wehub-resource-sync
56 lines
1.7 KiB
Python
56 lines
1.7 KiB
Python
import os
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os.environ['CUDA_VISIBLE_DEVICES'] = '0'
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os.environ['ASCEND_RT_VISIBLE_DEVICES'] = '0'
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def test_engine():
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from swift.dataset import load_dataset
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from swift.infer_engine import RequestConfig, SglangEngine
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dataset = load_dataset('AI-ModelScope/alpaca-gpt4-data-zh#20')[0]
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engine = SglangEngine('Qwen/Qwen2.5-0.5B-Instruct')
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request_config = RequestConfig(max_tokens=1024)
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resp_list = engine.infer(list(dataset), request_config=request_config)
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for resp in resp_list[:5]:
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print(resp)
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resp_list = engine.infer(list(dataset), request_config=request_config)
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for resp in resp_list[:5]:
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print(resp)
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def test_engine_stream():
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from swift.dataset import load_dataset
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from swift.infer_engine import RequestConfig, SglangEngine
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dataset = load_dataset('AI-ModelScope/alpaca-gpt4-data-zh#1')[0]
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engine = SglangEngine('Qwen/Qwen2.5-0.5B-Instruct')
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request_config = RequestConfig(max_tokens=1024, stream=True)
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gen_list = engine.infer(list(dataset), request_config=request_config)
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for resp in gen_list[0]:
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if resp is None:
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continue
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print(resp.choices[0].delta.content, flush=True, end='')
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def test_infer():
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from swift import InferArguments, infer_main
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infer_main(
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InferArguments(model='Qwen/Qwen2.5-0.5B-Instruct', stream=True, infer_backend='sglang', max_new_tokens=2048))
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def test_eval():
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from swift import EvalArguments, eval_main
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eval_main(
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EvalArguments(
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model='Qwen/Qwen2-7B-Instruct',
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eval_dataset='arc_c',
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infer_backend='sglang',
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eval_backend='OpenCompass',
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))
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if __name__ == '__main__':
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test_engine()
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# test_engine_stream()
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# test_infer()
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# test_eval()
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