Support return_logprob for spec v2 (overlap safe) (#19801)
Co-authored-by: Ratish1 <ratish1501@gmail.com> Co-authored-by: Ratish1 <formula733@gmail.com> Co-authored-by: hnyls2002 <lsyincs@gmail.com>
This commit is contained in:
Qiaolin Yu
co-authored by
Ratish1
Ratish1
hnyls2002
Ratish1
Ratish1
hnyls2002
parent
76ee4bb98c
commit
09a118fafe
@@ -1,6 +1,9 @@
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import unittest
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from types import SimpleNamespace
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import numpy as np
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import requests
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from sglang.srt.environ import envs
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from sglang.srt.utils import kill_process_tree
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from sglang.test.ci.ci_register import register_cuda_ci
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@@ -98,6 +101,145 @@ class TestEagleServerBase(CustomTestCase, MatchedStopMixin):
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) # 0.3333 for 60 questions; 0.234 for 1319 questions
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assert self.process.poll() is None
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def test_logprob_spec_v2_match(self):
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"""Verify spec v2 decode logprobs match prefill scoring logprobs.
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Generate tokens with spec v2, then score the same sequence via
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prefill-only (no speculation). The two sets of logprobs should be
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close, validating that spec v2 computes logprobs correctly.
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Runs two rounds with different prompts to catch state-dependent bugs.
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"""
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top_k = 5
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probe_token_ids = [1, 2, 10, 100, 1000]
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prompts = [
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"The capital of France is",
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"Explain quantum computing in simple terms:",
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]
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for round_idx, prompt in enumerate(prompts):
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with self.subTest(round=round_idx, prompt=prompt):
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gen_res = requests.post(
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self.base_url + "/generate",
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json={
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"text": prompt,
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"sampling_params": {
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"temperature": 0,
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"max_new_tokens": 32,
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"ignore_eos": True,
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},
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"return_logprob": True,
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"top_logprobs_num": top_k,
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"token_ids_logprob": probe_token_ids,
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"logprob_start_len": 0,
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},
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).json()
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decode_logprobs = gen_res["meta_info"]["output_token_logprobs"]
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decode_top_logprobs = gen_res["meta_info"]["output_top_logprobs"]
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decode_tid_logprobs = gen_res["meta_info"]["output_token_ids_logprobs"]
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input_token_ids = [
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t[1] for t in gen_res["meta_info"]["input_token_logprobs"]
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]
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output_token_ids = [t[1] for t in decode_logprobs]
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num_prompt_tokens = gen_res["meta_info"]["prompt_tokens"]
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score_res = requests.post(
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self.base_url + "/generate",
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json={
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"input_ids": input_token_ids + output_token_ids,
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"sampling_params": {
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"temperature": 0,
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"max_new_tokens": 0,
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},
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"return_logprob": True,
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"top_logprobs_num": top_k,
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"token_ids_logprob": probe_token_ids,
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"logprob_start_len": 0,
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},
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).json()
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score_logprobs = score_res["meta_info"]["input_token_logprobs"][
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num_prompt_tokens:
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]
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score_top_logprobs = score_res["meta_info"]["input_top_logprobs"][
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num_prompt_tokens:
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]
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score_tid_logprobs = score_res["meta_info"]["input_token_ids_logprobs"][
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num_prompt_tokens:
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]
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self.assertEqual(len(decode_logprobs), len(score_logprobs))
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# Check per-token logprobs
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decode_vals = np.array([t[0] for t in decode_logprobs])
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score_vals = np.array([t[0] for t in score_logprobs])
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max_diff = np.max(np.abs(decode_vals - score_vals))
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print(
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f"[round {round_idx}] prompt={prompt!r} "
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f"logprob max_diff={max_diff:.6f}"
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)
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print(f"[round {round_idx}] decode_vals[-5:]={decode_vals[-5:]}")
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print(f"[round {round_idx}] score_vals[-5:]={score_vals[-5:]}")
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self.assertLess(max_diff, 0.255)
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# Check top-k logprobs
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for pos in range(len(decode_logprobs)):
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dec_top = {t[1]: t[0] for t in decode_top_logprobs[pos]}
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scr_top = {t[1]: t[0] for t in score_top_logprobs[pos]}
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common_ids = set(dec_top.keys()) & set(scr_top.keys())
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self.assertGreater(len(common_ids), 0)
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for tid in common_ids:
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self.assertAlmostEqual(dec_top[tid], scr_top[tid], delta=0.255)
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# Check token_ids_logprob
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self.assertEqual(len(decode_tid_logprobs), len(score_tid_logprobs))
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for pos in range(len(decode_tid_logprobs)):
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dec_tid = {t[1]: t[0] for t in decode_tid_logprobs[pos]}
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scr_tid = {t[1]: t[0] for t in score_tid_logprobs[pos]}
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self.assertEqual(set(dec_tid.keys()), set(scr_tid.keys()))
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for tid in dec_tid:
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self.assertAlmostEqual(dec_tid[tid], scr_tid[tid], delta=0.255)
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def test_token_ids_logprob_ragged(self):
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"""Regression: get_token_ids_logprobs_raw crashes on ragged token_ids_logprob lists.
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Sends concurrent requests with different-length token_ids_logprob lists
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so they land in the same batch. torch.tensor() on ragged input will crash.
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"""
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import concurrent.futures
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def send(probe_ids):
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return requests.post(
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self.base_url + "/generate",
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json={
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"text": "Hello world",
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"sampling_params": {
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"temperature": 0,
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"max_new_tokens": 8,
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},
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"return_logprob": True,
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"top_logprobs_num": 3,
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"token_ids_logprob": probe_ids,
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},
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).json()
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ragged_probes = [
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[1, 2],
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[3, 4, 5],
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[6],
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[10, 20, 30, 40],
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[1, 2],
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[3, 4, 5],
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[6],
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[10, 20, 30, 40],
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]
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with concurrent.futures.ThreadPoolExecutor(max_workers=8) as pool:
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futs = [pool.submit(send, ids) for ids in ragged_probes]
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for f in concurrent.futures.as_completed(futs):
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res = f.result()
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self.assertIn("text", res, f"Server error: {res}")
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class TestEagleServerPage(TestEagleServerBase):
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other_launch_args = ["--page-size", "64"]
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