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)

Bases: mxnet.gluon.block.HybridBlock

hybrid_forward(F, x: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol]) → Tuple[Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol]]

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)

Bases: gluonts.mx.distribution.distribution_output.DistributionOutput

args_dim: Dict[str, int]

distr_cls: type

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

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) → gluonts.mx.distribution.distribution_output.ArgProj