Uses of Class
org.nd4j.autodiff.samediff.SameDiff

Packages that use SameDiff

Package	Description
org.nd4j.autodiff.execution
org.nd4j.autodiff.functions
org.nd4j.autodiff.samediff
org.nd4j.autodiff.samediff.impl
org.nd4j.autodiff.validation
org.nd4j.imports.graphmapper
org.nd4j.imports.graphmapper.onnx
org.nd4j.imports.graphmapper.tf
org.nd4j.linalg.activations
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.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.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.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 SameDiff in org.nd4j.autodiff.execution

Methods in org.nd4j.autodiff.execution with parameters of type SameDiff

Modifier and Type	Method and Description
ByteBuffer	GraphExecutioner.convertToFlatBuffers(SameDiff diff, ExecutorConfiguration configuration) This method converts given SameDiff instance to FlatBuffers representation
ByteBuffer	BasicGraphExecutioner.convertToFlatBuffers(SameDiff diff, ExecutorConfiguration configuration)
INDArray[]	GraphExecutioner.executeGraph(SameDiff graph)
INDArray[]	BasicGraphExecutioner.executeGraph(SameDiff sd) This method executes given graph and returns results PLEASE NOTE: Default configuration is used
INDArray[]	GraphExecutioner.executeGraph(SameDiff graph, ExecutorConfiguration configuration) This method executes given graph and returns results
INDArray[]	BasicGraphExecutioner.executeGraph(SameDiff graph, ExecutorConfiguration configuration) This method executes given graph and returns results
int	GraphExecutioner.registerGraph(SameDiff graph) This method stores given graph for future execution
int	BasicGraphExecutioner.registerGraph(SameDiff graph) This method stores given graph for future execution
INDArray[]	GraphExecutioner.reuseGraph(SameDiff graph, Map<Integer,INDArray> inputs)
INDArray[]	BasicGraphExecutioner.reuseGraph(SameDiff graph, Map<Integer,INDArray> inputs)

Uses of SameDiff in org.nd4j.autodiff.functions

Fields in org.nd4j.autodiff.functions declared as SameDiff

Modifier and Type	Field and Description
protected SameDiff	DifferentialFunctionFactory.sameDiff
protected SameDiff	DifferentialFunction.sameDiff

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

Modifier and Type	Method and Description
SameDiff	DifferentialFunctionFactory.sameDiff()

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

Modifier and Type	Method and Description
abstract void	DifferentialFunction.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph) Iniitialize the function from the given OnnxProto3.NodeProto
abstract void	DifferentialFunction.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph) Initialize the function from the given NodeDef

Constructors in org.nd4j.autodiff.functions with parameters of type SameDiff

Constructor and Description
DifferentialFunction(SameDiff sameDiff, boolean inPlace, Object[] extraArgs)
DifferentialFunction(SameDiff sameDiff, boolean inPlace, SDVariable[] args) Add the various arguments for this function
DifferentialFunction(SameDiff sameDiff, NodeDef nodeDef, Map<String,AttrValue> attributesForNode, GraphDef graph) Initialize the function from the given NodeDef
DifferentialFunction(SameDiff sameDiff, Object[] extraArgs)
DifferentialFunction(SameDiff sameDiff, OnnxProto3.NodeProto node, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph) Initialize the function from the given OnnxProto3.NodeProto
DifferentialFunction(SameDiff sameDiff, SDVariable[] args)
DifferentialFunctionFactory(SameDiff sameDiff)

Uses of SameDiff in org.nd4j.autodiff.samediff

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

Modifier and Type	Method and Description
static SameDiff	SameDiff.create() Create a new (empty) SameDiff instance without any functions or variables
static SameDiff	SameDiff.create(SameDiff originalSameDiff) Create a new SameDiff instance from an existing instance.
SameDiff	SameDiff.defineFunction(String function, SameDiffFunctionDefinition functionDefinition, SDVariable[] variables)
SameDiff	SameDiff.disableDebugging() Clears debugging state and disables debug mode.
SameDiff	SameDiff.dup() Clone/duplicate the SameDiff instance, including arrays etc.
SameDiff	SameDiff.enableDebugMode() Enables tracing of graphs automatically.
SameDiff	SameDiff.getFunction(String functionName) Get a SameDiff function instance given the name of the function

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

Modifier and Type	Method and Description
protected int	SameDiff.asFlatNode(String name, SameDiff scope, com.google.flatbuffers.FlatBufferBuilder bufferBuilder)
static SameDiff	SameDiff.create(SameDiff originalSameDiff) Create a new SameDiff instance from an existing instance.
SDVariable[]	SameDiffFunctionDefinition.define(SameDiff sameDiff, Map<String,INDArray> inputs, SDVariable[] variableInputs)
SDVariable	SameDiffConditional.eval(SameDiff context, SameDiffFunctionDefinition body, SDVariable[] inputVars)
void	SDVariable.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	SDVariable.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
SDVariable	SameDiff.invokeFunctionOn(String functionName, SameDiff with)
SDVariable	SameDiff.invokeGraphOn(SameDiff sameDiff)
void	SameDiff.putSubFunction(String name, SameDiff nameSpace) Associate a SameDiff namespace as a sub function.

Uses of SameDiff in org.nd4j.autodiff.samediff.impl

Methods in org.nd4j.autodiff.samediff.impl with parameters of type SameDiff

Modifier and Type	Method and Description
SDVariable	DefaultSameDiffConditional.eval(SameDiff context, SameDiffFunctionDefinition body, SDVariable[] inputVars)

Uses of SameDiff in org.nd4j.autodiff.validation

Methods in org.nd4j.autodiff.validation with parameters of type SameDiff

Modifier and Type	Method and Description
static boolean	GradCheckUtil.checkGradients(SameDiff sd)
static boolean	GradCheckUtil.checkGradients(SameDiff sd, boolean print, boolean exitOnFirstFailure)
static boolean	GradCheckUtil.checkGradients(SameDiff sd, double eps, double maxRelError, double minAbsError, boolean print, boolean exitOnFirstFailure)
static boolean	GradCheckUtil.checkGradients(SameDiff sd, double eps, double maxRelError, double minAbsError, boolean print, boolean exitOnFirstFailure, boolean skipValidation, boolean debugMode, Set<String> skipVariables)
static boolean	GradCheckUtil.checkGradients(SameDiff sd, String... skipVariables)
static void	GradCheckUtil.validateInternalState(SameDiff sd, boolean generateAndCheckGradFn)

Constructors in org.nd4j.autodiff.validation with parameters of type SameDiff

Constructor and Description
TestCase(SameDiff sameDiff)

Uses of SameDiff in org.nd4j.imports.graphmapper

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

Modifier and Type	Method and Description
SameDiff	GraphMapper.importGraph(File graphFile) Import a graph as same diff from the given file
SameDiff	BaseGraphMapper.importGraph(File graphFile)
SameDiff	GraphMapper.importGraph(GRAPH_TYPE tfGraph) This method converts given TF
SameDiff	BaseGraphMapper.importGraph(GRAPH_TYPE tfGraph) This method converts given TF
SameDiff	GraphMapper.importGraph(InputStream graphFile) Import a graph as same diff from the given file
SameDiff	BaseGraphMapper.importGraph(InputStream inputStream)
SameDiff	GraphMapper.importGraph(String graphFile) This method converts given TF graph file
SameDiff	BaseGraphMapper.importGraph(String graphFile)

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

Modifier and Type	Method and Description
void	GraphMapper.mapProperties(DifferentialFunction on, NODE_TYPE node, GRAPH_TYPE graph, SameDiff sameDiff, Map<String,Map<String,PropertyMapping>> propertyMappings)
void	BaseGraphMapper.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 SameDiff in org.nd4j.imports.graphmapper.onnx

