gluonts.mx.distribution.transformed_distribution_output module

class gluonts.mx.distribution.transformed_distribution_output.TransformedDistributionOutput(base_distr_output: gluonts.mx.distribution.distribution_output.DistributionOutput, transforms_output: List[gluonts.mx.distribution.bijection_output.BijectionOutput])[source]

Bases: gluonts.mx.distribution.distribution_output.DistributionOutput

Class to connect a network to a distribution that is transformed by a sequence of learnable bijections.

distr_cls = None
distribution(distr_args, loc: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol, None] = None, scale: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol, None] = None) → gluonts.mx.distribution.distribution.Distribution[source]

Construct the associated distribution, given the collection of constructor arguments and, optionally, a scale tensor.

Parameters
  • distr_args – Constructor arguments for the underlying Distribution type.

  • loc – Optional tensor, of the same shape as the batch_shape+event_shape of the resulting distribution.

  • scale – Optional tensor, of the same shape as the batch_shape+event_shape of the resulting distribution.

domain_map(F, *args: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol])[source]

Converts arguments to the right shape and domain. The domain depends on the type of distribution, while the correct shape is obtained by reshaping the trailing axis in such a way that the returned tensors define a distribution of the right event_shape.

property event_shape

Shape of each individual event contemplated by the distributions that this object constructs.

get_args_proj(prefix: Optional[str] = None) → gluonts.mx.distribution.distribution_output.ArgProj[source]