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49 lines
1.5 KiB
Python
49 lines
1.5 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from abc import ABC, abstractmethod
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class BaseTask(ABC):
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"""
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A task represents a single evaluation benchmark, including it's dataset, preprocessing, postprocessing and scoring methods.
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Base class for all evaluation tasks. Each task needs to implement the following methods:
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- F1: preprocess_sample(self)
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- F2: postprocess_sample(self)
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- F3: score_sample(self)
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"""
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def __init__(self, dataset, *args, **kwargs):
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super().__init__(*args, **kwargs)
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self._name = self.__class__.__name__
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self.dataset = dataset
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@abstractmethod
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def preprocess_sample(self, sample):
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raise NotImplementedError()
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@abstractmethod
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def postprocess_sample(self, sample):
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raise NotImplementedError()
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@abstractmethod
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def score_sample(self, sample, ground_truth):
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raise NotImplementedError()
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@abstractmethod
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def aggregate_results(self, eval_results):
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raise NotImplementedError()
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def preprocess(self):
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return [self.preprocess_sample(sample) for sample in self.dataset]
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def postprocess(self, generation):
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return [self.postprocess_sample(sample) for sample in generation]
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def score(self, postprocessed):
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return [
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self.score_sample(sample, ground_truth)
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for sample, ground_truth in zip(postprocessed, self.dataset)
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]
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