895e56097c
Co-authored-by: cy <chenyang08056032@163.com> Co-authored-by: Cherry_ming <136634645@qq.com>
112 lines
3.5 KiB
Python
112 lines
3.5 KiB
Python
import json
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import random
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import unittest
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from concurrent.futures import ThreadPoolExecutor
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import requests
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from sglang.srt.utils import kill_process_tree
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from sglang.test.ascend.test_ascend_utils import LLAMA_3_2_1B_INSTRUCT_WEIGHTS_PATH
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from sglang.test.ci.ci_register import register_npu_ci
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from sglang.test.test_utils import (
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DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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DEFAULT_URL_FOR_TEST,
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CustomTestCase,
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popen_launch_server,
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)
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register_npu_ci(est_time=400, suite="nightly-1-npu-a3", nightly=True)
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class TestPenalty(CustomTestCase):
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"""Testcase：Verify successful processing of inference requests with three specific mechanisms(frequency_penalty, presence_penalty, min_new_tokens).
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[Test Category] Interface
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[Test Target] /generate
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"""
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@classmethod
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def setUpClass(cls):
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cls.model = LLAMA_3_2_1B_INSTRUCT_WEIGHTS_PATH
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other_args = [
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"--attention-backend",
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"ascend",
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"--disable-cuda-graph",
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]
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cls.base_url = DEFAULT_URL_FOR_TEST
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cls.process = popen_launch_server(
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cls.model,
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cls.base_url,
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timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
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other_args=other_args,
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)
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@classmethod
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def tearDownClass(cls):
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kill_process_tree(cls.process.pid)
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def run_decode(self, sampling_params):
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# Send inference request with specified sampling/penalty parameters.
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return_logprob = True
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top_logprobs_num = 5
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return_text = True
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n = 1
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response = requests.post(
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self.base_url + "/generate",
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json={
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# prompt that is supposed to generate < 32 tokens
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"text": "<|start_header_id|>user<|end_header_id|>\n\nWhat is the answer for 1 + 1 = ?<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
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"sampling_params": {
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"max_new_tokens": 48,
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"n": n,
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**sampling_params,
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},
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"return_logprob": return_logprob,
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"top_logprobs_num": top_logprobs_num,
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"return_text_in_logprobs": return_text,
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"logprob_start_len": 0,
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},
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)
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self.assertEqual(response.status_code, 200)
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print(json.dumps(response.json()))
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print("=" * 100)
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def test_default_values(self):
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self.run_decode({})
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def test_frequency_penalty(self):
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self.run_decode({"frequency_penalty": 2})
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def test_min_new_tokens(self):
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self.run_decode({"min_new_tokens": 16})
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def test_presence_penalty(self):
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self.run_decode({"presence_penalty": 2})
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def test_penalty_mixed(self):
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args = [
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{},
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{},
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{},
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{"frequency_penalty": 2},
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{"presence_penalty": 1},
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{"min_new_tokens": 16},
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{"frequency_penalty": 0.2},
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{"presence_penalty": 0.4},
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{"min_new_tokens": 8},
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{"frequency_penalty": 0.4, "presence_penalty": 0.8},
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{"frequency_penalty": 0.4, "min_new_tokens": 12},
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{"presence_penalty": 0.8, "min_new_tokens": 12},
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{"presence_penalty": -0.3, "frequency_penalty": 1.3, "min_new_tokens": 32},
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{"presence_penalty": 0.3, "frequency_penalty": -1.3, "min_new_tokens": 32},
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]
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random.shuffle(args * 5)
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with ThreadPoolExecutor(8) as executor:
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list(executor.map(self.run_decode, args))
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if __name__ == "__main__":
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unittest.main(verbosity=3)
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