Class DepthToSpace
- 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.layers.convolution.DepthToSpace
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- All Implemented Interfaces:
CustomOp
public class DepthToSpace extends DynamicCustomOp
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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.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 DepthToSpace()
DepthToSpace(SameDiff sameDiff, SDVariable[] args, int blockSize, DataFormat dataFormat)
DepthToSpace(SameDiff sameDiff, SDVariable args, int blockSize, DataFormat dataFormat)
DepthToSpace(INDArray in, int blockSize, DataFormat dataFormat)
DepthToSpace(INDArray in, INDArray out, int blockSize, DataFormat dataFormat)
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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.List<SDVariable>
doDiff(List<SDVariable> i_v)
The actual implementation for automatic differentiation.void
initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map<String,AttrValue> attributesForNode, GraphDef graph)
Initialize the function from the givenNodeDef
Map<String,Map<String,PropertyMapping>>
mappingsForFunction()
Returns the mappings for a given function ( for tensorflow and onnx import mapping properties of this function).String
opName()
This method returns op opName as stringvoid
setPropertiesForFunction(Map<String,Object> properties)
String
tensorflowName()
The opName of this function tensorflowString[]
tensorflowNames()
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, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numSArguments, numTArguments, onnxName, 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
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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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DepthToSpace
public DepthToSpace()
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DepthToSpace
public DepthToSpace(SameDiff sameDiff, SDVariable args, int blockSize, DataFormat dataFormat)
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DepthToSpace
public DepthToSpace(SameDiff sameDiff, SDVariable[] args, int blockSize, DataFormat dataFormat)
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DepthToSpace
public DepthToSpace(INDArray in, INDArray out, int blockSize, DataFormat dataFormat)
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DepthToSpace
public DepthToSpace(INDArray in, int blockSize, DataFormat dataFormat)
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Method Detail
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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:
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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
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mappingsForFunction
public Map<String,Map<String,PropertyMapping>> mappingsForFunction()
Description copied from class:DifferentialFunction
Returns the mappings for a given function ( for tensorflow and onnx import mapping properties of this function). The mapping is indexed by field name. If the function has no properties, this returned map will be empty. Note that some functions have multiple names. This function returns a map indexed by each alias it has for a given name. These names include both onnx and tensorflow names (which might be 1 or more)- Overrides:
mappingsForFunction
in classDynamicCustomOp
- Returns:
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setPropertiesForFunction
public void setPropertiesForFunction(Map<String,Object> properties)
- Overrides:
setPropertiesForFunction
in classDynamicCustomOp
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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:
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tensorflowNames
public String[] tensorflowNames()
Description copied from class:DifferentialFunction
The opName of this function tensorflow- Overrides:
tensorflowNames
in classDifferentialFunction
- Returns:
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tensorflowName
public String tensorflowName()
Description copied from class:DifferentialFunction
The opName of this function tensorflow- Overrides:
tensorflowName
in classDynamicCustomOp
- Returns:
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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 classDifferentialFunction
- Parameters:
dataTypes
- The data types of the inputs- Returns:
- The data types of the outputs
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