diff --git a/pvnet/models/multimodal/multimodal.py b/pvnet/models/multimodal/multimodal.py index 8ebe9e09..9b04a52d 100644 --- a/pvnet/models/multimodal/multimodal.py +++ b/pvnet/models/multimodal/multimodal.py @@ -58,22 +58,22 @@ def __init__( """Neural network which combines information from different sources. Notes: - In the args, where it says a module `m` is partially instantiated, it means that a + In the args, where it says a module `m` is partially instantiated, it means that a normal pytorch module will be returned by running `mod = m(**kwargs)`. In this library, - this partial instantiation is generally achieved using partial instantiation via hydra. - However, the arg is still valid as long as `m(**kwargs)` returns a valid pytorch module + this partial instantiation is generally achieved using partial instantiation via hydra. + However, the arg is still valid as long as `m(**kwargs)` returns a valid pytorch module - for example if `m` is a regular function. Args: - output_network: A partially instatiated pytorch Module class used to combine the 1D + output_network: A partially instatiated pytorch Module class used to combine the 1D features to produce the forecast. output_quantiles: A list of float (0.0, 1.0) quantiles to predict values for. If set to None the output is a single value. - nwp_encoder: A partially instatiated pytorch Module class used to encode the NWP data + nwp_encoder: A partially instatiated pytorch Module class used to encode the NWP data from 4D into an 1D feature vector. - sat_encoder: A partially instatiated pytorch Module class used to encode the satellite + sat_encoder: A partially instatiated pytorch Module class used to encode the satellite data from 4D into an 1D feature vector. - pv_encoder: A partially instatiated pytorch Module class used to encode the site-level + pv_encoder: A partially instatiated pytorch Module class used to encode the site-level PV data from 2D into an 1D feature vector. add_image_embedding_channel: Add a channel to the NWP and satellite data with the embedding of the GSP ID. @@ -83,9 +83,9 @@ def __init__( `None`. forecast_minutes: The amount of minutes that should be forecasted. history_minutes: The default amount of historical minutes that are used. - sat_history_minutes: Length of recent observations used for satellite inputs. Defaults + sat_history_minutes: Length of recent observations used for satellite inputs. Defaults to `history_minutes` if not provided. - min_sat_delay_minutes: Minimum delay with respect to t0 of the latest available + min_sat_delay_minutes: Minimum delay with respect to t0 of the latest available satellite image. nwp_forecast_minutes: Period of future NWP forecast data used as input. Defaults to `forecast_minutes` if not provided.