Core Module Documentation#
- class neuralprophet.components.future_regressors.base.FutureRegressors(config, id_list, quantiles, n_forecasts, device, config_trend_none_bool)#
- class neuralprophet.components.future_regressors.linear.LinearFutureRegressors(config, id_list, quantiles, n_forecasts, device, config_trend_none_bool)#
- forward(inputs, mode, indeces=None)#
Compute all seasonality components. :param f_r: future regressors inputs :type f_r: torch.Tensor, float :param mode: mode of the regressors :type mode: string, either “additive” or “multiplicative”
- Returns
Forecast component of dims (batch, n_forecasts, no_quantiles)
- Return type
torch.Tensor
- get_reg_weights(name)#
Retrieve the weights of regressor features given the name
- Parameters
name (string) – Regressor name
- Returns
Weight corresponding to the given regressor
- Return type
torch.tensor
- scalar_features_effects(features, params, indices=None)#
Computes events component of the model
- Parameters
features (torch.Tensor, float) – Features (either additive or multiplicative) related to event component dims (batch, n_forecasts, n_features)
params (nn.Parameter) – Params (either additive or multiplicative) related to events
indices (list of int) – Indices in the feature tensors related to a particular event
- Returns
Forecast component of dims (batch, n_forecasts)
- Return type
torch.Tensor
- class neuralprophet.components.future_regressors.neural_nets.NeuralNetsFutureRegressors(config, id_list, quantiles, n_forecasts, device, config_trend_none_bool)#
- all_regressors(regressor_inputs, mode)#
Compute all regressors components. :param regressor_inputs: regressor values at corresponding, dims: (batch, n_forecasts, num_regressors) :type regressor_inputs: torch.Tensor, float
- Returns
Forecast component of dims (batch, n_forecasts, num_quantiles)
- Return type
torch.Tensor
- forward(inputs, mode, indeces=None)#
Compute all seasonality components. :param f_r: future regressors inputs :type f_r: torch.Tensor, float :param mode: mode of the regressors :type mode: string, either “additive” or “multiplicative”
- Returns
Forecast component of dims (batch, n_forecasts, no_quantiles)
- Return type
torch.Tensor
- get_reg_weights(name)#
Get attributions of regressors component network w.r.t. the model input.
- Parameters
name (string) – Regressor name
- Returns
Weight corresponding to the given regressor
- Return type
torch.tensor
- regressor(regressor_input, name)#
Compute single regressor component. :param regressor_input: regressor values at corresponding, dims: (batch, n_forecasts, 1) :type regressor_input: torch.Tensor, float :param nam: Name of regressor, for attribution to corresponding model weights :type nam: str
- Returns
Forecast component of dims (batch, n_forecasts, num_quantiles)
- Return type
torch.Tensor
Compute all seasonality components. :param inputs: future regressors inputs :type inputs: torch.Tensor, float :param mode: mode of the regressors :type mode: string, either “additive” or “multiplicative”
- Returns
Forecast component of dims (batch, n_forecasts, no_quantiles)
- Return type
torch.Tensor
Get attributions of regressors component network w.r.t. the model input.
- Parameters
name (string) – Regressor name
- Returns
Weight corresponding to the given regressor
- Return type
torch.tensor
Compute single regressor component. :param regressor_input: regressor values at corresponding, dims: (batch, n_forecasts, num_regressors) :type regressor_input: torch.Tensor, float :param nam: Name of regressor, for attribution to corresponding model weights :type nam: str
- Returns
Forecast component of dims (batch, n_forecasts, num_quantiles)
- Return type
torch.Tensor
Compute all seasonality components. :param f_r: future regressors inputs :type f_r: torch.Tensor, float :param mode: mode of the regressors :type mode: string, either “additive” or “multiplicative”
- Returns
Forecast component of dims (batch, n_forecasts, no_quantiles)
- Return type
torch.Tensor
Get attributions of regressors component network w.r.t. the model input.
- Parameters
name (string) – Regressor name
- Returns
Weight corresponding to the given regressor
- Return type
torch.tensor
Compute single regressor component. :param regressor_input: regressor values at corresponding, dims: (batch, n_forecasts, 1) :type regressor_input: torch.Tensor, float :param nam: Name of regressor, for attribution to corresponding model weights :type nam: str
- Returns
Forecast component of dims (batch, n_forecasts, num_quantiles)
- Return type
torch.Tensor