Available Methods
- putScalar ( )
- length ( )
- dup ( )
- get ( )
- size ( )
- shape ( )
- assign ( )
- rows ( )
- getDouble ( )
- reshape ( )
- addi ( )
- muli ( )
- rank ( )
- mmul ( )
- columns ( )
- put ( )
- lengthLong ( )
- ordering ( )
- sum ( )
- mul ( )
- putRow ( )
- getRow ( )
- divi ( )
- castTo ( )
- permute ( )
- mean ( )
- add ( )
- slice ( )
- sub ( )
- tensorAlongDimension ( )
- muliColumnVector ( )
- dataType ( )
- addiRowVector ( )
- transpose ( )
- isVector ( )
- subi ( )
- getInt ( )
- isView ( )
- isScalar ( )
- subiRowVector ( )
- std ( )
- getFloat ( )
- diviColumnVector ( )
- stride ( )
- slices ( )
- max ( )
- muliRowVector ( )
- data ( )
- getColumn ( )
- equalShapes ( )
- div ( )
- rsubi ( )
- equals ( )
- rsub ( )
- isEmpty ( )
- var ( )
- elementWiseStride ( )
- markAsCompressed ( )
- norm2 ( )
- mmuli ( )
- getColumns ( )
- linearView ( )
- diviRowVector ( )
- isRowVector ( )
- isSparse ( )
- like ( )
- ulike ( )
- offset ( )
- unsafeDuplication ( )
- putSlice ( )
- isRowVectorOrScalar ( )
- equalsWithEps ( )
- rdivi ( )
- addiColumnVector ( )
- setData ( )
- gt ( )
- rdiv ( )
- tensorsAlongDimension ( )
- toString ( )
- vectorsAlongDimension ( )
- mulColumnVector ( )
- detach ( )
- close ( )
- tensorssAlongDimension ( )
- putColumn ( )
- javaTensorAlongDimension ( )
- isCompressed ( )
- norm1 ( )
- getRows ( )
- ravel ( )
- broadcast ( )
- isMatrix ( )
- mulRowVector ( )
- addColumnVector ( )
- toFloatVector ( )
- dimShuffle ( )
- isR ( )
- min ( )
- negi ( )
- isS ( )
- addRowVector ( )
- vectorAlongDimension ( )
- isColumnVectorOrScalar ( )
- isAttached ( )
- distance2 ( )
- shapeInfoDataBuffer ( )
Related Classes
- java.util.Arrays
- java.io.File
- java.util.Collections
- java.util.Random
- java.nio.ByteBuffer
- org.junit.Ignore
- org.apache.spark.api.java.JavaRDD
- org.nd4j.linalg.factory.Nd4j
- org.deeplearning4j.nn.conf.NeuralNetConfiguration
- org.deeplearning4j.nn.weights.WeightInit
- org.deeplearning4j.nn.multilayer.MultiLayerNetwork
- org.deeplearning4j.nn.conf.layers.DenseLayer
- org.deeplearning4j.nn.conf.layers.OutputLayer
- org.nd4j.linalg.activations.Activation
- org.deeplearning4j.nn.conf.MultiLayerConfiguration
- org.nd4j.linalg.lossfunctions.LossFunctions
- org.nd4j.linalg.dataset.DataSet
- org.deeplearning4j.nn.api.OptimizationAlgorithm
- org.nd4j.linalg.dataset.api.iterator.DataSetIterator
- org.deeplearning4j.nn.graph.ComputationGraph
- org.nd4j.linalg.ops.transforms.Transforms
- org.deeplearning4j.nn.conf.inputs.InputType
- org.nd4j.linalg.indexing.NDArrayIndex
- org.nd4j.linalg.learning.config.Adam
- org.deeplearning4j.nn.conf.ComputationGraphConfiguration
Java Code Examples for org.nd4j.linalg.api.ndarray.INDArray#isR()
The following examples show how to use
org.nd4j.linalg.api.ndarray.INDArray#isR() .
You can vote up the ones you like or vote down the ones you don't like,
and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example 1
Source File: MaxOut.java From deeplearning4j with Apache License 2.0 | 6 votes |
@Override public boolean validateDataTypes(OpContext oc, boolean experimentalMode) { INDArray x = oc != null ? oc.getInputArray(0) : x(); INDArray y = oc != null ? oc.getInputArray(1) : y(); INDArray z = oc != null ? oc.getOutputArray(0) : z(); if (!x.isR()) return false; if (y != null && !y().isR()) return false; if (z != null && z().dataType() != x().dataType()) return false; return true; }
Example 2
Source File: Variance.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public DataType resultType(OpContext oc){ INDArray x = oc != null ? oc.getInputArray(0) : x(); if (x != null && x.isR()) return x.dataType(); if(this.arg() != null){ return this.arg().dataType(); } return Nd4j.defaultFloatingPointType(); }
Example 3
Source File: Variance.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public boolean validateDataTypes(OpContext oc) { INDArray x = oc != null ? oc.getInputArray(0) : x(); if (x != null && !x.isR()) { return false; } INDArray y = oc != null ? oc.getInputArray(1) : y(); if (y != null && !y.isR()) return false; INDArray z = oc != null ? oc.getOutputArray(0) : z(); return !(z != null && !z.isR()); }
Example 4
Source File: BaseReduceFloatOp.java From deeplearning4j with Apache License 2.0 | 5 votes |
@Override public DataType resultType(OpContext oc) { INDArray x = oc != null ? oc.getInputArray(0) : x(); if (x != null && x.isR()) return x.dataType(); return Nd4j.defaultFloatingPointType(); }