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

Modifier and Type	Method and Description
void	OnnxGraphMapper.mapProperty(String name, DifferentialFunction on, OnnxProto3.NodeProto node, OnnxProto3.GraphProto graph, SameDiff sameDiff, Map<String,Map<String,PropertyMapping>> propertyMappingsForFunction)

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

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

Modifier and Type	Method and Description
void	TFGraphMapper.mapProperty(String name, DifferentialFunction on, NodeDef node, GraphDef graph, SameDiff sameDiff, Map<String,Map<String,PropertyMapping>> propertyMappingsForFunction)

Uses of SameDiff in org.nd4j.linalg.activations

Methods in org.nd4j.linalg.activations with parameters of type SameDiff

Modifier and Type	Method and Description
SDVariable	Activation.asSameDiff(SameDiff sd, SDVariable input) Get the Activation as a SameDiff variable
SDVariable	Activation.asSameDiff(String variableName, SameDiff sd, SDVariable input) Get the Activation as a SameDiff variable

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

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

Modifier and Type	Method and Description
void	NoOp.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	BaseOp.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	BaseBroadcastOp.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	DynamicCustomOp.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	BaseAccumulation.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	NoOp.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	BaseOp.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	BaseBroadcastOp.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	DynamicCustomOp.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	BaseAccumulation.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DynamicCustomOp.SameDiffBuilder	DynamicCustomOp.SameDiffBuilder.sameDiff(SameDiff sameDiff)
static DynamicCustomOp.SameDiffBuilder	DynamicCustomOp.sameDiffBuilder(String opName, SameDiff sameDiff)

Constructors in org.nd4j.linalg.api.ops with parameters of type SameDiff

Constructor and Description
BaseAccumulation(SameDiff sameDiff)
BaseAccumulation(SameDiff sameDiff, SDVariable i_v)
BaseAccumulation(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
BaseAccumulation(SameDiff sameDiff, SDVariable i_v, int[] dimensions, boolean keepDims)
BaseAccumulation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
BaseAccumulation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, boolean keepDims)
BaseBroadcastOp(SameDiff sameDiff)
BaseBroadcastOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BaseBroadcastOp(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BaseBroadcastOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BaseBroadcastOp(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BaseBroadcastOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BaseBroadcastOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BaseBroadcastOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BaseGradientOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
BaseGradientOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
BaseIndexAccumulation(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
BaseIndexAccumulation(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, boolean keepDims, int[] dimensions)
BaseModule(String opName, SameDiff sameDiff, SDVariable[] args, boolean inPlace, List<Module> modules)
BaseOp(SameDiff sameDiff, boolean inPlace, Object[] extraArgs)
BaseOp(SameDiff sameDiff, Object[] extraArgs)
BaseScalarOp(SameDiff sameDiff, SDVariable i_v, Number scalar)
BaseScalarOp(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
BaseScalarOp(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
BaseScalarOp(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
BaseTransformOp(SameDiff sameDiff)
BaseTransformOp(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
BaseTransformOp(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
BaseTransformOp(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
BaseTransformOp(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
BaseTransformOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
BaseTransformOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
BaseTransformOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
DynamicCustomOp(String opName, SameDiff sameDiff, SDVariable[] args)
DynamicCustomOp(String opName, SameDiff sameDiff, SDVariable[] args, boolean inPlace) Initialize this for SameDiff execution Any extra int or float arguments for operations must be added to the respective TArguments or IArguments lists upon construction
NoOp(SameDiff sd, SDVariable in)
SameDiffBuilder(String opName, SameDiff sameDiff, long hash, int numInputs, int numOutputs, boolean inplaceAllowed, int numTArguments, int numIArguments)
ShapeOp(SameDiff sameDiff)
ShapeOp(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
ShapeOp(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
ShapeOp(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)

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

Methods in org.nd4j.linalg.api.ops.impl.accum with parameters of type SameDiff

Modifier and Type	Method and Description
void	TensorMmul.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	CumSum.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	CumProd.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Mmul.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	TensorMmul.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Moments.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	CumSum.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	CumProd.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Mmul.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	NormalizeMoments.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	SoftmaxCrossEntropyLossWithLogits.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	SoftmaxCrossEntropyLoss.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	SigmoidCrossEntropyLoss.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.accum with parameters of type SameDiff

Constructor and Description
All(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
AMax(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
AMax(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
AMean(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
AMean(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
AMin(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
AMin(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
Any(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
ASum(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
ASum(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
BaseReduction(SameDiff sameDiff, SDVariable input, boolean keepDims, int... dimensions)
BaseReduction(SameDiff sameDiff, SDVariable input1, SDVariable input2, boolean keepDims, int... dimensions)
BatchMmul(SameDiff sameDiff, SDVariable[] matrices, boolean transposeA, boolean transposeB)
Bias(SameDiff sameDiff, SDVariable i_v, int[] dimensions, double mean)
Bias(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, double mean)
CountNonZero(SameDiff sameDiff, SDVariable input, int... dimensions)
CountZero(SameDiff sameDiff, SDVariable input, int... dimensions)
CumProd(SameDiff sameDiff, SDVariable x, boolean exclusive, boolean reverse, int... axis)
CumProd(SameDiff sameDiff, SDVariable x, int... axis)
CumSum(SameDiff sameDiff, SDVariable x, boolean exclusive, boolean reverse, int... axis)
CumSum(SameDiff sameDiff, SDVariable x, int... axis)
Dot(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int... dimensions)
Entropy(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
EqualsWithEps(SameDiff sameDiff, SDVariable i_v, int[] dimensions, double eps)
EqualsWithEps(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, double eps)
LogEntropy(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
LogSumExp(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
LogSumExp(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
MatchCondition(SameDiff sameDiff, SDVariable in, Condition condition, boolean keepDims, int... dimensions)
Max(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
Max(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
Mean(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
Min(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
Mmul(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
Mmul(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, MMulTranspose mt)
Moments(SameDiff sameDiff, SDVariable input)
Moments(SameDiff sameDiff, SDVariable input, int[] axes)
Norm1(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
Norm2(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
NormalizeMoments(SameDiff sameDiff, SDVariable counts, SDVariable means, SDVariable variances)
NormalizeMoments(SameDiff sameDiff, SDVariable counts, SDVariable means, SDVariable variances, double shift)
NormMax(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
NormMax(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
Prod(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
Prod(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
ShannonEntropy(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
ShannonEntropy(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
SigmoidCrossEntropyLoss(SameDiff sameDiff, SDVariable logits, SDVariable weights, SDVariable labels, int reductionMode)
SigmoidCrossEntropyLoss(SameDiff sameDiff, SDVariable logits, SDVariable weights, SDVariable labels, int reductionMode, double labelSmoothing)
SoftmaxCrossEntropyLoss(SameDiff sameDiff, SDVariable logits, SDVariable weights, SDVariable labels, int reductionMode)
SoftmaxCrossEntropyLoss(SameDiff sameDiff, SDVariable logits, SDVariable weights, SDVariable labels, int reductionMode, double labelSmoothing)
SoftmaxCrossEntropyLossWithLogits(SameDiff sameDiff, SDVariable logits, SDVariable weights, SDVariable labels, int reductionMode)
SoftmaxCrossEntropyLossWithLogits(SameDiff sameDiff, SDVariable logits, SDVariable weights, SDVariable labels, int reductionMode, double labelSmoothing)
SquaredNorm(SameDiff sameDiff, SDVariable input, boolean keepDims, int... dimensions)
StandardDeviation(SameDiff sameDiff, SDVariable i_v, boolean biasCorrected, boolean keepDims, int[] dimensions)
Sum(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
Sum(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
TensorMmul(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[][] dimensions)
TensorMmul(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[][] dimensions, MMulTranspose mMulTranspose)
Variance(SameDiff sameDiff, SDVariable i_v, boolean biasCorrected, boolean keepDims, int[] dimensions)
WeightedCrossEntropyLoss(SameDiff sameDiff, SDVariable targets, SDVariable inputs, SDVariable weights)
ZeroFraction(SameDiff sameDiff, SDVariable input)

