# coding=utf-8
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# Licensed under the Apache License, Version 2.0 (the "License");
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# http://www.apache.org/licenses/LICENSE-2.0
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import copy
import math
from collections import OrderedDict
from libai.utils import distributed as dist
from .evaluator import DatasetEvaluator
[docs]class PPLEvaluator(DatasetEvaluator):
"""
Evaluate perplexity for Language Model.
Perplexity is a measurement of how well a probability distribution or
probability model predicts a sample.
"""
def __init__(self):
self._predictions = []
[docs] def reset(self):
self._predictions = []
[docs] def process(self, inputs, outputs):
for k, v in outputs.items():
ppl = math.exp(min(20, v.item()))
self._predictions.append({f"{k}_PPL": ppl})
[docs] def evaluate(self):
if not dist.is_main_process():
return {}
else:
predictions = self._predictions
self._results = OrderedDict()
for prediction in predictions:
for k, v in prediction.items():
if k not in self._results:
self._results[k] = 0
self._results[k] += v
for k in self._results.keys():
self._results[k] /= len(predictions)
return copy.deepcopy(self._results)