DataEmbedding_inverted

class pytorch_forecasting.models.timexer.sub_modules.DataEmbedding_inverted(c_in, d_model, embed_type='fixed', freq='h', dropout=0.1)

Bases: Module

Data embedding module for time series data. :param c_in: Number of input features. :type c_in: int :param d_model: Dimension of the model. :type d_model: int :param embed_type: Type of embedding to use. Defaults to “fixed”. :type embed_type: str :param freq: Frequency of the time series data. Defaults to “h”. :type freq: str :param dropout: Dropout rate. Defaults to 0.1. :type dropout: float

Initialize internal Module state, shared by both nn.Module and ScriptModule.

Methods

forward(x, x_mark)

Define the computation performed at every call.

forward(x, x_mark)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.