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# Copyright 2025 the LlamaFactory team.
#
# 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 pytest
from datasets import load_dataset
from llamafactory.v1.config.data_args import DataArguments
from llamafactory.v1.core.data_engine import DataEngine
@pytest.mark.parametrize("num_samples", [16])
def test_alpaca_converter(num_samples: int):
data_args = DataArguments(dataset="llamafactory/v1-sft-demo/dataset_info.yaml")
data_engine = DataEngine(data_args)
original_data = load_dataset("llamafactory/tiny-supervised-dataset", split="train")
indexes = random.choices(range(len(data_engine)), k=num_samples)
for index in indexes:
print(data_engine[index])
expected_data = {
"messages": [
{
"role": "user",
"content": [
{"type": "text", "value": original_data[index]["instruction"] + original_data[index]["input"]}
],
"loss_weight": 0.0,
},
{
"role": "assistant",
"content": [{"type": "text", "value": original_data[index]["output"]}],
"loss_weight": 1.0,
},
]
}
assert data_engine[index] == {"_dataset_name": "tiny_dataset", **expected_data}
if __name__ == "__main__":
test_alpaca_converter(1)
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