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’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.
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.

Examples

For more information on how metric works with Engine, visit Attach Engine API.

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

`compute`	Computes the metric based on it's accumulated state.
`reset`	Resets the metric to it's initial state.
`update`	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 when completed() is called.

Return type

Any

Raises

NotComputableError – raised when the metric cannot be computed.

reset()[source]#

Resets the metric to it’s initial state.

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

Return type: None

update(output)[source]#

Updates the metric’s state using the passed batch output.

By default, this is called once for each batch.

Parameters: output (Tuple[Sequence[Sequence[Any]], Sequence[Sequence[Sequence[Any]]]]) – the is the output from the engine’s process function.
Return type: None