Class Permute
- java.lang.Object
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- org.nd4j.autodiff.functions.DifferentialFunction
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- org.nd4j.linalg.api.ops.DynamicCustomOp
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- org.nd4j.linalg.api.ops.impl.shape.Transpose
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- org.nd4j.linalg.api.ops.impl.shape.Permute
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Nested Class Summary
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Nested classes/interfaces inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder
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Field Summary
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Fields inherited from class org.nd4j.linalg.api.ops.impl.shape.Transpose
permuteDims
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Fields inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, sArguments, tArguments
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Fields inherited from class org.nd4j.autodiff.functions.DifferentialFunction
dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue
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Constructor Summary
Constructors Constructor Description Permute()
Permute(SameDiff sameDiff, SDVariable i_v, int... permuteDims)
Permute(SameDiff sd, SDVariable input, SDVariable permuteDims)
Permute(INDArray input, int... permuteDims)
Permute(INDArray input, INDArray result, int... permuteDims)
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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.void
configureFromArguments()
This allows a custom op to configure relevant fields from its arguments.List<SDVariable>
doDiff(List<SDVariable> i_v)
The actual implementation for automatic differentiation.String
onnxName()
The opName of this function in onnxString
opName()
This method returns op opName as stringvoid
setPropertiesForFunction(Map<String,Object> properties)
String
tensorflowName()
The opName of this function tensorflow-
Methods inherited from class org.nd4j.linalg.api.ops.impl.shape.Transpose
initFromOnnx, initFromTensorFlow, mappingsForFunction
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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, dArgs, generateFake, generateFake, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getSArgument, getTArgument, getValue, iArgs, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numSArguments, numTArguments, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, propertiesForFunction, removeIArgument, removeInputArgument, removeOutputArgument, removeSArgument, removeTArgument, sArgs, setInputArgument, setInputArguments, setOutputArgument, setValueFor, tArgs, toString, wrapFilterNull, wrapOrNull, wrapOrNull
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Methods inherited from class org.nd4j.autodiff.functions.DifferentialFunction
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, configureWithSameDiff, diff, dup, equals, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getNumOutputs, getStringFromProperty, hashCode, isConfigProperties, larg, onnxNames, outputs, outputVariable, outputVariablesNames, rarg, replaceArg, setInstanceId, tensorflowNames
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Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
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Methods inherited from interface org.nd4j.linalg.api.ops.CustomOp
isInplaceCall
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Constructor Detail
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Permute
public Permute(SameDiff sameDiff, SDVariable i_v, int... permuteDims)
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Permute
public Permute(SameDiff sd, SDVariable input, SDVariable permuteDims)
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Permute
public Permute(INDArray input, int... permuteDims)
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Permute
public Permute()
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Method Detail
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opName
public String opName()
Description copied from class:DynamicCustomOp
This method returns op opName as string
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doDiff
public List<SDVariable> doDiff(List<SDVariable> i_v)
Description copied from class:DifferentialFunction
The actual implementation for automatic differentiation.
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configureFromArguments
public void configureFromArguments()
Description copied from interface:CustomOp
This allows a custom op to configure relevant fields from its arguments. This is needed when ops are created via reflection for things like model import.- Specified by:
configureFromArguments
in interfaceCustomOp
- Overrides:
configureFromArguments
in classDynamicCustomOp
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setPropertiesForFunction
public void setPropertiesForFunction(Map<String,Object> properties)
- Overrides:
setPropertiesForFunction
in classDynamicCustomOp
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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 classTranspose
- Parameters:
dataTypes
- The data types of the inputs- Returns:
- The data types of the outputs
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tensorflowName
public String tensorflowName()
Description copied from class:DifferentialFunction
The opName of this function tensorflow- Overrides:
tensorflowName
in classTranspose
- Returns:
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onnxName
public String onnxName()
Description copied from class:DifferentialFunction
The opName of this function in onnx
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