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

Constructors in org.nd4j.linalg.api.ops.impl.accum.bp with parameters of type SameDiff

Constructor and Description
BaseReductionBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
BaseReductionBp(SameDiff sameDiff, SDVariable origInput1, SDVariable origInput2, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
CumProdBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean exclusive, boolean reverse, int... axis)
CumSumBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean exclusive, boolean reverse, int... axis)
DotBp(SameDiff sameDiff, SDVariable origInput1, SDVariable origInput2, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
MaxBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
MeanBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
MinBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
Norm1Bp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
Norm2Bp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
NormMaxBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
ProdBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
SquaredNormBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
StandardDeviationBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean biasCorrected, boolean keepDims, int... dimensions)
SumBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean keepDims, int... dimensions)
VarianceBp(SameDiff sameDiff, SDVariable origInput, SDVariable gradAtOutput, boolean biasCorrected, boolean keepDims, int... dimensions)

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

Methods in org.nd4j.linalg.api.ops.impl.accum.distances with parameters of type SameDiff

Modifier and Type	Method and Description
static List<SDVariable>	CosineSimilarity.doDiff(SameDiff sameDiff, DifferentialFunctionFactory f, SDVariable x, SDVariable y, SDVariable gradOut, int... dimensions)

Constructors in org.nd4j.linalg.api.ops.impl.accum.distances with parameters of type SameDiff

Constructor and Description
CosineDistance(SameDiff sameDiff, SDVariable i_v, int[] dimensions, Number constantNormalizedByNorm2X, Number constantNormalizedByNorm2Y)
CosineDistance(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int... dimensions)
CosineSimilarity(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
CosineSimilarity(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
EuclideanDistance(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
EuclideanDistance(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
HammingDistance(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int... dimensions)
JaccardDistance(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int... dimensions)
ManhattanDistance(SameDiff sameDiff, SDVariable i_v, int[] dimensions)
ManhattanDistance(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int... dimensions)

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

Methods in org.nd4j.linalg.api.ops.impl.broadcast with parameters of type SameDiff

Modifier and Type	Method and Description
void	BiasAdd.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.broadcast with parameters of type SameDiff

Constructor and Description
BiasAdd(SameDiff sameDiff, SDVariable input, SDVariable bias)
BiasAddGrad(SameDiff sameDiff, SDVariable input, SDVariable bias, SDVariable gradient)
BroadcastAddOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastAddOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastAddOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastAMax(SameDiff sameDiff)
BroadcastAMax(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastAMax(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastAMax(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastAMax(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastAMax(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastAMax(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastAMin(SameDiff sameDiff)
BroadcastAMin(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastAMin(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastAMin(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastAMin(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastAMin(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastAMin(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastCopyOp(SameDiff sameDiff)
BroadcastCopyOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastCopyOp(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastCopyOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastCopyOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastCopyOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastCopyOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastDivOp(SameDiff sameDiff)
BroadcastDivOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastDivOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastDivOp(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastEqualTo(SameDiff sameDiff)
BroadcastEqualTo(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastEqualTo(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastEqualTo(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastEqualTo(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastEqualTo(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastEqualTo(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastGradientArgs(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastGradientArgs(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastGradientArgs(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastGreaterThan(SameDiff sameDiff)
BroadcastGreaterThan(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastGreaterThan(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastGreaterThan(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastGreaterThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastGreaterThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastGreaterThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastGreaterThanOrEqual(SameDiff sameDiff)
BroadcastGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastLessThan(SameDiff sameDiff)
BroadcastLessThan(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastLessThan(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastLessThan(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastLessThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastLessThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastLessThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastLessThanOrEqual(SameDiff sameDiff)
BroadcastLessThanOrEqual(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastLessThanOrEqual(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastLessThanOrEqual(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastLessThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastLessThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastLessThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastMax(SameDiff sameDiff)
BroadcastMax(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastMax(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastMax(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastMax(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastMax(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastMax(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastMin(SameDiff sameDiff)
BroadcastMin(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastMin(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastMin(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastMin(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastMin(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastMin(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastMulOp(SameDiff sameDiff)
BroadcastMulOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastMulOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastMulOp(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastMulOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastMulOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastMulOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastNotEqual(SameDiff sameDiff)
BroadcastNotEqual(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastNotEqual(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastNotEqual(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastNotEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastNotEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastNotEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastRDivOp(SameDiff sameDiff)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastRDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastRSubOp(SameDiff sameDiff)
BroadcastRSubOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastRSubOp(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastRSubOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastRSubOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastRSubOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastRSubOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)
BroadcastSubOp(SameDiff sameDiff)
BroadcastSubOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, boolean inPlace)
BroadcastSubOp(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, int[] dimension, Object[] extraArgs)
BroadcastSubOp(SameDiff sameDiff, SDVariable i_v, int[] dimension, Object[] extraArgs)
BroadcastSubOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, int[] dimension)
BroadcastSubOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension)
BroadcastSubOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, int[] dimension, Object[] extraArgs)

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

Fields in org.nd4j.linalg.api.ops.impl.controlflow declared as SameDiff

Modifier and Type	Field and Description
protected SameDiff	If.falseBodyExecution
protected SameDiff	While.loopBodyExecution
protected SameDiff	If.loopBodyExecution
protected SameDiff	While.predicateExecution
protected SameDiff	If.predicateExecution

Methods in org.nd4j.linalg.api.ops.impl.controlflow that return SameDiff

Modifier and Type	Method and Description
SameDiff	IfDerivative.getFalseBodyExecution()
SameDiff	WhileDerivative.getLoopBodyExecution()
SameDiff	IfDerivative.getLoopBodyExecution()
SameDiff	WhileDerivative.getPredicateExecution()
SameDiff	IfDerivative.getPredicateExecution()

Methods in org.nd4j.linalg.api.ops.impl.controlflow with parameters of type SameDiff

Modifier and Type	Method and Description
void	While.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	If.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	While.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Select.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	If.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.controlflow with parameters of type SameDiff

Constructor and Description
If(String blockName, SameDiff parent, SDVariable[] inputVars, SameDiffFunctionDefinition conditionBody, SameDiffConditional predicate, SameDiffFunctionDefinition trueBody, SameDiffFunctionDefinition falseBody)
Select(SameDiff sameDiff, SDVariable[] args)
Select(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
Where(SameDiff sameDiff, SDVariable[] args)
Where(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
WhereNumpy(SameDiff sameDiff, SDVariable[] args)
WhereNumpy(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
While(String blockName, SameDiff parent, SDVariable[] inputVars, SameDiffConditional predicate, SameDiffFunctionDefinition condition, SameDiffFunctionDefinition trueBody)

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

Methods in org.nd4j.linalg.api.ops.impl.controlflow.compat with parameters of type SameDiff

Modifier and Type	Method and Description
void	Merge.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LoopCond.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	BaseCompatOp.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	NextIteration.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Exit.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Switch.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Enter.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

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

Constructors in org.nd4j.linalg.api.ops.impl.indexaccum with parameters of type SameDiff

Constructor and Description
FirstIndex(SameDiff sameDiff, SDVariable i_v, Condition condition, boolean keepDims, int... dimensions)
IAMax(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
IAMin(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
IMax(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
IMin(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
LastIndex(SameDiff sameDiff, SDVariable i_v, Condition condition, boolean keepDims, int... dimensions)

