public class DeConv2D extends DynamicCustomOp
DynamicCustomOp.DynamicCustomOpsBuilder| Modifier and Type | Field and Description |
|---|---|
protected DeConv2DConfig |
config |
axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, tArgumentsdimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue| Constructor and Description |
|---|
DeConv2D(INDArray[] inputs,
INDArray[] outputs,
DeConv2DConfig config) |
DeConv2D(INDArray layerInput,
INDArray weights,
INDArray bias,
DeConv2DConfig config) |
DeConv2D(@NonNull INDArray input,
@NonNull INDArray weights,
INDArray bias,
INDArray output,
@NonNull DeConv2DConfig config) |
DeConv2D(SameDiff sameDiff,
SDVariable[] inputs,
DeConv2DConfig config) |
DeConv2D(@NonNull SameDiff sameDiff,
@NonNull SDVariable input,
@NonNull SDVariable weights,
SDVariable bias,
DeConv2DConfig config) |
| Modifier and Type | Method and Description |
|---|---|
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> f1)
The actual implementation for automatic differentiation.
|
Object |
getValue(Field property)
Get the value for a given property
for this function
|
long[] |
iArgs() |
void |
initFromOnnx(Onnx.NodeProto node,
SameDiff initWith,
Map<String,Onnx.AttributeProto> attributesForNode,
Onnx.GraphProto graph)
Iniitialize the function from the given
Onnx.NodeProto |
void |
initFromTensorFlow(NodeDef nodeDef,
SameDiff initWith,
Map<String,AttrValue> attributesForNode,
GraphDef graph)
Initialize the function from the given
NodeDef |
boolean |
isConfigProperties()
Returns true if the fields for this class should be looked up from a configuration class.
|
Map<String,Map<String,PropertyMapping>> |
mappingsForFunction()
Returns the mappings for a given function (
for tensorflow and onnx import mapping properties
of this function).
|
String |
onnxName()
The opName of this function in onnx
|
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, inputArguments, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numTArguments, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, removeIArgument, removeInputArgument, removeOutputArgument, removeTArgument, setInputArgument, setInputArguments, setOutputArgument, tArgs, tensorflowName, toString, wrapFilterNull, wrapOrNull, wrapOrNullarg, arg, argNames, args, attributeAdaptersForFunction, diff, dup, equals, getNumOutputs, hashCode, larg, onnxNames, outputs, outputVariable, outputVariablesNames, rarg, replaceArg, setInstanceId, setPropertiesForFunction, setValueFor, tensorflowNamesclone, finalize, getClass, notify, notifyAll, wait, wait, waitisInplaceCallprotected DeConv2DConfig config
public DeConv2D(@NonNull
@NonNull SameDiff sameDiff,
@NonNull
@NonNull SDVariable input,
@NonNull
@NonNull SDVariable weights,
SDVariable bias,
DeConv2DConfig config)
public DeConv2D(SameDiff sameDiff, SDVariable[] inputs, DeConv2DConfig config)
public DeConv2D(INDArray[] inputs, INDArray[] outputs, DeConv2DConfig config)
public DeConv2D(@NonNull
@NonNull INDArray input,
@NonNull
@NonNull INDArray weights,
INDArray bias,
INDArray output,
@NonNull
@NonNull DeConv2DConfig config)
public DeConv2D(INDArray layerInput, INDArray weights, INDArray bias, DeConv2DConfig config)
public long[] iArgs()
iArgs in interface CustomOpiArgs in class DynamicCustomOppublic Map<String,Object> propertiesForFunction()
DifferentialFunctionpropertiesForFunction in class DifferentialFunctionpublic boolean isConfigProperties()
DifferentialFunctionisConfigProperties in class DifferentialFunctionpublic String configFieldName()
DifferentialFunctionDifferentialFunction.isConfigProperties()
to facilitate mapping fields for model import.configFieldName in class DifferentialFunctionpublic Object getValue(Field property)
DifferentialFunctiongetValue in class DifferentialFunctionproperty - the property to getpublic Map<String,Map<String,PropertyMapping>> mappingsForFunction()
DifferentialFunctionmappingsForFunction in class DifferentialFunctionpublic void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
DifferentialFunctionNodeDefinitFromTensorFlow in class DynamicCustomOppublic void initFromOnnx(Onnx.NodeProto node, SameDiff initWith, Map<String,Onnx.AttributeProto> attributesForNode, Onnx.GraphProto graph)
DifferentialFunctionOnnx.NodeProtoinitFromOnnx in class DynamicCustomOppublic String opName()
DynamicCustomOpopName in interface CustomOpopName in class DynamicCustomOppublic String onnxName()
DifferentialFunctiononnxName in class DynamicCustomOppublic List<SDVariable> doDiff(List<SDVariable> f1)
DifferentialFunctiondoDiff in class DynamicCustomOppublic List<DataType> calculateOutputDataTypes(List<DataType> inputDataTypes)
DifferentialFunctionDifferentialFunction.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 DifferentialFunctioninputDataTypes - The data types of the inputsCopyright © 2021. All rights reserved.