Table Of Contents
Table Of Contents

Random Sampling

Random number generation in MXNet

mx.rnorm

Generate nomal distribution with mean and sd

mx.runif

Generate uniform distribution in [low, high) with specified shape

mx.set.seed

Set the seed used by mxnet device-specific random number generators

Random NDArrays

mx.nd.normal

Draw random samples from a normal (Gaussian) distribution

mx.nd.random.exponential

Draw random samples from an exponential distribution

mx.nd.random.gamma

Draw random samples from a gamma distribution

mx.nd.random.generalized.negative.binomial

Draw random samples from a generalized negative binomial distribution

mx.nd.random.negative.binomial

Draw random samples from a negative binomial distribution

mx.nd.random.normal

Draw random samples from a normal (Gaussian) distribution

mx.nd.random.poisson

Draw random samples from a Poisson distribution

mx.nd.random.uniform

Draw random samples from a uniform distribution

mx.nd.sample.exponential

Concurrent sampling from multiple exponential distributions with parameters lambda (rate)

mx.nd.sample.gamma

Concurrent sampling from multiple gamma distributions with parameters alpha (shape) and beta (scale)

mx.nd.sample.generalized.negative.binomial

Concurrent sampling from multiple generalized negative binomial distributions with parameters mu (mean) and alpha (dispersion)

mx.nd.sample.multinomial

Concurrent sampling from multiple multinomial distributions

mx.nd.sample.negative.binomial

Concurrent sampling from multiple negative binomial distributions with parameters k (failure limit) and p (failure probability)

mx.nd.sample.normal

Concurrent sampling from multiple normal distributions with parameters mu (mean) and sigma (standard deviation)

mx.nd.sample.poisson

Concurrent sampling from multiple. Poisson distributions with parameters lambda (rate)

mx.nd.sample.uniform

Concurrent sampling from multiple uniform distributions on the intervals given by [low,high)

mx.nd.uniform

Draw random samples from a uniform distribution

Random Symbols

mx.symbol.random_exponential

Draw random samples from an exponential distribution

mx.symbol.random_gamma

Draw random samples from a gamma distribution

mx.symbol.random_generalized_negative_binomial

Draw random samples from a generalized negative binomial distribution

mx.symbol.random_negative_binomial

Draw random samples from a negative binomial distribution

mx.symbol.random_normal

Draw random samples from a normal (Gaussian) distribution

mx.symbol.random_poisson

Draw random samples from a Poisson distribution

mx.symbol.random_uniform

Draw random samples from a uniform distribution

mx.symbol.sample_exponential

Concurrent sampling from multiple exponential distributions with parameters lambda (rate)

mx.symbol.sample_gamma

Concurrent sampling from multiple gamma distributions with parameters alpha (shape) and beta (scale)

mx.symbol.sample_generalized_negative_binomial

Concurrent sampling from multiple generalized negative binomial distributions with parameters mu (mean) and alpha (dispersion)

mx.symbol.sample_multinomial

Concurrent sampling from multiple multinomial distributions

mx.symbol.sample_negative_binomial

Concurrent sampling from multiple negative binomial distributions with parameters k (failure limit) and p (failure probability)

mx.symbol.sample_normal

Concurrent sampling from multiple normal distributions with parameters mu (mean) and sigma (standard deviation)

mx.symbol.sample_poisson

Concurrent sampling from multiple. Poisson distributions with parameters lambda (rate)

mx.symbol.sample_uniform

Concurrent sampling from multiple uniform distributions on the intervals given by [low,high)

mx.symbol.uniform

Draw random samples from a uniform distribution