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

Methods in org.nd4j.linalg.api.ops.impl.layers with parameters of type SameDiff

Modifier and Type	Method and Description
void	Linear.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Linear.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.layers with parameters of type SameDiff

Constructor and Description
Linear(SameDiff sameDiff, int nIn, int nOut, WeightInitScheme weightInitScheme, WeightInitScheme biasWeightInitScheme)

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

Methods in org.nd4j.linalg.api.ops.impl.layers.convolution with parameters of type SameDiff

Modifier and Type	Method and Description
void	LocalResponseNormalization.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	DeConv2D.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Conv2D.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	AvgPooling2D.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	DepthwiseConv2D.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	MaxPooling2D.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Conv1D.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Pooling2D.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	BatchNorm.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	DepthToSpace.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LocalResponseNormalization.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	DeConv2D.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Conv2D.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	SpaceToDepth.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	AvgPooling2D.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	DeConv2DTF.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Conv3D.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	DepthwiseConv2D.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	MaxPooling2D.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Conv1D.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Pooling2D.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	BatchNorm.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.layers.convolution with parameters of type SameDiff

Constructor and Description
AvgPooling2D(SameDiff sameDiff, SDVariable input, INDArray arrayInput, INDArray arrayOutput, Pooling2DConfig config)
BatchNorm(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputArrays, INDArray[] outputArrays, boolean inPlace, boolean applyGamma, boolean applyBeta, double epsilon)
BatchNormDerivative(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputArrays, INDArray[] outputArrays, boolean inPlace, boolean applyGamma, boolean applyBeta, double epsilon)
Col2Im(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputArrays, INDArray[] outputs, Conv2DConfig conv2DConfig)
Col2Im(SameDiff sd, SDVariable input, Conv2DConfig config)
Conv1D(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputArrays, INDArray[] outputs, Conv1DConfig config)
Conv2D(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputArrays, INDArray[] outputs, Conv2DConfig config)
Conv2DDerivative(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputArrays, INDArray[] outputs, Conv2DConfig config)
Conv3D(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputs, INDArray[] outputs, Conv3DConfig conv3DConfig)
Conv3DDerivative(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputs, INDArray[] outputs, Conv3DConfig conv3DConfig)
DeConv2D(SameDiff sameDiff, SDVariable[] inputs, INDArray[] inputArrays, INDArray[] outputs, DeConv2DConfig config)
DeConv2DDerivative(SameDiff sameDiff, SDVariable[] inputs, INDArray[] inputArrays, INDArray[] outputs, DeConv2DConfig config)
DeConv2DTF(SameDiff sameDiff, SDVariable[] inputs, INDArray[] inputArrays, INDArray[] outputs, DeConv2DConfig config)
DepthToSpace(SameDiff sameDiff, SDVariable[] args, int blockSize, String dataFormat)
DepthwiseConv2D(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputArrays, INDArray[] outputs, Conv2DConfig config)
FullConv3D(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputs, INDArray[] outputs, FullConv3DConfig config)
FullConv3DDerivative(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputs, INDArray[] outputs, FullConv3DConfig conv3DConfig)
Im2col(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputArrays, INDArray[] outputs, Conv2DConfig conv2DConfig)
Im2col(SameDiff sd, SDVariable input, Conv2DConfig config)
Im2colBp(SameDiff sd, SDVariable input, Conv2DConfig config)
Im2colBp(SameDiff sameDiff, SDVariable i2cInput, SDVariable gradAtOutput, Conv2DConfig conv2DConfig)
LocalResponseNormalization(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputs, INDArray[] outputs, boolean inPlace, LocalResponseNormalizationConfig config)
LocalResponseNormalizationDerivative(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputs, INDArray[] outputs, boolean inPlace, LocalResponseNormalizationConfig config)
MaxPooling2D(SameDiff sameDiff, SDVariable input, INDArray arrayInput, INDArray arrayOutput, Pooling2DConfig config)
Pooling2D(SameDiff sameDiff, SDVariable[] inputs, INDArray[] arrayInputs, INDArray[] arrayOutputs, Pooling2DConfig config)
Pooling2DDerivative(SameDiff sameDiff, SDVariable[] inputs, INDArray[] arrayInputs, INDArray[] arrayOutputs, Pooling2DConfig config)
Pooling3D(SameDiff sameDiff, SDVariable[] inputs, INDArray[] inputArrays, INDArray[] outputs, boolean inPlace, Pooling3DConfig pooling3DConfig, Pooling3D.Pooling3DType type)
Pooling3DDerivative(SameDiff sameDiff, SDVariable[] inputs, INDArray[] inputArrays, INDArray[] outputs, boolean inPlace, Pooling3DConfig pooling3DConfig, Pooling3D.Pooling3DType type)
SConv2D(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputArrays, INDArray[] outputs, Conv2DConfig conv2DConfig)
SConv2DDerivative(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputArrays, INDArray[] outputs, Conv2DConfig conv2DConfig)
SpaceToDepth(SameDiff sameDiff, SDVariable[] args, int blockSize, String dataFormat)
Upsampling2d(SameDiff sameDiff, SDVariable input, boolean nchw, int scaleH, int scaleW)
Upsampling2dDerivative(SameDiff sameDiff, SDVariable input, SDVariable gradient, boolean nchw, int scaleH, int scaleW)

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

Methods in org.nd4j.linalg.api.ops.impl.layers.recurrent with parameters of type SameDiff

Modifier and Type	Method and Description
void	SRUCell.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LSTMCell.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	SRU.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	GRUCell.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	SRUCell.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LSTMCell.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	SRU.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	GRUCell.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.layers.recurrent with parameters of type SameDiff

Constructor and Description
GRUCell(SameDiff sameDiff, GRUCellConfiguration configuration)
LSTMCell(SameDiff sameDiff, LSTMCellConfiguration configuration)
SRU(SameDiff sameDiff, SRUConfiguration configuration)
SRUCell(SameDiff sameDiff, SRUCellConfiguration configuration)

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

Constructors in org.nd4j.linalg.api.ops.impl.loss with parameters of type SameDiff

Constructor and Description
L2Loss(SameDiff sameDiff, SDVariable[] args)

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

Constructors in org.nd4j.linalg.api.ops.impl.scalar with parameters of type SameDiff

Constructor and Description
ScalarAdd(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarAdd(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarAdd(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
ScalarDivision(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarDivision(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarDivision(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarDivision(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
ScalarFMod(SameDiff sd, SDVariable in, Number number)
ScalarMax(SameDiff sd, SDVariable in, Number number)
ScalarMin(SameDiff sd, SDVariable in, Number number)
ScalarMultiplication(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarMultiplication(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarMultiplication(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarMultiplication(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
ScalarRemainder(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarRemainder(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarRemainder(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarRemainder(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
ScalarReverseDivision(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarReverseDivision(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarReverseDivision(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarReverseDivision(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
ScalarReverseSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarReverseSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarReverseSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarReverseSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
ScalarSet(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarSet(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarSet(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarSet(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
ScalarSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarSubtraction(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)

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

Constructors in org.nd4j.linalg.api.ops.impl.scalar.comparison with parameters of type SameDiff

Constructor and Description
ScalarEquals(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarEquals(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarEquals(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarEquals(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
ScalarGreaterThan(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarGreaterThan(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarGreaterThan(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarGreaterThan(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
ScalarGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
ScalarLessThan(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarLessThanOrEqual(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarLessThanOrEqual(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarNotEquals(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarNotEquals(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarNotEquals(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarNotEquals(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)
ScalarSetValue(SameDiff sameDiff, SDVariable i_v, Number scalar)
ScalarSetValue(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace)
ScalarSetValue(SameDiff sameDiff, SDVariable i_v, Number scalar, boolean inPlace, Object[] extraArgs)
ScalarSetValue(SameDiff sameDiff, SDVariable i_v, Number scalar, Object[] extraArgs)

