mxfusion.components.distributions.bernoulli

Members

class mxfusion.components.distributions.bernoulli.BernoulliLogPDFDecorator

Bases: mxfusion.components.distributions.distribution.LogPDFDecorator

class mxfusion.components.distributions.bernoulli.BernoulliDrawSamplesDecorator

Bases: mxfusion.components.distributions.distribution.DrawSamplesDecorator

class mxfusion.components.distributions.bernoulli.Bernoulli(prob_true, rand_gen=None, dtype=None, ctx=None)

Bases: mxfusion.components.distributions.univariate.UnivariateDistribution

The Bernoulli distribution.

Parameters:
  • prob_true (Variable) – the probability of being true.
  • rand_gen (RandomGenerator) – the random generator (default: MXNetRandomGenerator).
  • dtype (numpy.float32 or numpy.float64) – the data type for float point numbers.
  • ctx (None or mxnet.cpu or mxnet.gpu) – the mxnet context (default: None/current context).
replicate_self(attribute_map=None)

This functions as a copy constructor for the object. In order to do a copy constructor we first call __new__ on the class which creates a blank object. We then initialize that object using the methods standard init procedures, and do any extra copying of attributes.

Replicates this Factor, using new inputs, outputs, and a new uuid. Used during model replication to functionally replicate a factor into a new graph.

Parameters:
  • inputs (List of tuples of name to node e.g. [('random_variable': Variable y)] or None) – new input variables of the factor.
  • outputs (List of tuples of name to node e.g. [('random_variable': Variable y)] or None) – new output variables of the factor.
log_pdf(F, variables, targets=None)

Computes the logarithm of the probability density/mass function (PDF/PMF) of the distribution. The inputs and outputs variables are fetched from the variables argument according to their UUIDs.

Parameters:
  • F (mxnet.symbol or mxnet.ndarray) – the MXNet computation mode
  • variables – the set of MXNet arrays that holds the values of

variables at runtime. :type variables: {str(UUID): MXNet NDArray or MXNet Symbol} :returns: log pdf of the distribution :rtypes: MXNet NDArray or MXNet Symbol

draw_samples(F, variables, num_samples=1, always_return_tuple=False, targets=None)

Draw a set of samples from the distribution. The inputs variables are fetched from the variables argument according to their UUIDs.

Parameters:
  • F (mxnet.symbol or mxnet.ndarray) – the MXNet computation mode
  • variables – the set of MXNet arrays that holds the values of

variables at runtime. :type variables: {str(UUID): MXNet NDArray or MXNet Symbol} :param num_samples: the number of drawn samples (default: one) :int num_samples: int :param always_return_tuple: Whether return a tuple even if there is only one variables in outputs. :type always_return_tuple: boolean :returns: a set samples of the distribution :rtypes: MXNet NDArray or MXNet Symbol or [MXNet NDArray or MXNet Symbol]

static define_variable(prob_true, shape=None, rand_gen=None, dtype=None, ctx=None)

Creates and returns a random variable drawn from a Bernoulli distribution.

Parameters:
  • prob_true (Variable) – the probability being true.
  • shape (tuple of int) – the shape of the Bernoulli variable.
  • rand_gen (RandomGenerator) – the random generator (default: MXNetRandomGenerator).
  • dtype (numpy.float32 or numpy.float64) – the data type for float point numbers.
  • ctx (None or mxnet.cpu or mxnet.gpu) – the mxnet context (default: None/current context).
Returns:

RandomVariable drawn from the Bernoulli distribution.
Rtypes:

Variable