mxfusion.components.distributions.dirichlet¶
Members¶
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class
mxfusion.components.distributions.dirichlet.Dirichlet(alpha, normalization=True, rand_gen=None, dtype=None, ctx=None)¶ Bases:
mxfusion.components.distributions.distribution.DistributionThe Dirichlet distribution.
Parameters: - a (Variable) – alpha, the concentration parameters of the distribution.
- normalization (boolean) – If true, L1 normalization is applied.
- 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).
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log_pdf_impl(alpha, random_variable, F=None)¶ Computes the logarithm of the probability density function (pdf) of the Dirichlet distribution.
Parameters: - a (MXNet NDArray or MXNet Symbol) – the a parameter (alpha) of the Dirichlet distribution.
- random_variable (MXNet NDArray or MXNet Symbol) – the random variable of the Dirichlet distribution.
- F – the MXNet computation mode (mxnet.symbol or mxnet.ndarray).
Returns: log pdf of the distribution.
Rtypes: MXNet NDArray or MXNet Symbol
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draw_samples_impl(alpha, rv_shape, num_samples=1, F=None)¶ Draw samples from the Dirichlet distribution.
Parameters: - a (MXNet NDArray or MXNet Symbol) – the a parameter (alpha) of the Dirichlet distribution.
- rv_shape (tuple) – the shape of each sample (this variable is not used because the shape of the random var is given by the shape of a)
- num_samples (int) – the number of drawn samples (default: one).
- F – the MXNet computation mode (mxnet.symbol or mxnet.ndarray).
Returns: a set samples of the Dirichlet distribution.
Rtypes: MXNet NDArray or MXNet Symbol
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static
define_variable(alpha, shape=None, normalization=True, rand_gen=None, dtype=None, ctx=None)¶ Creates and returns a random variable drawn from a Dirichlet distribution.
Parameters: - a (Variable) – alpha, the concentration parameters of the distribution.
- normalization (boolean) – If true, L1 normalization is applied.
- 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: the random variables drawn from the Dirichlet distribution.
Rtypes: Variable
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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: