Random

bernoulli

INDArray bernoulli(double p, DataType datatype, long[] shape)
SDVariable bernoulli(double p, DataType datatype, long[] shape)
SDVariable bernoulli(String name, double p, DataType datatype, long[] shape)
Generate a new random INDArray, where values are randomly sampled according to a Bernoulli distribution,
with the specified probability. Array values will have value 1 with probability P and value 0 with probability
1-P.
  • p - Probability of value 1
  • datatype - Data type of the output variable
  • shape - Shape of the new random INDArray, as a 1D array (Size: AtLeast(min=0))

binomial

INDArray binomial(int nTrials, double p, DataType datatype, long[] shape)
SDVariable binomial(int nTrials, double p, DataType datatype, long[] shape)
SDVariable binomial(String name, int nTrials, double p, DataType datatype, long[] shape)
Generate a new random INDArray, where values are randomly sampled according to a Binomial distribution,
with the specified number of trials and probability.
  • nTrials - Number of trials parameter for the binomial distribution
  • p - Probability of success for each trial
  • datatype - Data type of the output variable
  • shape - Shape of the new random INDArray, as a 1D array (Size: AtLeast(min=0))

exponential

INDArray exponential(double lambda, DataType datatype, long[] shape)
SDVariable exponential(double lambda, DataType datatype, long[] shape)
SDVariable exponential(String name, double lambda, DataType datatype, long[] shape)
Generate a new random INDArray, where values are randomly sampled according to a exponential distribution:
P(x) = lambda exp(-lambda x)
  • lambda - lambda parameter
  • datatype - Data type of the output variable
  • shape - Shape of the new random INDArray, as a 1D array (Size: AtLeast(min=0))

logNormal

INDArray logNormal(double mean, double stddev, DataType datatype, long[] shape)
SDVariable logNormal(double mean, double stddev, DataType datatype, long[] shape)
SDVariable logNormal(String name, double mean, double stddev, DataType datatype, long[] shape)
Generate a new random INDArray, where values are randomly sampled according to a Log Normal distribution,
i.e., log(x) ~ N(mean, stdev)
  • mean - Mean value for the random array
  • stddev - Standard deviation for the random array
  • datatype - Data type of the output variable
  • shape - Shape of the new random INDArray, as a 1D array (Size: AtLeast(min=0))

normal

INDArray normal(double mean, double stddev, DataType datatype, long[] shape)
SDVariable normal(double mean, double stddev, DataType datatype, long[] shape)
SDVariable normal(String name, double mean, double stddev, DataType datatype, long[] shape)
Generate a new random INDArray, where values are randomly sampled according to a Gaussian (normal) distribution,
N(mean, stdev)
  • mean - Mean value for the random array
  • stddev - Standard deviation for the random array
  • datatype - Data type of the output variable
  • shape - Shape of the new random INDArray, as a 1D array (Size: AtLeast(min=0))

normalTruncated

INDArray normalTruncated(double mean, double stddev, DataType datatype, long[] shape)
SDVariable normalTruncated(double mean, double stddev, DataType datatype, long[] shape)
SDVariable normalTruncated(String name, double mean, double stddev, DataType datatype, long[] shape)
Generate a new random INDArray, where values are randomly sampled according to a Gaussian (normal) distribution,
N(mean, stdev). However, any values more than 1 standard deviation from the mean are dropped and re-sampled
  • mean - Mean value for the random array
  • stddev - Standard deviation for the random array
  • datatype - Data type of the output variable
  • shape - Shape of the new random INDArray, as a 1D array (Size: AtLeast(min=0))

uniform

INDArray uniform(double min, double max, DataType datatype, long[] shape)
SDVariable uniform(double min, double max, DataType datatype, long[] shape)
SDVariable uniform(String name, double min, double max, DataType datatype, long[] shape)
Generate a new random INDArray, where values are randomly sampled according to a uniform distribution,
U(min,max)
  • min - Minimum value
  • max - Maximum value.
  • datatype - Data type of the output variable
  • shape - Shape of the new random INDArray, as a 1D array (Size: AtLeast(min=0))