HardTanhDerivative Hard tanh elementwise derivative function
class	LeakyReLUDerivative Leaky ReLU derivative.
class	LogSoftMaxDerivative
class	RationalTanhDerivative Rational Tanh Derivative, as described at https://github.com/deeplearning4j/libnd4j/issues/351 Calculates dOut/dIn given input, not dL/dIn given dL/dOut and input
class	RectifiedTanhDerivative Rectified Tanh Derivative
class	Relu6Derivative Derivative of Rectified linear unit 6, i.e.
class	SELUDerivative SELU Derivative elementwise function https://arxiv.org/pdf/1706.02515.pdf
class	SoftmaxBp Softmax backpropagation op - dL/dIn from in and dL/dOut
class	SoftMaxDerivative Deprecated. To be replaced by SoftmaxBp
class	SoftSignDerivative SoftSign derivative.

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.segment

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.segment

Modifier and Type	Class and Description
class	SegmentMax Segment max operation
class	SegmentMean Segment mean operation
class	SegmentMin Segment min operation
class	SegmentProd Segment product operation
class	SegmentSum Segment sum operation
class	UnsortedSegmentMax Unsorted segment max operation
class	UnsortedSegmentMean Unsorted segment mean operation
class	UnsortedSegmentMin Unsorted segment min operation
class	UnsortedSegmentProd Unsorted segment product operation
class	UnsortedSegmentSqrtN Unsorted Sqrt(count) op
class	UnsortedSegmentSum Unsorted segment sum operation

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.segment.bp

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.segment.bp

Modifier and Type	Class and Description
class	SegmentMaxBp Segment max backprop operation
class	SegmentMeanBp Segment mean backprop operation
class	SegmentMinBp Segment min backprop operation
class	SegmentProdBp Segment product backprop operation
class	SegmentSumBp Segment sum backprop operation
class	UnsortedSegmentMaxBp Unsorted segment max backprop operation
class	UnsortedSegmentMeanBp Unsorted segment mean backprop operation
class	UnsortedSegmentMinBp Unsorted segment min backprop operation
class	UnsortedSegmentProdBp Unsorted segment product backprop operation
class	UnsortedSegmentSqrtNBp Unsorted segment sqrt(n) backprop operation
class	UnsortedSegmentSumBp Unsorted segment sum backprop operation

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.temp

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.impl.transforms.temp

Modifier and Type	Class and Description
class	ExternalErrorsFunction

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.persistence

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.persistence

Modifier and Type	Class and Description
class	RestoreV2
class	SaveV2

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.random

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.random

Modifier and Type	Class and Description
class	BaseRandomOp

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.random.compat

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.random.compat

Modifier and Type	Class and Description
class	RandomStandardNormal This op is a wrapper for RandomNormal Op

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.random.custom

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.random.custom

Modifier and Type	Class and Description
class	DistributionUniform Uniform distribution wrapper
class	RandomBernoulli Random bernoulli distribution: p(x=1) = p, p(x=0) = 1-p i.e., output is 0 or 1 with probability p.
class	RandomExponential Random exponential distribution: p(x) = lambda * exp(-lambda * x)
class	RandomNormal Random normal distribution

Uses of DifferentialFunction in org.nd4j.linalg.api.ops.random.impl

Subclasses of DifferentialFunction in org.nd4j.linalg.api.ops.random.impl

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	Range Range Op implementation, generates from..to distribution within Z
class	TruncatedNormalDistribution This Op generates truncated normal distribution over provided mean and stddev
class	UniformDistribution

Uses of DifferentialFunction in org.nd4j.linalg.lossfunctions.impl

Subclasses of DifferentialFunction in org.nd4j.linalg.lossfunctions.impl

Modifier and Type	Class and Description
class	LossBinaryXENT Binary cross entropy loss function https://en.wikipedia.org/wiki/Cross_entropy#Cross-entropy_error_function_and_logistic_regression Labels are assumed to take values 0 or 1
class	LossCosineProximity Created by susaneraly on 9/9/16.
class	LossFMeasure F???measure loss function is a loss function design for training on imbalanced datasets.
class	LossHinge Created by susaneraly on 8/15/16.
class	LossKLD Kullback Leibler Divergence loss function
class	LossL1 L1 loss function: i.e., sum of absolute errors, L = sum_i abs(predicted_i - actual_i) See also LossMAE for a mathematically similar loss function (MAE has division by N, where N is output size)
class	LossL2 L2 loss function: i.e., sum of squared errors, L = sum_i (actual_i - predicted)^2 The L2 loss function is the square of the L2 norm of the difference between actual and predicted.
class	LossMAE Mean absolute error loss function: L = 1/N sum_i abs(predicted_i - actual_i) See also LossL1 for a mathematically similar loss function (LossL1 does not have division by N, where N is output size)
class	LossMAPE Created by susaneraly on 8/15/16.
class	LossMCXENT Multi-Class Cross Entropy loss function: L = sum_i actual_i * log( predicted_i )
class	LossMixtureDensity This is a cost function associated with a mixture-density network.
class	LossMSE Mean Squared Error loss function: L = 1/N sum_i (actual_i - predicted)^2 See also LossL2 for a mathematically similar loss function (LossL2 does not have division by N, where N is output size)
class	LossMSLE Mean Squared Logarithmic Error loss function: L = 1/N sum_i (log(1+predicted_i) - log(1+actual_i))^2
class	LossMultiLabel Multi-Label-Loss Function, maybe more commonly known as BPMLL
class	LossNegativeLogLikelihood Negative log likelihood loss function
class	LossPoisson Created by susaneraly on 9/9/16.
class	LossSquaredHinge Created by susaneraly on 9/9/16.