Class Svd
- java.lang.Object
-
- org.nd4j.autodiff.functions.DifferentialFunction
-
- org.nd4j.linalg.api.ops.DynamicCustomOp
-
- org.nd4j.linalg.api.ops.impl.transforms.custom.Svd
-
- All Implemented Interfaces:
CustomOp
public class Svd extends DynamicCustomOp
-
-
Nested Class Summary
-
Nested classes/interfaces inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder
-
-
Field Summary
Fields Modifier and Type Field Description static int
DEFAULT_SWITCHNUM
-
Fields inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, sArguments, tArguments
-
Fields inherited from class org.nd4j.autodiff.functions.DifferentialFunction
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
-
-
Constructor Summary
Constructors Constructor Description Svd()
Svd(SameDiff sd, SDVariable input, boolean fullUV, boolean computeUv)
Svd(SameDiff sd, SDVariable input, boolean fullUV, boolean computeUv, int switchNum)
Svd(INDArray input, boolean fullUV, boolean computeUV, int switchNum)
Svd(INDArray input, boolean full_matrices, INDArray s, INDArray u, INDArray v)
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description List<DataType>
calculateOutputDataTypes(List<DataType> dataTypes)
Calculate the data types for the output arrays.List<SDVariable>
doDiff(List<SDVariable> i_v)
The actual implementation for automatic differentiation.int
getNumOutputs()
void
initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
Initialize the function from the givenNodeDef
String
opName()
This method returns op opName as stringString
tensorflowName()
The opName of this function tensorflow-
Methods inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp
addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addOutputsToOp, addSArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, calculateOutputShape, clearArrays, computeArrays, configureFromArguments, dArgs, generateFake, generateFake, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getSArgument, getTArgument, getValue, iArgs, initFromOnnx, inputArguments, mappingsForFunction, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numSArguments, numTArguments, onnxName, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, propertiesForFunction, removeIArgument, removeInputArgument, removeOutputArgument, removeSArgument, removeTArgument, sArgs, setInputArgument, setInputArguments, setOutputArgument, setPropertiesForFunction, setValueFor, tArgs, toString, wrapFilterNull, wrapOrNull, wrapOrNull
-
Methods inherited from class org.nd4j.autodiff.functions.DifferentialFunction
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, configureWithSameDiff, diff, dup, equals, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getStringFromProperty, hashCode, isConfigProperties, larg, onnxNames, outputs, outputVariable, outputVariablesNames, rarg, replaceArg, setInstanceId, tensorflowNames
-
Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
-
Methods inherited from interface org.nd4j.linalg.api.ops.CustomOp
isInplaceCall
-
-
-
-
Field Detail
-
DEFAULT_SWITCHNUM
public static final int DEFAULT_SWITCHNUM
- See Also:
- Constant Field Values
-
-
Constructor Detail
-
Svd
public Svd()
-
Svd
public Svd(SameDiff sd, SDVariable input, boolean fullUV, boolean computeUv)
-
Svd
public Svd(SameDiff sd, SDVariable input, boolean fullUV, boolean computeUv, int switchNum)
-
Svd
public Svd(INDArray input, boolean fullUV, boolean computeUV, int switchNum)
-
-
Method Detail
-
opName
public String opName()
Description copied from class:DynamicCustomOp
This method returns op opName as string- Specified by:
opName
in interfaceCustomOp
- Overrides:
opName
in classDynamicCustomOp
- Returns:
-
tensorflowName
public String tensorflowName()
Description copied from class:DifferentialFunction
The opName of this function tensorflow- Overrides:
tensorflowName
in classDynamicCustomOp
- Returns:
-
initFromTensorFlow
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
Description copied from class:DifferentialFunction
Initialize the function from the givenNodeDef
- Overrides:
initFromTensorFlow
in classDynamicCustomOp
-
doDiff
public List<SDVariable> doDiff(List<SDVariable> i_v)
Description copied from class:DifferentialFunction
The actual implementation for automatic differentiation.- Overrides:
doDiff
in classDynamicCustomOp
- Returns:
-
getNumOutputs
public int getNumOutputs()
- Overrides:
getNumOutputs
in classDifferentialFunction
-
calculateOutputDataTypes
public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes)
Description copied from class:DifferentialFunction
Calculate the data types for the output arrays. Though datatypes can also be inferred fromDifferentialFunction.calculateOutputShape()
, this method differs in that it does not require the input arrays to be populated. This is important as it allows us to do greedy datatype inference for the entire net - even if arrays are not available.- Overrides:
calculateOutputDataTypes
in classDifferentialFunction
- Parameters:
dataTypes
- The data types of the inputs- Returns:
- The data types of the outputs
-
-