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# Copyright (c) Alibaba, Inc. and its affiliates.
import unittest
from typing import Any, Dict, Optional
import torch
from swift.llm import (DatasetMeta, InferRequest, Model, ModelGroup, ModelMeta, PtEngine, RequestConfig,
ResponsePreprocessor, TemplateMeta, get_model_tokenizer_with_flash_attn, load_dataset,
register_dataset, register_model, register_template)
class CustomPreprocessor(ResponsePreprocessor):
prompt = """Task: Based on the given two sentences, provide a similarity score between 0.0 and 5.0.
Sentence 1: {text1}
Sentence 2: {text2}
Similarity score: """
def preprocess(self, row: Dict[str, Any]) -> Optional[Dict[str, Any]]:
return super().preprocess({
'query': self.prompt.format(text1=row['text1'], text2=row['text2']),
'response': f"{row['label']:.1f}"
})
register_dataset(
DatasetMeta(
ms_dataset_id='swift/stsb',
hf_dataset_id='SetFit/stsb',
preprocess_func=CustomPreprocessor(),
))
register_template(
TemplateMeta(
template_type='custom',
prefix=['<extra_id_0>System\n{{SYSTEM}}\n'],
prompt=['<extra_id_1>User\n{{QUERY}}\n<extra_id_1>Assistant\n'],
chat_sep=['\n']))
register_model(
ModelMeta(
model_type='custom',
model_groups=[
ModelGroup([Model('AI-ModelScope/Nemotron-Mini-4B-Instruct', 'nvidia/Nemotron-Mini-4B-Instruct')])
],
template='custom',
get_function=get_model_tokenizer_with_flash_attn,
ignore_patterns=['nemo']))
class TestCustom(unittest.TestCase):
def test_custom_model(self):
infer_request = InferRequest(messages=[{'role': 'user', 'content': 'who are you?'}])
request_config = RequestConfig(max_tokens=512, temperature=0)
engine = PtEngine('AI-ModelScope/Nemotron-Mini-4B-Instruct', torch.float16)
response = engine.infer([infer_request], request_config)
swift_response = response[0].choices[0].message.content
engine.default_template.template_backend = 'jinja'
response = engine.infer([infer_request], request_config)
jinja_response = response[0].choices[0].message.content
assert swift_response == jinja_response, (f'swift_response: {swift_response}\njinja_response: {jinja_response}')
print(f'response: {swift_response}')
def test_custom_dataset(self):
dataset = load_dataset(['swift/stsb'])[0]
assert len(dataset) == 5749
assert list(dataset[0].keys()) == ['messages']
print(f'dataset: {dataset}')
print(f'dataset[0]: {dataset[0]}')
if __name__ == '__main__':
unittest.main()
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