gluonts.mx.distribution.lowrank_gp module#

class gluonts.mx.distribution.lowrank_gp.GPArgProj(rank: int, sigma_init: float = 1.0, sigma_minimum: float = 0.001, mu_ratio: float = 1.0, dropout_rate: float = 0.0, prefix: Optional[str] = None)[source]#

Bases: HybridBlock

hybrid_forward(F, x: Union[NDArray, Symbol]) → Tuple[Union[NDArray, Symbol], Union[NDArray, Symbol], Union[NDArray, Symbol]][source]#
Parameters:

  • F –

  • x ((..., dim, hidden_dim)) –

Returns:

  • Returns (mu, D, W) where shapes are (…, dim), (…, dim),

  • (…, dim, rank)

class gluonts.mx.distribution.lowrank_gp.LowrankGPOutput(rank: int, dim: Optional[int] = None, sigma_init: float = 1.0, mu_ratio: float = 1.0, dropout_rate: float = 0.0)[source]#

Bases: DistributionOutput

distribution(distr_args, loc=None, scale=None, dim=None)[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.

property event_dim: int#

Number of event dimensions, i.e., length of the event_shape tuple, of the distributions that this object constructs.

property event_shape: Tuple#

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

get_args_proj(prefix: Optional[str] = None) → ArgProj[source]#