# Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import random import unittest from transformers import is_bitsandbytes_available, is_sklearn_available, is_wandb_available from trl import BaseBinaryJudge, BasePairwiseJudge, is_diffusers_available, is_llm_blender_available # transformers.testing_utils contains a require_bitsandbytes function, but relies on pytest markers which we don't use # in our test suite. We therefore need to implement our own version of this function. def require_bitsandbytes(test_case): """ Decorator marking a test that requires bitsandbytes. Skips the test if bitsandbytes is not available. """ return unittest.skipUnless(is_bitsandbytes_available(), "test requires bitsandbytes")(test_case) def require_diffusers(test_case): """ Decorator marking a test that requires diffusers. Skips the test if diffusers is not available. """ return unittest.skipUnless(is_diffusers_available(), "test requires diffusers")(test_case) def require_no_wandb(test_case): """ Decorator marking a test that requires no wandb. Skips the test if wandb is available. """ return unittest.skipUnless(not is_wandb_available(), "test requires no wandb")(test_case) def require_sklearn(test_case): """ Decorator marking a test that requires sklearn. Skips the test if sklearn is not available. """ return unittest.skipUnless(is_sklearn_available(), "test requires sklearn")(test_case) def require_llm_blender(test_case): """ Decorator marking a test that requires llm-blender. Skips the test if llm-blender is not available. """ return unittest.skipUnless(is_llm_blender_available(), "test requires llm-blender")(test_case) class RandomBinaryJudge(BaseBinaryJudge): """ Random binary judge, for testing purposes. """ def judge(self, prompts, completions, gold_completions=None, shuffle_order=True): return [random.choice([0, 1, -1]) for _ in range(len(prompts))] class RandomPairwiseJudge(BasePairwiseJudge): """ Random pairwise judge, for testing purposes. """ def judge(self, prompts, completions, shuffle_order=True, return_scores=False): if not return_scores: return [random.randint(0, len(completion) - 1) for completion in completions] else: return [random.random() for _ in range(len(prompts))]