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

Constructors in org.nd4j.linalg.api.ops.impl.scatter with parameters of type SameDiff

Constructor and Description
ScatterAdd(SameDiff sameDiff, SDVariable ref, SDVariable indices, SDVariable updates)
ScatterDiv(SameDiff sameDiff, SDVariable ref, SDVariable indices, SDVariable updates)
ScatterMax(SameDiff sameDiff, SDVariable ref, SDVariable indices, SDVariable updates)
ScatterMin(SameDiff sameDiff, SDVariable ref, SDVariable indices, SDVariable updates)
ScatterMul(SameDiff sameDiff, SDVariable ref, SDVariable indices, SDVariable updates)
ScatterSub(SameDiff sameDiff, SDVariable ref, SDVariable indices, SDVariable updates)
ScatterUpdate(SameDiff sameDiff, SDVariable ref, SDVariable indices, SDVariable updates)

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

Methods in org.nd4j.linalg.api.ops.impl.shape with parameters of type SameDiff

Modifier and Type	Method and Description
void	Transpose.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Diag.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	MergeSum.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Gather.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Unstack.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	ParallelStack.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Reshape.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	MergeAvg.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Concat.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	DiagPart.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Shape.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	MergeMax.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Rank.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Stack.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Repeat.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Transpose.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Split.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	StridedSlice.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Diag.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	MergeSum.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Gather.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	ConfusionMatrix.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	ExpandDims.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Slice.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Unstack.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Tile.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	ParallelStack.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	SequenceMask.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Reshape.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	MergeAvg.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Concat.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	SplitV.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	ZerosLike.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Squeeze.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	DiagPart.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Shape.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	MergeMax.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Rank.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Stack.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	OneHot.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	ApplyGradientDescent.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	OnesLike.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Repeat.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.shape with parameters of type SameDiff

Constructor and Description
Broadcast(SameDiff sameDiff, SDVariable iX, long[] shape)
BroadcastDynamicShape(SameDiff sameDiff, SDVariable in, SDVariable shape)
Concat(SameDiff sameDiff, int concatDimension, SDVariable... inputs)
ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred)
ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, Integer numClasses)
ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, Integer numClasses, SDVariable weights)
ConfusionMatrix(SameDiff sameDiff, SDVariable labels, SDVariable pred, SDVariable weights)
Cross(SameDiff sameDiff, SDVariable[] args)
Diag(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
DiagPart(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
ExpandDims(SameDiff sameDiff, SDVariable[] args)
ExpandDims(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
ExpandDims(SameDiff sameDiff, SDVariable[] args, int axis)
Eye(SameDiff sameDiff, int numRows)
Eye(SameDiff sameDiff, int numRows, int numCols)
Eye(SameDiff sameDiff, int numRows, int numCols, int[] batchDimension)
Eye(SameDiff sameDiff, SDVariable numRows)
Eye(SameDiff sameDiff, SDVariable numRows, SDVariable numCols)
Eye(SameDiff sameDiff, SDVariable numRows, SDVariable numCols, SDVariable batch_shape)
Gather(SameDiff sameDiff, SDVariable input, int[] indices, int axis, boolean inPlace)
Gather(SameDiff sameDiff, SDVariable input, SDVariable indices, int axis, boolean inPlace)
GatherNd(SameDiff sameDiff, SDVariable input, SDVariable indices, boolean inPlace)
MergeAvg(SameDiff sameDiff, SDVariable... inputs)
MergeMax(SameDiff sameDiff, SDVariable... inputs)
MergeSum(SameDiff sameDiff, SDVariable... inputs)
MeshGrid(SameDiff sd, boolean cartesian, SDVariable... inputs)
OneHot(SameDiff sameDiff, SDVariable indices, int depth)
OneHot(SameDiff sameDiff, SDVariable indices, int depth, int axis, double on, double off)
OnesLike(String name, SameDiff sameDiff, SDVariable input)
OnesLike(String name, SameDiff sameDiff, SDVariable input, boolean inPlace)
ParallelStack(SameDiff sameDiff, SDVariable[] values)
Permute(SameDiff sameDiff, SDVariable i_v, int... permuteDims)
Rank(SameDiff sameDiff, SDVariable input, boolean inPlace)
Repeat(SameDiff sameDiff, SDVariable[] args, boolean inPlace, int axis)
Repeat(SameDiff sameDiff, SDVariable[] args, int axis)
Reshape(SameDiff sameDiff, SDVariable i_v, long[] shape)
Reshape(SameDiff sameDiff, SDVariable i_v, SDVariable shape)
RollAxis(SameDiff sameDiff, int axis)
RollAxis(SameDiff sameDiff, SDVariable i_v, int axis)
RollAxis(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, int axis)
SequenceMask(SameDiff sameDiff, SDVariable input)
SequenceMask(SameDiff sameDiff, SDVariable input, int maxLen)
SequenceMask(SameDiff sameDiff, SDVariable input, SDVariable maxLen)
Shape(SameDiff sameDiff, SDVariable input, boolean inPlace)
Size(SameDiff sameDiff, SDVariable input)
SizeAt(SameDiff sameDiff, SDVariable input, int dimension)
Slice(SameDiff sameDiff, SDVariable input, int[] begin, int[] size)
Squeeze(SameDiff sameDiff, SDVariable arg, int[] squeezeDims)
Stack(SameDiff sameDiff, SDVariable[] values, int axis)
StridedSlice(SameDiff sameDiff, SDVariable in, int[] begin, int[] end, int[] strides)
StridedSlice(SameDiff sameDiff, SDVariable in, int[] begin, int[] end, int[] strides, int beginMask, int endMask, int ellipsisMask, int newAxisMask, int shrinkAxisMask)
StridedSlice(SameDiff sameDiff, SDVariable in, long[] begin, long[] end, long[] strides)
StridedSlice(SameDiff sameDiff, SDVariable in, long[] begin, long[] end, long[] strides, int beginMask, int endMask, int ellipsisMask, int newAxisMask, int shrinkAxisMask)
Tile(SameDiff sameDiff, SDVariable i_v, int[] axis)
Transpose(SameDiff sameDiff, SDVariable i_v)
Unstack(SameDiff sameDiff, SDVariable value, int axis)
Unstack(SameDiff sameDiff, SDVariable value, int axis, int num)
ZerosLike(String name, SameDiff sameDiff, SDVariable input)
ZerosLike(String name, SameDiff sameDiff, SDVariable input, boolean inPlace)

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

Methods in org.nd4j.linalg.api.ops.impl.shape.bp with parameters of type SameDiff

Modifier and Type	Method and Description
void	ConcatBp.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	ConcatBp.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.shape.bp with parameters of type SameDiff

Constructor and Description
ConcatBp(SameDiff sameDiff, int concatDimension, SDVariable... inputsAndGrad)
SliceBp(SameDiff sameDiff, SDVariable input, SDVariable gradient, int[] begin, int[] size)
StridedSliceBp(SameDiff sameDiff, SDVariable in, SDVariable grad, long[] begin, long[] end, long[] strides, int beginMask, int endMask, int ellipsisMask, int newAxisMask, int shrinkAxisMask)
TileBp(SameDiff sameDiff, SDVariable in, SDVariable grad, int[] repeat)

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

Methods in org.nd4j.linalg.api.ops.impl.shape.tensorops that return SameDiff

Modifier and Type	Method and Description
SameDiff	TensorArrayV3.getSameDiff()

Methods in org.nd4j.linalg.api.ops.impl.shape.tensorops with parameters of type SameDiff

