gluonts.mx.representation.embedding module#
- class gluonts.mx.representation.embedding.Embedding(num_bins: int, size: Optional[int] = None, *args, **kwargs)[source]#
Bases:
gluonts.mx.representation.representation.Representation
A class representing an embedding operation on top of a given binning. Note that this representation is intended to applied on top of categorical/binned data.
- Parameters
num_bins – The number of categories/bins of the data on which this representation is applied.
size – The desired embedding size. By default, the following heuristic is used: https://developers.googleblog.com/2017/11/introducing-tensorflow-feature-columns.html (default: round(num_bins**(1/4)))
- hybrid_forward(F, data: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], observed_indicator: Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], scale: Optional[Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol]], rep_params: List[Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol]], **kwargs) Tuple[Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol], List[Union[mxnet.ndarray.ndarray.NDArray, mxnet.symbol.symbol.Symbol]]] [source]#
Transform the data into the desired representation.
- Parameters
F –
data – Target data.
observed_indicator – Target observed indicator.
scale – Pre-computed scale.
rep_params – Additional pre-computed representation parameters.
**kwargs – Additional block-specfic parameters.
:param : Additional block-specfic parameters.
- Returns
Tuple consisting of the transformed data, the computed scale, and additional parameters to be passed to post_transform.
- Return type
Tuple[Tensor, Tensor, List[Tensor]]