MinMaxDataType (nd4j-api 1.0.0-M2.1 API)

java.lang.Object
- org.nd4j.autodiff.functions.DifferentialFunction
- - org.nd4j.linalg.api.ops.DynamicCustomOp
  - - org.nd4j.linalg.api.ops.impl.transforms.dtype.MinMaxDataType

All Implemented Interfaces:

CustomOp
```
public class MinMaxDataType
extends DynamicCustomOp
```
Returns the min or max (0 or 1 in int arguments) for a given data type. The first data type is passed in as an int represented in DataType.fromInt(int) The second value (as described above) is min or max representing the value. This value is returned as a scalar.

Nested Class Summary
- Nested classes/interfaces inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp
  DynamicCustomOp.DynamicCustomOpsBuilder

Field Summary
- Fields inherited from class org.nd4j.linalg.api.ops.DynamicCustomOp
  axis, bArguments, dArguments, iArguments, inplaceCall, inputArguments, outputArguments, outputVariables, sArguments, tArguments
- Fields inherited from class org.nd4j.autodiff.functions.DifferentialFunction
  dimensions, extraArgs, inPlace, ownName, ownNameSetWithDefault, sameDiff, scalarValue

Constructor Summary

Constructors
Constructor	Description
`MinMaxDataType()`
`MinMaxDataType(int datatype, int minOrMax)`
`MinMaxDataType(SameDiff sd, int datatype, int minOrMax)`

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.
`String`	`opName()`	This method returns op opName as string

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, doDiff, generateFake, generateFake, getBArgument, getDescriptor, getIArgument, getInputArgument, getOutputArgument, getSArgument, getTArgument, getValue, iArgs, initFromOnnx, initFromTensorFlow, inputArguments, mappingsForFunction, numBArguments, numDArguments, numIArguments, numInputArguments, numOutputArguments, numSArguments, numTArguments, onnxName, opHash, opNum, opType, outputArguments, outputVariables, outputVariables, propertiesForFunction, removeIArgument, removeInputArgument, removeOutputArgument, removeSArgument, removeTArgument, sArgs, setInputArgument, setInputArguments, setOutputArgument, setPropertiesForFunction, setValueFor, tArgs, tensorflowName, toString, wrapFilterNull, wrapOrNull, wrapOrNull

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, tensorflowNames

Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface org.nd4j.linalg.api.ops.CustomOp
isInplaceCall

- Constructor Detail
  - MinMaxDataType
```
public MinMaxDataType()
```
  - MinMaxDataType
```
public MinMaxDataType(SameDiff sd,
                      int datatype,
                      int minOrMax)
```
  - MinMaxDataType
```
public MinMaxDataType(int datatype,
                      int minOrMax)
```
- Method Detail
  - opName
```
public String opName()
```
    Description copied from class: DynamicCustomOp
    
    This method returns op opName as string
    
    Specified by:
    
    opName in interface CustomOp
    
    Overrides:
    
    opName in class DynamicCustomOp
    
    Returns:
  - 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 from 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.
    
    Overrides:
    
    calculateOutputDataTypes in class DifferentialFunction
    
    Parameters:
    
    dataTypes - The data types of the inputs
    
    Returns:
    
    The data types of the outputs