gluonts.mx.distribution.lowrank_gp module¶
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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:
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]][source]¶ - Parameters
F –
x ((.., dim, hidden_dim)) –
- Returns
- Return type
Returns (mu, D, W) where shapes are (.., dim), (.., dim), (.., dim, rank)
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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:
gluonts.mx.distribution.distribution_output.DistributionOutput-
distr_cls= None¶
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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.
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property
event_dim¶ Number of event dimensions, i.e., length of the event_shape tuple, of the distributions that this object constructs.
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property
event_shape¶ Shape of each individual event contemplated by the distributions that this object constructs.
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