Modifier and Type	Method and Description
TensorList	TensorSizeV3.execute(SameDiff sameDiff)
TensorList	TensorArrayConcatV3.execute(SameDiff sameDiff)
TensorList	TensorArrayReadV3.execute(SameDiff sameDiff)
TensorList	TensorArrayWriteV3.execute(SameDiff sameDiff)
TensorList	TensorArrayGatherV3.execute(SameDiff sameDiff)
TensorList	TensorArrayScatterV3.execute(SameDiff sameDiff)
TensorList	TensorArrayV3.execute(SameDiff sameDiff)
abstract TensorList	BaseTensorOp.execute(SameDiff sameDiff)
protected TensorList	BaseTensorOp.getList(SameDiff sameDiff)
void	TensorSizeV3.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	TensorArrayConcatV3.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	TensorArrayReadV3.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	TensorArrayGatherV3.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	TensorArrayScatterV3.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	TensorSizeV3.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	TensorArrayV3.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	BaseTensorOp.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.shape.tensorops with parameters of type SameDiff

Constructor and Description
BaseTensorOp(SameDiff sameDiff, SDVariable[] args)
BaseTensorOp(String name, SameDiff sameDiff, SDVariable[] args)
TensorArrayConcatV3(SameDiff sameDiff, SDVariable[] args)
TensorArrayConcatV3(String name, SameDiff sameDiff, SDVariable[] args)
TensorArrayGatherV3(SameDiff sameDiff, SDVariable[] args)
TensorArrayGatherV3(String name, SameDiff sameDiff, SDVariable[] args)
TensorArrayReadV3(SameDiff sameDiff, SDVariable[] args)
TensorArrayReadV3(String name, SameDiff sameDiff, SDVariable[] args)
TensorArrayScatterV3(SameDiff sameDiff, SDVariable[] args)
TensorArrayScatterV3(String name, SameDiff sameDiff, SDVariable[] args)
TensorArrayV3(SameDiff sameDiff)
TensorArrayV3(String name, SameDiff sameDiff)
TensorArrayWriteV3(SameDiff sameDiff, SDVariable[] args)
TensorArrayWriteV3(String name, SameDiff sameDiff, SDVariable[] args)

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

Methods in org.nd4j.linalg.api.ops.impl.transforms with parameters of type SameDiff

Modifier and Type	Method and Description
void	Histogram.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Fill.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Assign.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	RectifiedTanh.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	MirrorPad.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Pow.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	ReverseSequence.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Dilation2D.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	DynamicPartition.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	ParallelConcat.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Histogram.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Fill.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	Assign.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	DynamicStitch.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	RectifiedTanh.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.transforms with parameters of type SameDiff

Constructor and Description
Abs(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Abs(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
Abs(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
ACos(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
ACos(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
ACos(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
ACosh(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
ACosh(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
ACosh(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
And(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
And(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double comparable)
And(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
And(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, double comparable)
And(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
And(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double comparable)
And(SameDiff sameDiff, SDVariable ix, SDVariable iy)
ASin(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
ASin(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
ASin(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
ASinh(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
ASinh(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
ASinh(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Assign(SameDiff sameDiff, SDVariable x, SDVariable y)
ATan(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
ATan(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
ATan(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
ATan2(SameDiff sameDiff, SDVariable y, SDVariable x)
ATanh(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
ATanh(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
BaseDynamicTransformOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
BatchToSpace(SameDiff sameDiff, SDVariable[] args, int[] blocks, int[][] crops, boolean inPlace)
BinaryMinimalRelativeError(SameDiff sameDiff)
BinaryMinimalRelativeError(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
BinaryMinimalRelativeError(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
BinaryMinimalRelativeError(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
BinaryMinimalRelativeError(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
BinaryMinimalRelativeError(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
BinaryMinimalRelativeError(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
BinaryRelativeError(SameDiff sameDiff)
BinaryRelativeError(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
BinaryRelativeError(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
BinaryRelativeError(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
BinaryRelativeError(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
BinaryRelativeError(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
BinaryRelativeError(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
Ceil(SameDiff sameDiff, SDVariable i_v)
Ceil(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Ceil(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Constant(SameDiff sameDiff, SDVariable i_v, long[] shape)
Constant(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace)
Cos(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Cos(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Cos(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Cosh(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Cosh(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Cosh(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Cube(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Cube(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
Cube(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Dilation2D(SameDiff sameDiff, SDVariable[] inputAndWeights, int[] strides, int[] rates, boolean isSameMode, boolean inPlace)
DynamicPartition(SameDiff sameDiff, SDVariable input, SDVariable partitions, int numPartitions)
DynamicStitch(SameDiff sameDiff, SDVariable[] indices, SDVariable[] inputs)
ELU(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
ELU(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
ELU(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Erf(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Erf(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
Erf(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Erfc(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Erfc(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
Erfc(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Exp(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Expm1(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Expm1(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Expm1(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Fill(SameDiff sameDiff, SDVariable shape, double value)
Floor(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Floor(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
Floor(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
HardSigmoid(SameDiff sameDiff, SDVariable in, boolean inPlace)
HardTanh(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
HardTanh(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
HardTanh(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Histogram(SameDiff sameDiff)
Histogram(SameDiff sameDiff, SDVariable i_v, boolean inPlace, int numBins)
Histogram(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, int numBins)
Histogram(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, int numBins)
Identity(SameDiff sd, SDVariable input)
InvertPermutation(SameDiff sameDiff, SDVariable input, boolean inPlace)
IsFinite(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
IsFinite(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
IsFinite(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
IsInf(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
IsInf(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
IsInf(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
IsMax(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
IsMax(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
IsMax(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
IsNaN(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
IsNaN(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
IsNaN(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
LeakyReLU(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double alpha)
LeakyReLU(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, double alpha)
LeakyReLU(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double alpha)
LegacyDropOut(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double p)
LegacyDropOut(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs, double p)
LegacyDropOut(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double p)
LegacyDropOutInverted(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double p)
LegacyDropOutInverted(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs, double p)
LegacyDropOutInverted(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double p)
Log(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Log(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Log(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Log1p(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Log1p(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Log1p(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
LogSigmoid(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
LogSigmoid(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
LogSigmoid(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
LogSigmoidDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
LogSigmoidDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
LogSoftMax(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
LogSoftMax(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
LogSoftMax(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
LogX(SameDiff sameDiff, SDVariable i_v, double base)
MatchConditionTransform(SameDiff sameDiff, SDVariable in, Condition condition)
MatrixDeterminant(SameDiff sameDiff, SDVariable in, boolean inPlace)
MatrixDiag(SameDiff sameDiff, SDVariable in, boolean inPlace)
MatrixDiagPart(SameDiff sameDiff, SDVariable in, boolean inPlace)
MatrixInverse(SameDiff sameDiff, SDVariable in, boolean inPlace)
MatrixSetDiag(SameDiff sameDiff, SDVariable in, SDVariable diag, boolean inPlace)
MaxOut(SameDiff sameDiff, SDVariable i_v, boolean inPlace, Number max)
MaxOut(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs, Number max)
MaxOut(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, Number max)
Negative(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Negative(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
Negative(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Not(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double comparable)
Not(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, double comparable)
Not(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double comparable)
OldAtan2Op(SameDiff sameDiff)
OldAtan2Op(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OldAtan2Op(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
OldAtan2Op(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
OldAtan2Op(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldAtan2Op(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldAtan2Op(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
OldIdentity(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OldIdentity(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
OldIdentity(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
OldReverse(SameDiff sameDiff, SDVariable i_v, int... dimensions)
OldSoftMax(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OldSoftMax(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
OldSoftMax(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
OldSoftMax(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldSoftMax(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OneMinus(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OneMinus(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
OneMinus(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Or(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double comparable)
Or(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, double comparable)
Or(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double comparable)
Or(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
Or(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
Pow(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double pow)
Pow(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs, double pow)
Pow(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double pow)
PowDerivative(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double pow)
RationalTanh(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Reciprocal(SameDiff sameDiff, SDVariable in, boolean inPlace)
RectifedLinear(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double cutoff)
RectifedLinear(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, double cutoff)
RectifedLinear(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs, double cutoff)
RectifiedTanh(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
RelativeError(SameDiff sameDiff)
RelativeError(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
RelativeError(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
RelativeError(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
RelativeError(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
RelativeError(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
RelativeError(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
Relu6(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double cutoff)
Relu6(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, double cutoff)
Relu6(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs, double cutoff)
ReluLayer(SameDiff sameDiff, SDVariable input, SDVariable weights, SDVariable bias)
ReplaceNans(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double set)
ReplaceNans(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, double set)
ReplaceNans(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double set)
Reverse(SameDiff sameDiff, SDVariable i_v, int... dimensions)
ReverseSequence(SameDiff sameDiff, SDVariable i_v, SDVariable seqLengths)
ReverseSequence(SameDiff sameDiff, SDVariable i_v, SDVariable seqLengths, int seqDim, int batchDim)
Rint(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Rint(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
Rint(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Round(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Round(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Round(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
RSqrt(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
RSqrt(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
RSqrt(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
SELU(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
SELU(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
SELU(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Set(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Set(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Set(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
SetRange(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double min, double max)
SetRange(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, double min, double max)
SetRange(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double min, double max)
Sigmoid(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Sigmoid(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Sigmoid(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
SigmoidDerivative(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
SigmoidDerivative(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
SigmoidDerivative(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
SigmoidDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
SigmoidDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
Sign(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Sign(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Sign(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Sin(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Sin(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Sin(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Sinh(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Sinh(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Sinh(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
SoftMax(SameDiff sameDiff, SDVariable[] args)
SoftMax(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
SoftMaxDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
SoftMaxDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
SoftPlus(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
SoftPlus(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
SoftPlus(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
SoftSign(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
SoftSign(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
SoftSign(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
SpaceToBatch(SameDiff sameDiff, SDVariable[] args, int[] blocks, int[][] padding, boolean inPlace)
Sqrt(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Sqrt(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Sqrt(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Square(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Square(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Square(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Stabilize(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double realMin, double cutOff, double k)
Stabilize(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, double realMin, double cutOff, double k)
Stabilize(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double realMin, double cutOff, double k)
Step(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double cutoff)
Step(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs, double cutoff)
Step(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double cutoff)
Swish(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Swish(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Swish(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
SwishDerivative(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
SwishDerivative(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
SwishDerivative(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
SwishDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
SwishDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
Tan(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Tanh(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Tanh(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Tanh(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
TanhDerivative(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
TanhDerivative(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
TanhDerivative(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
TimesOneMinus(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
TimesOneMinus(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
TimesOneMinus(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Trace(SameDiff sd, SDVariable in)
Xor(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double comparable)
Xor(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs, double comparable)
Xor(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double comparable)
Xor(SameDiff sameDiff, SDVariable ix, SDVariable iy)
XwPlusB(SameDiff sameDiff, SDVariable input, SDVariable weights, SDVariable bias)

