Available Methods
- create ( )
- rand ( )
- exec ( )
- zeros ( )
- ones ( )
- linspace ( )
- createFromArray ( )
- createUninitialized ( )
- scalar ( )
- createBuffer ( )
- dataType ( )
- read ( )
- setDataType ( )
- order ( )
- getExecutioner ( )
- vstack ( )
- write ( )
- sizeOfDataType ( )
- valueArrayOf ( )
- randn ( )
- createArrayFromShapeBuffer ( )
- getStrides ( )
- getRandom ( )
- EPS_THRESHOLD
- createComplex ( )
- setDefaultDataTypes ( )
- hstack ( )
- concat ( )
- argMax ( )
- createTypedBuffer ( )
- createSparseCOO ( )
- pullRows ( )
- copy ( )
- shuffle ( )
- createDouble ( )
- defaultFloatingPointType ( )
- toFlattened ( )
- alloc ( )
- pile ( )
- getComplexStrides ( )
- zerosLike ( )
- empty ( )
- createBufferDetached ( )
- toNpyByteArray ( )
- createFromNpyFile ( )
- arange ( )
- ENFORCE_NUMERICAL_STABILITY
- gemm ( )
- averageAndPropagate ( )
- saveBinary ( )
- createSparseCSR ( )
- expandDims ( )
- sort ( )
- clearNans ( )
- tensorMmul ( )
- eye ( )
- append ( )
- createFromFlatArray ( )
- createComplexNumber ( )
- accumulate ( )
- readBinary ( )
- isFallbackModeEnabled ( )
- createFloat ( )
- MAX_SLICES_TO_PRINT
- writeComplex ( )
- createTypedBufferDetached ( )
- isExperimentalMode ( )
- trueScalar ( )
- createNpyFromByteArray ( )
- createFromNpzFile ( )
Related Classes
- java.util.Arrays
- java.io.File
- java.util.Collections
- java.util.Random
- java.nio.ByteBuffer
- org.junit.Ignore
- org.nd4j.linalg.api.ndarray.INDArray
- 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.bytedeco.javacpp.Pointer
- org.nd4j.linalg.indexing.NDArrayIndex
- org.nd4j.linalg.learning.config.Adam
- org.deeplearning4j.nn.conf.ComputationGraphConfiguration
Java Code Examples for org.nd4j.linalg.factory.Nd4j#MAX_SLICES_TO_PRINT
The following examples show how to use
org.nd4j.linalg.factory.Nd4j#MAX_SLICES_TO_PRINT .
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Example 1
Source File: BaseNd4jTest.java From nd4j with Apache License 2.0 | 5 votes |
@Before public void before() throws Exception { log.info("Running " + getClass().getName() + " on backend " + backend.getClass().getName()); Nd4j nd4j = new Nd4j(); nd4j.initWithBackend(backend); Nd4j.factory().setOrder(ordering()); Nd4j.MAX_ELEMENTS_PER_SLICE = -1; Nd4j.MAX_SLICES_TO_PRINT = -1; }
Example 2
Source File: BaseNd4jTest.java From nd4j with Apache License 2.0 | 5 votes |
@After public void after() throws Exception { log.info("Ending " + getClass().getName()); if (System.getProperties().getProperty("backends") != null && !System.getProperty("backends").contains(backend.getClass().getName())) return; Nd4j nd4j = new Nd4j(); nd4j.initWithBackend(backend); Nd4j.factory().setOrder(ordering()); Nd4j.MAX_ELEMENTS_PER_SLICE = -1; Nd4j.MAX_SLICES_TO_PRINT = -1; }
Example 3
Source File: OpExecutionerTestsC.java From nd4j with Apache License 2.0 | 5 votes |
@Test public void testColumnStd() { Nd4j.MAX_ELEMENTS_PER_SLICE = Integer.MAX_VALUE; Nd4j.MAX_SLICES_TO_PRINT = Integer.MAX_VALUE; INDArray twoByThree = Nd4j.linspace(1, 600, 600).reshape(150, 4); INDArray columnStd = twoByThree.std(0); INDArray assertion = Nd4j.create(new float[] {173.78147196982766f, 173.78147196982766f, 173.78147196982766f, 173.78147196982766f}); assertEquals(assertion, columnStd); }