public class Conv1D 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, ownName, ownNameSetWithDefault, sameDiff, scalarValue
Constructor and Description |
---|
Conv1D(INDArray[] inputs,
INDArray[] outputs,
Conv1DConfig config) |
Conv1D(INDArray input,
INDArray weights,
INDArray bias,
Conv1DConfig config) |
Conv1D(@NonNull INDArray input,
@NonNull INDArray weights,
INDArray bias,
INDArray output,
@NonNull Conv1DConfig config) |
Conv1D(SameDiff sameDiff,
SDVariable[] inputFunctions,
Conv1DConfig config) |
Conv1D(@NonNull SameDiff sameDiff,
@NonNull SDVariable input,
@NonNull SDVariable weights,
SDVariable bias,
@NonNull Conv1DConfig conv1DConfig) |
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.
|
List<SDVariable> |
doDiff(List<SDVariable> grads)
The actual implementation for automatic differentiation.
|
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, 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, getNumOutputs, 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 Conv1D(@NonNull @NonNull SameDiff sameDiff, @NonNull @NonNull SDVariable input, @NonNull @NonNull SDVariable weights, SDVariable bias, @NonNull @NonNull Conv1DConfig conv1DConfig)
public Conv1D(SameDiff sameDiff, SDVariable[] inputFunctions, Conv1DConfig config)
public Conv1D(INDArray[] inputs, INDArray[] outputs, Conv1DConfig config)
public Conv1D(@NonNull @NonNull INDArray input, @NonNull @NonNull INDArray weights, INDArray bias, INDArray output, @NonNull @NonNull Conv1DConfig config)
public Conv1D(INDArray input, INDArray weights, INDArray bias, 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 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 inputspublic List<SDVariable> doDiff(List<SDVariable> grads)
DifferentialFunction
doDiff
in class DynamicCustomOp
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