[BugFix] Resolve adaptive speculative decoding conflicts for Qwen3.5 (hybrid GDN) (#23331)
Signed-off-by: EanWang211123 <wangyiheng@sangfor.com.cn> Co-authored-by: shuwenn <47200617+alphabetc1@users.noreply.github.com> Co-authored-by: shuwenn <2508695655@qq.com>
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yiheng
co-authored by
shuwenn
shuwenn
shuwenn
shuwenn
parent
16bcc4583e
commit
b9c2bf717b
@@ -1,26 +1,53 @@
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import json
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import tempfile
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import unittest
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from sglang.srt.speculative.adaptive_spec_params import AdaptiveSpeculativeParams
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from sglang.srt.speculative.adaptive_spec_params import (
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AdaptiveSpeculativeParams,
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)
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from sglang.test.ci.ci_register import register_cpu_ci
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register_cpu_ci(est_time=6, suite="base-a-test-cpu")
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class TestAdaptiveSpeculativeParams(unittest.TestCase):
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def _make_params_from_config(self, initial_steps: int, config: dict[str, object]):
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with tempfile.NamedTemporaryFile("w", suffix=".json") as f:
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json.dump(config, f)
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f.flush()
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return AdaptiveSpeculativeParams(
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initial_steps=initial_steps, cfg_path=f.name
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)
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def test_params_loads_config_path(self):
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with tempfile.NamedTemporaryFile("w", suffix=".json") as f:
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json.dump(
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{
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"candidate_steps": [1, 5],
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"ema_alpha": 0.75,
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"warmup_batches": 2,
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},
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f,
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)
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f.flush()
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params = AdaptiveSpeculativeParams(initial_steps=3, cfg_path=f.name)
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self.assertEqual(params.candidate_steps, [1, 3, 5])
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self.assertEqual(params.ema_alpha, 0.75)
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self.assertEqual(params.warmup_batches, 2)
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def test_initial_steps_added_to_candidates_when_missing(self):
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params = AdaptiveSpeculativeParams(
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initial_steps=2,
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config={"candidate_steps": [1, 3, 7]},
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)
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params = self._make_params_from_config(2, {"candidate_steps": [1, 3, 7]})
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self.assertEqual(params.candidate_steps, [1, 2, 3, 7])
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self.assertEqual(params.current_steps, 2)
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self.assertEqual(params.ema_accept_len, 1.0)
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def test_update_respects_warmup_and_interval(self):
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params = AdaptiveSpeculativeParams(
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initial_steps=3,
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config={
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params = self._make_params_from_config(
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3,
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{
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"candidate_steps": [1, 3, 7],
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"ema_alpha": 1.0,
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"warmup_batches": 1,
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@@ -38,9 +65,9 @@ class TestAdaptiveSpeculativeParams(unittest.TestCase):
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self.assertEqual(params.current_steps, 1)
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def test_empty_batches_do_not_consume_warmup_or_shift_steps(self):
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params = AdaptiveSpeculativeParams(
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initial_steps=3,
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config={
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params = self._make_params_from_config(
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3,
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{
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"candidate_steps": [1, 3, 7],
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"ema_alpha": 1.0,
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"warmup_batches": 1,
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@@ -59,9 +86,9 @@ class TestAdaptiveSpeculativeParams(unittest.TestCase):
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self.assertEqual(params.current_steps, 1)
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def test_update_scales_up_across_candidates(self):
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params = AdaptiveSpeculativeParams(
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initial_steps=1,
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config={
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params = self._make_params_from_config(
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1,
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{
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"candidate_steps": [1, 3, 7],
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"ema_alpha": 1.0,
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"warmup_batches": 0,
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@@ -77,9 +104,9 @@ class TestAdaptiveSpeculativeParams(unittest.TestCase):
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self.assertEqual(params.current_steps, 7)
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def test_update_can_scale_down_across_candidates_in_one_recompute(self):
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params = AdaptiveSpeculativeParams(
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initial_steps=7,
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config={
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params = self._make_params_from_config(
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7,
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{
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"candidate_steps": [1, 3, 7],
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"ema_alpha": 1.0,
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"warmup_batches": 0,
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@@ -91,9 +118,9 @@ class TestAdaptiveSpeculativeParams(unittest.TestCase):
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self.assertEqual(params.current_steps, 1)
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def test_exact_rise_threshold_does_not_upshift(self):
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params = AdaptiveSpeculativeParams(
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initial_steps=3,
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config={
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params = self._make_params_from_config(
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3,
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{
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"candidate_steps": [1, 3, 7],
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"ema_alpha": 1.0,
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"warmup_batches": 0,
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@@ -110,9 +137,9 @@ class TestAdaptiveSpeculativeParams(unittest.TestCase):
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self.assertEqual(params.current_steps, 7)
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def test_exact_drop_threshold_does_downshift(self):
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params = AdaptiveSpeculativeParams(
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initial_steps=3,
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config={
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params = self._make_params_from_config(
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3,
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{
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"candidate_steps": [1, 3, 7],
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"ema_alpha": 1.0,
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"warmup_batches": 0,
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@@ -127,9 +154,9 @@ class TestAdaptiveSpeculativeParams(unittest.TestCase):
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self.assertEqual(params.ema_accept_len, 0.5)
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def test_hysteresis_can_prevent_premature_upshift(self):
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params = AdaptiveSpeculativeParams(
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initial_steps=3,
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config={
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params = self._make_params_from_config(
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3,
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{
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"candidate_steps": [1, 3, 7],
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"ema_alpha": 1.0,
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"warmup_batches": 0,
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@@ -145,9 +172,9 @@ class TestAdaptiveSpeculativeParams(unittest.TestCase):
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self.assertEqual(params.current_steps, 7)
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def test_down_hysteresis_can_prevent_premature_downshift(self):
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params = AdaptiveSpeculativeParams(
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initial_steps=7,
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config={
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params = self._make_params_from_config(
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7,
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{
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"candidate_steps": [1, 3, 7],
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"ema_alpha": 1.0,
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"warmup_batches": 0,
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@@ -163,9 +190,9 @@ class TestAdaptiveSpeculativeParams(unittest.TestCase):
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self.assertEqual(params.current_steps, 3)
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def test_multi_batch_sequence_can_ramp_up_then_back_down(self):
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params = AdaptiveSpeculativeParams(
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initial_steps=3,
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config={
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params = self._make_params_from_config(
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3,
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{
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"candidate_steps": [1, 3, 7],
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"ema_alpha": 0.5,
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"warmup_batches": 0,
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