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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)
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