wehub-resource-sync
71 lines
2.4 KiB
Python
71 lines
2.4 KiB
Python
import os
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import torch
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from typing import Literal
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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 _prepare(infer_backend: Literal['vllm', 'transformers', 'lmdeploy']):
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from swift.infer_engine import InferRequest
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if infer_backend == 'lmdeploy':
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from swift.infer_engine import LmdeployEngine
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engine = LmdeployEngine('OpenGVLab/InternVL2_5-2B', torch_dtype=torch.float32)
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elif infer_backend == 'transformers':
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from swift.infer_engine import TransformersEngine
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engine = TransformersEngine('Qwen/Qwen2-7B-Instruct', max_batch_size=16)
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elif infer_backend == 'vllm':
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from swift.infer_engine import VllmEngine
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engine = VllmEngine('Qwen/Qwen2-7B-Instruct')
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infer_requests = [
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# InferRequest([{'role': 'user', 'content': '晚上睡不着觉怎么办'}]) for i in range(100)
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InferRequest([{
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'role': 'user',
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'content': 'hello! who are you'
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}]) for i in range(100)
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]
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return engine, infer_requests
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def test_infer(infer_backend):
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from swift.infer_engine import RequestConfig
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from swift.metrics import InferStats
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engine, infer_requests = _prepare(infer_backend=infer_backend)
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request_config = RequestConfig(temperature=0)
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infer_stats = InferStats()
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response_list = engine.infer(infer_requests, request_config=request_config, metrics=[infer_stats])
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for response in response_list[:2]:
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print(response.choices[0].message.content)
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print(infer_stats.compute())
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def test_stream(infer_backend):
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from swift.infer_engine import RequestConfig
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from swift.metrics import InferStats
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engine, infer_requests = _prepare(infer_backend=infer_backend)
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infer_stats = InferStats()
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request_config = RequestConfig(temperature=0, stream=True, logprobs=True)
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gen_list = engine.infer(infer_requests, request_config=request_config, metrics=[infer_stats])
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for response in gen_list[0]:
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if response is None:
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continue
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print(response.choices[0].delta.content, end='', flush=True)
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print()
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print(infer_stats.compute())
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gen_list = engine.infer(infer_requests, request_config=request_config, use_tqdm=True, metrics=[infer_stats])
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for response in gen_list[0]:
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pass
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print(infer_stats.compute())
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if __name__ == '__main__':
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test_infer('transformers')
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# test_stream('transformers')
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