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77 lines
3.3 KiB
Python
77 lines
3.3 KiB
Python
# Copyright 2020-2025 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import time
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import unittest
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from trl import AllTrueJudge, HfPairwiseJudge, PairRMJudge
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from .testing_utils import RandomBinaryJudge, require_llm_blender
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class TestJudges(unittest.TestCase):
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def _get_prompts_and_pairwise_completions(self):
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prompts = ["The capital of France is", "The biggest planet in the solar system is"]
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completions = [["Paris", "Marseille"], ["Saturn", "Jupiter"]]
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return prompts, completions
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def _get_prompts_and_single_completions(self):
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prompts = ["What's the capital of France?", "What's the color of the sky?"]
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completions = ["Marseille", "blue"]
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return prompts, completions
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def test_all_true_judge(self):
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judge = AllTrueJudge(judges=[RandomBinaryJudge(), RandomBinaryJudge()])
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prompts, completions = self._get_prompts_and_single_completions()
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judgements = judge.judge(prompts=prompts, completions=completions)
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self.assertEqual(len(judgements), 2)
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self.assertTrue(all(judgement in {0, 1, -1} for judgement in judgements))
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@unittest.skip("This test needs to be run manually since it requires a valid Hugging Face API key.")
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def test_hugging_face_judge(self):
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judge = HfPairwiseJudge()
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prompts, completions = self._get_prompts_and_pairwise_completions()
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ranks = judge.judge(prompts=prompts, completions=completions)
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self.assertEqual(len(ranks), 2)
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self.assertTrue(all(isinstance(rank, int) for rank in ranks))
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self.assertEqual(ranks, [0, 1])
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def load_pair_rm_judge(self):
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# When using concurrent tests, PairRM may fail to load the model while another job is still downloading.
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# This is a workaround to retry loading the model a few times.
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for _ in range(5):
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try:
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return PairRMJudge()
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except ValueError:
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time.sleep(5)
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raise ValueError("Failed to load PairRMJudge")
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@require_llm_blender
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def test_pair_rm_judge(self):
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judge = self.load_pair_rm_judge()
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prompts, completions = self._get_prompts_and_pairwise_completions()
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ranks = judge.judge(prompts=prompts, completions=completions)
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self.assertEqual(len(ranks), 2)
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self.assertTrue(all(isinstance(rank, int) for rank in ranks))
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self.assertEqual(ranks, [0, 1])
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@require_llm_blender
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def test_pair_rm_judge_return_scores(self):
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judge = self.load_pair_rm_judge()
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prompts, completions = self._get_prompts_and_pairwise_completions()
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probs = judge.judge(prompts=prompts, completions=completions, return_scores=True)
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self.assertEqual(len(probs), 2)
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self.assertTrue(all(isinstance(prob, float) for prob in probs))
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self.assertTrue(all(0 <= prob <= 1 for prob in probs))
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