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