public class Conv1DDerivative extends DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder
Modifier and Type | Field and Description |
---|---|
protected Conv1DConfig |
config |
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArguments
dimensions, extraArgs, inPlace, sameDiff, scalarValue
Constructor and Description |
---|
Conv1DDerivative(INDArray[] inputs,
INDArray[] outputs,
Conv1DConfig config) |
Conv1DDerivative(@NonNull INDArray input,
@NonNull INDArray weights,
INDArray bias,
@NonNull INDArray gradOut,
INDArray output,
@NonNull Conv1DConfig config) |
Conv1DDerivative(@NonNull SameDiff sameDiff,
@NonNull SDVariable[] inputs,
@NonNull Conv1DConfig config) |
Conv1DDerivative(@NonNull SameDiff sd,
@NonNull SDVariable input,
@NonNull SDVariable weights,
SDVariable bias,
SDVariable gradOut,
@NonNull Conv1DConfig config) |
Modifier and Type | Method and Description |
---|---|
protected void |
addArgs() |
List<DataType> |
calculateOutputDataTypes(List<DataType> inputDataTypes)
Calculate the data types for the output arrays.
|
String |
configFieldName()
Returns the name of the field to be used for looking up field names.
|
int |
getNumOutputs() |
Object |
getValue(Field property)
Get the value for a given property
for this function
|
long[] |
iArgs() |
boolean |
isConfigProperties()
Returns true if the fields for this class should be looked up from a configuration class.
|
String |
opName()
This method returns op opName as string
|
Map<String,Object> |
propertiesForFunction()
Returns the properties for a given function
|
addBArgument, addDArgument, addIArgument, addIArgument, addInputArgument, addOutputArgument, addTArgument, assertValidForExecution, bArgs, builder, calculateOutputShape, calculateOutputShape, clearArrays, dArgs, doDiff, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getTArgument, initFromOnnx, initFromTensorFlow, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, onnxName, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, tensorflowName, toString, wrapFilterNull, wrapOrNull, wrapOrNull
arg, arg, argNames, args, attributeAdaptersForFunction, diff, dup, equals, hashCode, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariablesNames, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNames
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
isInplaceCall
protected Conv1DConfig config
public Conv1DDerivative(@NonNull @NonNull SameDiff sameDiff, @NonNull @NonNull SDVariable[] inputs, @NonNull @NonNull Conv1DConfig config)
public Conv1DDerivative(@NonNull @NonNull SameDiff sd, @NonNull @NonNull SDVariable input, @NonNull @NonNull SDVariable weights, SDVariable bias, SDVariable gradOut, @NonNull @NonNull Conv1DConfig config)
public Conv1DDerivative(INDArray[] inputs, INDArray[] outputs, Conv1DConfig config)
protected void addArgs()
public long[] iArgs()
iArgs
in interface CustomOp
iArgs
in class DynamicCustomOp
public Object getValue(Field property)
DifferentialFunction
getValue
in class DifferentialFunction
property
- the property to getpublic Map<String,Object> propertiesForFunction()
DifferentialFunction
propertiesForFunction
in class DifferentialFunction
public boolean isConfigProperties()
DifferentialFunction
isConfigProperties
in class DifferentialFunction
public String configFieldName()
DifferentialFunction
DifferentialFunction.isConfigProperties()
to facilitate mapping fields for model import.configFieldName
in class DifferentialFunction
public String opName()
DynamicCustomOp
opName
in interface CustomOp
opName
in class DynamicCustomOp
public int getNumOutputs()
getNumOutputs
in class DifferentialFunction
public List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes)
DifferentialFunction
DifferentialFunction.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.calculateOutputDataTypes
in class DifferentialFunction
inputDataTypes
- The data types of the inputsCopyright © 2020. All rights reserved.