diff --git a/python/paddle/trainer_config_helpers/evaluators.py b/python/paddle/trainer_config_helpers/evaluators.py index 72cfbecf6d36ce33f4dfc185cb963f759a822186..57979db4de08989ab583b0ab41589c09789a0921 100644 --- a/python/paddle/trainer_config_helpers/evaluators.py +++ b/python/paddle/trainer_config_helpers/evaluators.py @@ -297,7 +297,8 @@ def auc_evaluator( def pnpair_evaluator( input, label, - weight, + info, + weight=None, name=None, ): """ Positive-negative pair rate Evaluator which adapts to rank task like @@ -307,22 +308,29 @@ def pnpair_evaluator( .. code-block:: python - eval = pnpair_evaluator(input, label, weight) + eval = pnpair_evaluator(input, label, info) :param input: Input Layer name. The output prediction of network. :type input: LayerOutput :param label: Label layer name. :type label: LayerOutput + :param info: Info layer name. (TODO, explaination) + :type info: LayerOutput :param weight: Weight Layer name. It should be a matrix with size [sample_num, 1]. (TODO, explaination) :type weight: LayerOutput :param name: Evaluator name. :type name: None|basestring """ + if not isinstance(input, list): + input = [input] + if label: + input.append(label) + if info: + input.append(info) evaluator_base( input=input, type="pnpair", - label=label, weight=weight, name=name, ) @@ -425,12 +433,12 @@ def chunk_evaluator( .. code-block:: text - Scheme Description + Scheme Description plain Use the same label for the whole chunk. - IOB Two labels for chunk type X, B-X for chunk begining and I-X for chunk inside. + IOB Two labels for chunk type X, B-X for chunk begining and I-X for chunk inside. IOE Two labels for chunk type X, E-X for chunk ending and I-X for chunk inside. - IOBES Four labels for chunk type X, B-X for chunk begining, I-X for chunk inside, E-X for chunk end and S-X for single word chunk. - + IOBES Four labels for chunk type X, B-X for chunk begining, I-X for chunk inside, E-X for chunk end and S-X for single word chunk. + To make it clear, let's illustrate by an NER example. Assuming that there are three named entity types including ORG, PER and LOC which are called 'chunk type' here, if 'IOB' scheme were used, the label set will be extended to a set including B-ORG, I-ORG, B-PER, I-PER, B-LOC, I-LOC and O, @@ -447,7 +455,7 @@ def chunk_evaluator( tagType = label % numTagType chunkType = label / numTagType otherChunkType = numChunkTypes - + The following table shows the mapping rule between tagType and tag type in each scheme. .. code-block:: text @@ -471,7 +479,7 @@ def chunk_evaluator( O 6 In this example, chunkType has three values: 0 for ORG, 1 for PER, 2 for LOC, because the scheme is - "IOB" so tagType has two values: 0 for B and 1 for I. + "IOB" so tagType has two values: 0 for B and 1 for I. Here we will use I-LOC to explain the above mapping rules in detail. For I-LOC, the label id is 5, so we can get tagType=1 and chunkType=2, which means I-LOC is a part of NER chunk LOC and the tag is I. @@ -482,7 +490,7 @@ def chunk_evaluator( eval = chunk_evaluator(input, label, chunk_scheme, num_chunk_types) - + :param input: The input layers. :type input: LayerOutput :param label: An input layer containing the ground truth label.