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| # Copyright 2020-2025 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 unittest | |
| import torch | |
| from trl.trainer.dpo_trainer import DataCollatorForPreference | |
| class TestDataCollatorForPreference(unittest.TestCase): | |
| def setUp(self): | |
| self.collator = DataCollatorForPreference(pad_token_id=0) | |
| def assertTensorEqual(self, tensor1, tensor2): | |
| self.assertTrue(torch.equal(tensor1, tensor2), f"Tensors are not equal:\n{tensor1}\n{tensor2}") | |
| def test_padding_behavior(self): | |
| examples = [ | |
| {"prompt_input_ids": [1, 2, 3], "chosen_input_ids": [4, 5], "rejected_input_ids": [6]}, | |
| {"prompt_input_ids": [7, 8], "chosen_input_ids": [9, 10], "rejected_input_ids": [11, 12, 13]}, | |
| ] | |
| output = self.collator.torch_call(examples) | |
| expected_prompt_input_ids = torch.tensor([[1, 2, 3], [0, 7, 8]]) | |
| expected_prompt_attention_mask = torch.tensor([[1, 1, 1], [0, 1, 1]]) | |
| expected_chosen_input_ids = torch.tensor([[4, 5], [9, 10]]) | |
| expected_chosen_attention_mask = torch.tensor([[1, 1], [1, 1]]) | |
| expected_rejected_input_ids = torch.tensor([[6, 0, 0], [11, 12, 13]]) | |
| expected_rejected_attention_mask = torch.tensor([[1, 0, 0], [1, 1, 1]]) | |
| self.assertTensorEqual(output["prompt_input_ids"], expected_prompt_input_ids) | |
| self.assertTensorEqual(output["prompt_attention_mask"], expected_prompt_attention_mask) | |
| self.assertTensorEqual(output["chosen_input_ids"], expected_chosen_input_ids) | |
| self.assertTensorEqual(output["chosen_attention_mask"], expected_chosen_attention_mask) | |
| self.assertTensorEqual(output["rejected_input_ids"], expected_rejected_input_ids) | |
| self.assertTensorEqual(output["rejected_attention_mask"], expected_rejected_attention_mask) | |
| def test_optional_fields(self): | |
| examples = [ | |
| { | |
| "prompt_input_ids": [1], | |
| "chosen_input_ids": [2], | |
| "rejected_input_ids": [3], | |
| "pixel_values": [[[0.1, 0.2], [0.3, 0.4]]], # Example 3D tensor (1x2x2) | |
| }, | |
| { | |
| "prompt_input_ids": [4], | |
| "chosen_input_ids": [5], | |
| "rejected_input_ids": [6], | |
| "pixel_values": [[[0.5, 0.6], [0.7, 0.8]]], # Example 3D tensor (1x2x2) | |
| }, | |
| ] | |
| output = self.collator.torch_call(examples) | |
| expected_pixel_values = torch.tensor( | |
| [ | |
| [[[0.1, 0.2], [0.3, 0.4]]], | |
| [[[0.5, 0.6], [0.7, 0.8]]], | |
| ] | |
| ) # Shape: (2, 1, 2, 2) | |
| self.assertTensorEqual(output["pixel_values"], expected_pixel_values) | |