sup3r.utilities.loss_metrics.GeothermalPhysicsLoss#
- class GeothermalPhysicsLoss(gen_features='all', true_features=None)[source]#
Bases:
Sup3rLossPhysics based loss for Geothermal applications
TODO: Fill in call with appropriate physics equations. This is currently just a dummy equation for testing.
Initialize the loss with given input features
- Parameters:
gen_features (list | str) – List of generator output features that the loss metric will be calculated on. If ‘all’, the loss will be calculated on all generator features. Otherwise, the loss will be calculated on the features specified in the list. The order of features in the list will be checked to determine the order of features in the generator output tensor.
true_features (list | str) – List of true features that the loss metric will be calculated on. If None, this will be the same as gen_features. The order of features in the list will be checked to determine the order of features in the ground truth tensor.
Methods
call(y_true, y_pred)Invokes the Loss instance.
from_config(config)Instantiates a Loss from its config (output of get_config()).
Returns the config dictionary for a Loss instance.
Attributes
LOSS_METRIC- abstract call(y_true, y_pred)#
Invokes the Loss instance.
- Args:
- y_true: Ground truth values. shape = [batch_size, d0, .. dN],
except sparse loss functions such as sparse categorical crossentropy where shape = [batch_size, d0, .. dN-1]
y_pred: The predicted values. shape = [batch_size, d0, .. dN]
- Returns:
Loss values with the shape [batch_size, d0, .. dN-1].
- classmethod from_config(config)#
Instantiates a Loss from its config (output of get_config()).
- Args:
config: Output of get_config().
- Returns:
A Loss instance.
- get_config()#
Returns the config dictionary for a Loss instance.