Class Min
- java.lang.Object
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- org.nd4j.autodiff.functions.DifferentialFunction
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- org.nd4j.linalg.api.ops.BaseOp
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- org.nd4j.linalg.api.ops.BaseReduceOp
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- org.nd4j.linalg.api.ops.BaseReduceSameOp
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- org.nd4j.linalg.api.ops.impl.reduce.same.Min
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- All Implemented Interfaces:
Op
,ReduceOp
,ReduceSameOp
public class Min extends BaseReduceSameOp
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Field Summary
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Fields inherited from class org.nd4j.linalg.api.ops.BaseReduceOp
dimensionVariable, isComplex, isEmptyReduce, keepDims
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Fields inherited from class org.nd4j.linalg.api.ops.BaseOp
dimensionz, extraArgz, x, xVertexId, y, yVertexId, z, zVertexId
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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 Min()
Min(SameDiff sameDiff)
Min(SameDiff sameDiff, SDVariable i_v)
Min(SameDiff sameDiff, SDVariable i_v, boolean keepDims)
Min(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
Min(SameDiff sameDiff, SDVariable input, int... dimensions)
Min(SameDiff sameDiff, SDVariable input, int[] dimensions, boolean keepDims)
Min(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2)
Min(SameDiff sameDiff, SDVariable i_v, SDVariable dimensions, boolean keepDims)
Min(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
Min(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, boolean keepDims)
Min(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, SDVariable dimensions)
Min(INDArray x, boolean keepDims, int... dimensions)
Min(INDArray x, int... dimensions)
Min(INDArray in, int[] dimensions, boolean keepDims)
Min(INDArray x, INDArray z, boolean keepDims, int... dimensions)
Min(INDArray x, INDArray z, int... dimensions)
Min(INDArray x, INDArray y, INDArray z, boolean keepDims, int[] dimensions)
Min(INDArray x, INDArray y, INDArray z, int... dimensions)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description List<SDVariable>
doDiff(List<SDVariable> grad)
The actual implementation for automatic differentiation.String
onnxName()
The opName of this function in onnxString
opName()
The name of the opint
opNum()
The number of the op (mainly for old legacy XYZ ops likeOp
)String
tensorflowName()
The opName of this function tensorflow-
Methods inherited from class org.nd4j.linalg.api.ops.BaseReduceSameOp
calculateOutputDataTypes, calculateOutputShape, calculateOutputShape, dimensions, getOpType, opType, resultType, resultType, validateDataTypes
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Methods inherited from class org.nd4j.linalg.api.ops.BaseReduceOp
configureWithSameDiff, hasReductionIndices, initFromOnnx, initFromTensorFlow, isComplexAccumulation, isKeepDims, noOp, setDimensions, setPropertiesForFunction
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Methods inherited from class org.nd4j.linalg.api.ops.BaseOp
clearArrays, computeVariables, defineDimensions, equals, extraArgs, extraArgsBuff, extraArgsDataBuff, getFinalResult, getInputArgument, getNumOutputs, getOpType, hashCode, outputVariables, setX, setY, setZ, toCustomOp, toString, x, y, z
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Methods inherited from class org.nd4j.autodiff.functions.DifferentialFunction
arg, arg, argNames, args, attributeAdaptersForFunction, configFieldName, diff, dup, getBooleanFromProperty, getDoubleValueFromProperty, getIntValueFromProperty, getLongValueFromProperty, getStringFromProperty, getValue, isConfigProperties, larg, mappingsForFunction, onnxNames, outputs, outputVariable, outputVariables, outputVariablesNames, propertiesForFunction, rarg, replaceArg, setInstanceId, setValueFor, 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.Op
clearArrays, extraArgs, extraArgsBuff, extraArgsDataBuff, setExtraArgs, setX, setY, setZ, toCustomOp, x, y, z
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Methods inherited from interface org.nd4j.linalg.api.ops.ReduceOp
getFinalResult, isComplexAccumulation, isKeepDims, noOp, setDimensions
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Constructor Detail
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Min
public Min(SameDiff sameDiff, SDVariable i_v, boolean keepDims, int[] dimensions)
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Min
public Min()
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Min
public Min(INDArray x, int... dimensions)
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Min
public Min(INDArray x, boolean keepDims, int... dimensions)
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Min
public Min(SameDiff sameDiff)
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Min
public Min(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, SDVariable dimensions)
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Min
public Min(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions)
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Min
public Min(SameDiff sameDiff, SDVariable i_v, boolean keepDims)
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Min
public Min(SameDiff sameDiff, SDVariable i_v, SDVariable dimensions, boolean keepDims)
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Min
public Min(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2)
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Min
public Min(SameDiff sameDiff, SDVariable input, int[] dimensions, boolean keepDims)
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Min
public Min(SameDiff sameDiff, SDVariable i_v, SDVariable i_v2, int[] dimensions, boolean keepDims)
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Min
public Min(SameDiff sameDiff, SDVariable i_v)
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Min
public Min(SameDiff sameDiff, SDVariable input, int... dimensions)
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Min
public Min(INDArray in, int[] dimensions, boolean keepDims)
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Method Detail
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opNum
public int opNum()
Description copied from class:DifferentialFunction
The number of the op (mainly for old legacy XYZ ops likeOp
)- Specified by:
opNum
in interfaceOp
- Overrides:
opNum
in classDifferentialFunction
- Returns:
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opName
public String opName()
Description copied from class:DifferentialFunction
The name of the op- Specified by:
opName
in interfaceOp
- Overrides:
opName
in classDifferentialFunction
- Returns:
- the opName of this operation
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onnxName
public String onnxName()
Description copied from class:DifferentialFunction
The opName of this function in onnx
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tensorflowName
public String tensorflowName()
Description copied from class:DifferentialFunction
The opName of this function tensorflow- Overrides:
tensorflowName
in classBaseOp
- Returns:
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doDiff
public List<SDVariable> doDiff(List<SDVariable> grad)
Description copied from class:DifferentialFunction
The actual implementation for automatic differentiation.- Specified by:
doDiff
in classDifferentialFunction
- Returns:
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