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

Constructors in org.nd4j.linalg.api.ops.impl.transforms.arithmetic with parameters of type SameDiff

Constructor and Description
AddOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
Axpy(SameDiff sameDiff, double p)
Axpy(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double p)
Axpy(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, double p)
Axpy(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double p)
Axpy(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, double p)
Axpy(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, double p)
Axpy(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs, double p)
CopyOp(SameDiff sameDiff)
CopyOp(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
CopyOp(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
CopyOp(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
CopyOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
CopyOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
CopyOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
DivOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
FloorDivOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
FloorDivOp(SameDiff sameDiff, SDVariable x, SDVariable y)
FloorModOp(SameDiff sameDiff, SDVariable x, SDVariable y)
FModOp(SameDiff sameDiff)
FModOp(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
FModOp(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
FModOp(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
FModOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
FModOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
FModOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
MergeAddOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
MulOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
OldAddOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldAddOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldFloorDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldFloorDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldFModOp(SameDiff sameDiff)
OldFModOp(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OldFModOp(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
OldFModOp(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
OldFModOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldFModOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldFModOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
OldMulOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldMulOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldRDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldRDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldSubOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldSubOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
RDivOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
RealDivOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
RemainderOp(SameDiff sameDiff)
RemainderOp(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
RemainderOp(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
RemainderOp(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
RemainderOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
RemainderOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
RemainderOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
RSubOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
RSubOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
RSubOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
SquaredDifferenceOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
SubOp(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
TruncateDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
TruncateDivOp(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)

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

Constructors in org.nd4j.linalg.api.ops.impl.transforms.arithmetic.bp with parameters of type SameDiff

Constructor and Description
AddBpOp(SameDiff sameDiff, SDVariable x, SDVariable y, SDVariable eps)
BaseArithmeticBackpropOp(SameDiff sameDiff, SDVariable x, SDVariable y, SDVariable eps)
DivBpOp(SameDiff sameDiff, SDVariable x, SDVariable y, SDVariable eps)
FloorDivBpOp(SameDiff sameDiff, SDVariable x, SDVariable y, SDVariable eps)
FloorModBpOp(SameDiff sameDiff, SDVariable x, SDVariable y, SDVariable eps)
MulBpOp(SameDiff sameDiff, SDVariable x, SDVariable y, SDVariable eps)
RDivBpOp(SameDiff sameDiff, SDVariable x, SDVariable y, SDVariable eps)
RSubBpOp(SameDiff sameDiff, SDVariable x, SDVariable y, SDVariable eps)
SquaredDifferenceBpOp(SameDiff sameDiff, SDVariable[] args)
SubBpOp(SameDiff sameDiff, SDVariable x, SDVariable y, SDVariable eps)

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

Methods in org.nd4j.linalg.api.ops.impl.transforms.clip with parameters of type SameDiff

Modifier and Type	Method and Description
void	ClipByValue.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	ClipByNorm.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	ClipByValue.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	ClipByNorm.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.transforms.clip with parameters of type SameDiff

Constructor and Description
ClipByNorm(SameDiff sameDiff, SDVariable x, double clipValue, int... dimensions)
ClipByNormBp(SameDiff sameDiff, SDVariable x, SDVariable eps, double clipValue, int... dimensions)
ClipByValue(SameDiff sameDiff, SDVariable x, double clipValueMin, double clipValueMax)
ClipByValue(SameDiff sameDiff, SDVariable x, double clipValueMin, double clipValueMax, boolean inPlace)

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

Constructors in org.nd4j.linalg.api.ops.impl.transforms.comparison with parameters of type SameDiff

