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X

x - Variable in class org.nd4j.linalg.api.ops.BaseOp
 
x() - Method in class org.nd4j.linalg.api.ops.BaseOp
 
x() - Method in interface org.nd4j.linalg.api.ops.Op
The origin ndarray
X_MAX - Static variable in class org.deeplearning4j.spark.models.embeddings.glove.GlovePerformer
 
XavierFanInInitScheme - Class in org.nd4j.weightinit.impl
Initialize the weight to: randn(shape) //N(0, 2/nIn);
XavierFanInInitScheme(char, double) - Constructor for class org.nd4j.weightinit.impl.XavierFanInInitScheme
 
XavierInitScheme - Class in org.nd4j.weightinit.impl
Initialize the weight to: range = = U * sqrt(2.0 / (fanIn + fanOut)
XavierInitScheme(char, double, double) - Constructor for class org.nd4j.weightinit.impl.XavierInitScheme
 
XavierUniformInitScheme - Class in org.nd4j.weightinit.impl
Initialize the weight to: //As per Glorot and Bengio 2010: Uniform distribution U(-s,s) with s = sqrt(6/(fanIn + fanOut)) Eq 16: http://jmlr.org/proceedings/papers/v9/glorot10a/glorot10a.pdf
XavierUniformInitScheme(char, double, double) - Constructor for class org.nd4j.weightinit.impl.XavierUniformInitScheme
 
Xception - Class in org.deeplearning4j.zoo.model
U-Net An implementation of Xception in Deeplearning4j.
xHat - Variable in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
 
xMax - Variable in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
 
xMax(double) - Method in class org.deeplearning4j.models.embeddings.learning.impl.elements.GloVe.Builder
Parameter specifying cutoff in weighting function; default 100.0
xMax(double) - Method in class org.deeplearning4j.models.glove.Glove.Builder
Parameter specifying cutoff in weighting function; default 100.0
xMax(double) - Method in class org.deeplearning4j.models.glove.GloveWeightLookupTable.Builder
Deprecated.
 
xMax(double) - Method in class org.deeplearning4j.spark.models.embeddings.glove.GloveParam.Builder
 
xMax(double) - Method in class org.deeplearning4j.ui.components.chart.ChartHorizontalBar.Builder
 
xMin(double) - Method in class org.deeplearning4j.ui.components.chart.ChartHorizontalBar.Builder
 
xMu - Variable in class org.deeplearning4j.nn.layers.normalization.BatchNormalization
 
XOR(Condition, Condition) - Static method in class org.datavec.api.transform.condition.BooleanCondition
And of all the given conditions
xor(SDVariable, SDVariable) - Method in class org.nd4j.autodiff.functions.DifferentialFunctionFactory
 
xor(SDVariable, SDVariable) - Method in class org.nd4j.autodiff.samediff.SameDiff
Boolean XOR (exclusive OR) operation: elementwise (x != 0) XOR (y != 0)
If x and y arrays have equal shape, the output shape is the same as these inputs.
Note: supports broadcasting if x and y have different shapes and are broadcastable.
Returns an array with values 1 where condition is satisfied, or value 0 otherwise.
xor(String, SDVariable, SDVariable) - Method in class org.nd4j.autodiff.samediff.SameDiff
Boolean XOR (exclusive OR) operation: elementwise (x != 0) XOR (y != 0)
If x and y arrays have equal shape, the output shape is the same as these inputs.
Note: supports broadcasting if x and y have different shapes and are broadcastable.
Returns an array with values 1 where condition is satisfied, or value 0 otherwise.
Xor - Class in org.nd4j.linalg.api.ops.impl.transforms
Boolean XOR pairwise transform
Xor(SameDiff, SDVariable, SDVariable) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
Xor(SameDiff, SDVariable, boolean, double) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
Xor(SameDiff, SDVariable, long[], boolean, Object[], double) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
Xor(SameDiff, SDVariable, Object[], double) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
Xor() - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
Xor(INDArray, INDArray) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
Xor(INDArray, INDArray, Number) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
Xor(INDArray, INDArray, INDArray, Number) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
Xor(INDArray, INDArray, long) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
Xor(INDArray, INDArray, INDArray) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
Xor(INDArray, INDArray, INDArray, long) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
Xor(INDArray, INDArray, INDArray, Number, long) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.Xor
 
xor(INDArray, INDArray) - Static method in class org.nd4j.linalg.ops.transforms.Transforms
 
Xoroshiro128(Pointer) - Constructor for class org.nd4j.nativeblas.Nd4jCpu.Xoroshiro128
Pointer cast constructor.
Xoroshiro128(Nd4jCpu.RandomBuffer) - Constructor for class org.nd4j.nativeblas.Nd4jCpu.Xoroshiro128
 
Xoroshiro128(Pointer) - Constructor for class org.nd4j.nativeblas.Nd4jCuda.Xoroshiro128
Pointer cast constructor.
Xoroshiro128(Nd4jCuda.RandomBuffer) - Constructor for class org.nd4j.nativeblas.Nd4jCuda.Xoroshiro128
 
xVals(double[]) - Static method in class org.deeplearning4j.clustering.util.MathUtils
This returns the x values of the given vector.
xVals(double[]) - Static method in class org.nd4j.linalg.util.MathUtils
This returns the x values of the given vector.
xVertexId - Variable in class org.nd4j.linalg.api.ops.BaseOp
 
xwPlusB(SDVariable, SDVariable, SDVariable) - Method in class org.nd4j.autodiff.functions.DifferentialFunctionFactory
 
XwPlusB - Class in org.nd4j.linalg.api.ops.impl.transforms
Composed op: mmul (X, W) + b
XwPlusB(SameDiff, SDVariable, SDVariable, SDVariable) - Constructor for class org.nd4j.linalg.api.ops.impl.transforms.XwPlusB
 
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