Rouge#
- class ignite.metrics.Rouge(variants=None, multiref='average', alpha=0, output_transform=<function Rouge.<lambda>>, device=device(type='cpu'))[source]#
Calculates the Rouge score for multiples Rouge-N and Rouge-L metrics.
More details can be found in Lin 2004.
update
must receive output of the form(y_pred, y)
or{'y_pred': y_pred, 'y': y}
.y_pred (list(list(str))) must be a sequence of tokens.
y (list(list(list(str))) must be a list of sequence of tokens.
- Parameters
variants (Optional[Sequence[Union[str, int]]]) – set of metrics computed. Valid inputs are “L” and integer 1 <= n <= 9.
multiref (str) – reduces scores for multi references. Valid values are “best” and “average” (default: “average”).
alpha (float) – controls the importance between recall and precision (alpha -> 0: recall is more important, alpha -> 1: precision is more important)
output_transform (Callable) – a callable that is used to transform the
Engine
’sprocess_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.device (Union[str, torch.device]) – specifies which device updates are accumulated on. Setting the metric’s device to be the same as your
update
arguments ensures theupdate
method is non-blocking. By default, CPU.
Examples
from ignite.metrics import Rouge m = Rouge(variants=["L", 2], multiref="best") candidate = "the cat is not there".split() references = [ "the cat is on the mat".split(), "there is a cat on the mat".split() ] m.update(([candidate], [references])) print(m.compute())
{'Rouge-L-P': 0.6, 'Rouge-L-R': 0.5, 'Rouge-L-F': 0.5, 'Rouge-2-P': 0.5, 'Rouge-2-R': 0.4, 'Rouge-2-F': 0.4}
New in version 0.4.5.
Changed in version 0.4.7:
update
method has changed and now works on batch of inputs.Methods
Computes the metric based on it's accumulated state.
Resets the metric to it's initial state.
Updates the metric's state using the passed batch output.
- compute()[source]#
Computes the metric based on it’s accumulated state.
By default, this is called at the end of each epoch.
- Returns
- the actual quantity of interest. However, if a
Mapping
is returned, it will be (shallow) flattened into engine.state.metrics whencompleted()
is called. - Return type
Any
- Raises
NotComputableError – raised when the metric cannot be computed.