Constructor and Description
Choose(SameDiff sameDiff, SDVariable[] args, Condition condition)
Choose(String opName, SameDiff sameDiff, SDVariable[] args, boolean inPlace)
CompareAndReplace(SameDiff sameDiff, SDVariable to, SDVariable from, Condition condition)
CompareAndSet(SameDiff sameDiff, SDVariable to, Number set, Condition condition)
Eps(SameDiff sameDiff)
Eps(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
Eps(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
Eps(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
Eps(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
Eps(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
Eps(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
EqualTo(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
GreaterThan(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
GreaterThanOrEqual(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
IsNonDecreasing(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
IsNumericTensor(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
IsStrictlyIncreasing(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
LessThan(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
LessThanOrEqual(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
Max(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
Max(SameDiff sameDiff, SDVariable first, SDVariable second)
Min(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
Min(SameDiff sameDiff, SDVariable first, SDVariable second)
NotEqualTo(SameDiff sameDiff, SDVariable[] args, boolean inPlace)
OldEqualTo(SameDiff sameDiff)
OldEqualTo(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OldEqualTo(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
OldEqualTo(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
OldEqualTo(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldEqualTo(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldEqualTo(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
OldGreaterThan(SameDiff sameDiff)
OldGreaterThan(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OldGreaterThan(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
OldGreaterThan(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
OldGreaterThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldGreaterThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldGreaterThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
OldGreaterThanOrEqual(SameDiff sameDiff)
OldGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OldGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
OldGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
OldGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldGreaterThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
OldLessThan(SameDiff sameDiff)
OldLessThan(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OldLessThan(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
OldLessThan(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
OldLessThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldLessThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldLessThan(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
OldLessThanOrEqual(SameDiff sameDiff)
OldLessThanOrEqual(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OldLessThanOrEqual(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
OldLessThanOrEqual(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
OldLessThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldLessThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldLessThanOrEqual(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
OldMax(SameDiff sameDiff)
OldMax(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OldMax(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
OldMax(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
OldMax(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldMax(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldMax(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
OldMin(SameDiff sameDiff)
OldMin(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
OldMin(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
OldMin(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
OldMin(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldMin(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
OldMin(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, Object[] extraArgs)
OldNotEqualTo(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
OldNotEqualTo(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)

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

Methods in org.nd4j.linalg.api.ops.impl.transforms.dtype with parameters of type SameDiff

Modifier and Type	Method and Description
void	Cast.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.transforms.dtype with parameters of type SameDiff

Constructor and Description
Cast(SameDiff sameDiff, SDVariable arg, DataBuffer.Type dst)

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

Constructors in org.nd4j.linalg.api.ops.impl.transforms.gradient with parameters of type SameDiff

Constructor and Description
CubeDerivative(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
CubeDerivative(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
CubeDerivative(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
ELUDerivative(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
ELUDerivative(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
ELUDerivative(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
GradientBackwardsMarker(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
GradientBackwardsMarker(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
HardSigmoidDerivative(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
HardSigmoidDerivative(SameDiff sameDiff, SDVariable i_v, long[] shape, boolean inPlace, Object[] extraArgs)
HardSigmoidDerivative(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
HardTanhDerivative(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
HardTanhDerivative(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
HardTanhDerivative(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
LeakyReLUDerivative(SameDiff sameDiff, SDVariable i_v, boolean inPlace, double alpha)
LeakyReLUDerivative(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs, double alpha)
LeakyReLUDerivative(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs, double alpha)
LeakyReLUDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace, double alpha)
LeakyReLUDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, double alpha)
LogSoftMaxDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
LogSoftMaxDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
RationalTanhDerivative(SameDiff sameDiff, SDVariable in, boolean inPlace)
RectifiedTanhDerivative(SameDiff sameDiff, SDVariable in, boolean inPlace)
Relu6Derivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, double cutoff)
SELUDerivative(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
SELUDerivative(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
SELUDerivative(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
SigmoidDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
SigmoidDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)
SoftmaxBp(SameDiff sd, SDVariable input, SDVariable grad, Integer dimension)
SoftSignDerivative(SameDiff sameDiff, SDVariable i_v, boolean inPlace)
SoftSignDerivative(SameDiff sameDiff, SDVariable i_v, int[] shape, boolean inPlace, Object[] extraArgs)
SoftSignDerivative(SameDiff sameDiff, SDVariable i_v, Object[] extraArgs)
TanhDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2)
TanhDerivative(SameDiff sameDiff, SDVariable i_v1, SDVariable i_v2, boolean inPlace)

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

Constructors in org.nd4j.linalg.api.ops.impl.transforms.segment with parameters of type SameDiff

Constructor and Description
SegmentMax(SameDiff sameDiff, SDVariable data, SDVariable segmentIds)
SegmentMean(SameDiff sameDiff, SDVariable data, SDVariable segmentIds)
SegmentMin(SameDiff sameDiff, SDVariable data, SDVariable segmentIds)
SegmentProd(SameDiff sameDiff, SDVariable data, SDVariable segmentIds)
SegmentSum(SameDiff sameDiff, SDVariable data, SDVariable segmentIds)

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

Methods in org.nd4j.linalg.api.ops.impl.transforms.temp with parameters of type SameDiff

Modifier and Type	Method and Description
void	ExternalErrorsFunction.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	ExternalErrorsFunction.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.impl.transforms.temp with parameters of type SameDiff

Constructor and Description
ExternalErrorsFunction(SameDiff sd, List<SDVariable> inputs, Map<String,INDArray> gradients)

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

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

Modifier and Type	Method and Description
void	RestoreV2.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	SaveV2.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

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

Constructors in org.nd4j.linalg.api.ops.random with parameters of type SameDiff

Constructor and Description
BaseRandomOp(SameDiff sd, long[] shape)
BaseRandomOp(SameDiff sameDiff, SDVariable i_v)

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

Constructors in org.nd4j.linalg.api.ops.random.compat with parameters of type SameDiff

Constructor and Description
RandomStandardNormal(SameDiff sameDiff, SDVariable[] args)

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

Methods in org.nd4j.linalg.api.ops.random.custom with parameters of type SameDiff

Modifier and Type	Method and Description
void	DistributionUniform.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.random.custom with parameters of type SameDiff

Constructor and Description
DistributionUniform(SameDiff sd, SDVariable shape, double min, double max)
RandomBernoulli(SameDiff sd, SDVariable shape, double p)
RandomExponential(SameDiff sd, SDVariable shape, double lambda)
RandomNormal(SameDiff sameDiff, SDVariable shape, double mean, double stdev)

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

Methods in org.nd4j.linalg.api.ops.random.impl with parameters of type SameDiff

Modifier and Type	Method and Description
void	Range.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	DropOutInverted.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	Range.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	DropOutInverted.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)

Constructors in org.nd4j.linalg.api.ops.random.impl with parameters of type SameDiff

Constructor and Description
BernoulliDistribution(SameDiff sd, double prob, long[] shape)
BinomialDistribution(SameDiff sd, int trials, double probability, long[] shape)
DropOut(SameDiff sameDiff, SDVariable input, double p)
DropOutInverted(SameDiff sameDiff, SDVariable input, double p)
GaussianDistribution(SameDiff sd, double mean, double stddev, long[] shape)
Linspace(SameDiff sd, double from, double to, long length)
LogNormalDistribution(SameDiff sd, double mean, double stdev, long... shape)
Range(SameDiff sd, double from, double to, double step)
TruncatedNormalDistribution(SameDiff sd, double mean, double stddev, long[] shape)
UniformDistribution(SameDiff sd, double from, double to, long[] shape)

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

Methods in org.nd4j.linalg.lossfunctions.impl with parameters of type SameDiff

Modifier and Type	Method and Description
void	LossMAPE.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossMSLE.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossMultiLabel.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossCosineProximity.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossHinge.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossSquaredHinge.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossFMeasure.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossMSE.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossMAE.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossKLD.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossBinaryXENT.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossMCXENT.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossMixtureDensity.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossL1.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossPoisson.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossL2.initFromOnnx(OnnxProto3.NodeProto node, SameDiff initWith, Map<String,OnnxProto3.AttributeProto> attributesForNode, OnnxProto3.GraphProto graph)
void	LossMAPE.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossMSLE.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossMultiLabel.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossCosineProximity.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossHinge.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossSquaredHinge.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossFMeasure.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossMSE.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossMAE.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossKLD.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossBinaryXENT.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossMCXENT.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossMixtureDensity.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossL1.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossPoisson.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
void	LossL2.initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)