class ignite.contrib.metrics.regression.R2Score(output_transform=<function Metric.<lambda>>, device=device(type='cpu'))[source]#

Calculates the R-Squared, the coefficient of determination.

R2=1j=1n(AjPj)2j=1n(AjAˉ)2R^2 = 1 - \frac{\sum_{j=1}^n(A_j - P_j)^2}{\sum_{j=1}^n(A_j - \bar{A})^2}

where AjA_j is the ground truth, PjP_j is the predicted value and Aˉ\bar{A} is the mean of the ground truth.

  • update must receive output of the form (y_pred, y) or {'y_pred': y_pred, 'y': y}.

  • y and y_pred must be of same shape (N, ) or (N, 1) and of type float32.

Parameters are inherited from Metric.__init__.

  • output_transform (Callable) – a callable that is used to transform the Engine’s process_function’s output into the form expected by the metric. This can be useful if, for example, you have a multi-output model and you want to compute the metric with respect to one of the outputs. By default, metrics require the output as (y_pred, y) or {'y_pred': y_pred, 'y': y}.

  • device (Union[str, device]) – specifies which device updates are accumulated on. Setting the metric’s device to be the same as your update arguments ensures the update method is non-blocking. By default, CPU.

Changed in version 0.4.3: Works with DDP.



Computes the metric based on it's accumulated state.


Resets the metric to it's initial state.


Computes the metric based on it’s accumulated state.

By default, this is called at the end of each epoch.


the actual quantity of interest. However, if a Mapping is returned, it will be (shallow) flattened into engine.state.metrics when completed() is called.

Return type



NotComputableError – raised when the metric cannot be computed.


Resets the metric to it’s initial state.

By default, this is called at the start of each epoch.

Return type