feat: Naive support Spec V2 + Constrained Decoding (#13425)

Signed-off-by: Ubospica <ubospica@gmail.com>
Co-authored-by: Liangsheng Yin <lsyincs@gmail.com>
This commit is contained in:
Yixin Dong
2025-11-27 04:31:46 -08:00
committed by GitHub
parent 25758647b1
commit 6350042696
8 changed files with 149 additions and 8 deletions

View File

@@ -1924,6 +1924,8 @@ class ScheduleBatch(ScheduleBatchDisaggregationDecodeMixin):
dimensions=self.dimensions,
dllm_block_offsets=[req.dllm_block_offset for req in self.reqs],
dllm_config=self.dllm_config,
reqs=self.reqs,
has_grammar=self.has_grammar,
)
def copy(self):
@@ -2041,3 +2043,8 @@ class ModelWorkerBatch:
# Diffusion LLM
dllm_block_offsets: Optional[List[int]] = None
dllm_config: Optional[DllmConfig] = None
# For constrained decoding
# FIXME(lsyin): remove this after fully overlap grammar
reqs: Optional[List[Req]] = None
has_grammar: bool = False

View File

@@ -1016,7 +1016,16 @@ class Scheduler(
and self.last_batch.forward_mode.is_extend()
)
if disable_overlap_for_batch:
# FIXME(lsyin): remove this grammar sync
need_grammar_sync = (
batch is not None
and batch.forward_mode.is_decode()
and batch.has_grammar
and batch.is_v2_eagle
and len(self.result_queue) > 0
)
if disable_overlap_for_batch or need_grammar_sync:
pop_and_process()
batch_result = None
@@ -1025,7 +1034,7 @@ class Scheduler(
self.result_queue.append((batch.copy(), batch_result))
if self.last_batch:
if not disable_overlap_for_batch:
if not disable_overlap_for_batch and not need_grammar_sync:
pop_and_process()
elif batch is None:
# When the server is idle, do self-check and re-init some states

View File

@@ -395,10 +395,16 @@ class SchedulerOutputProcessorMixin:
logits_output.hidden_states[i].cpu().clone().tolist()
)
if req.grammar is not None and batch.spec_algorithm.is_none():
if req.grammar is not None:
# FIXME: this try-except block is for handling unexpected xgrammar issue.
try:
req.grammar.accept_token(next_token_id)
if batch.spec_algorithm.is_none():
# Normal decode: single token
req.grammar.accept_token(next_token_id)
elif batch.is_v2_eagle:
# Speculative decode: next_token_id is a list of accepted tokens
for token_id in next_token_id:
req.grammar.accept_token(token_id)
except ValueError as e:
# Grammar accept_token can raise ValueError if the token is not in the grammar.
# This can happen if the grammar is not set correctly or the token is invalid.

View File

@@ -256,6 +256,7 @@ class EagleVerifyInputV2Mixin:
self: EagleVerifyInput,
batch: ModelWorkerBatch,
logits_output: LogitsProcessorOutput,
vocab_mask: torch.Tensor = None,
):
"""
Verify and find accepted tokens based on logits output and batch
@@ -276,6 +277,13 @@ class EagleVerifyInputV2Mixin:
next_token_logits = logits_output.next_token_logits
device = batch.input_ids.device
# Apply grammar mask if provided
if vocab_mask is not None:
assert self.grammar is not None
self.grammar.apply_vocab_mask(
logits=next_token_logits, vocab_mask=vocab_mask
)
candidates = self.draft_token.reshape(bs, self.draft_token_num)
predict_shape = list(next_token_logits.shape)[:-1]
predict = torch.zeros(predict_shape, dtype=torch.int32, device=device).flatten()

View File

@@ -36,6 +36,7 @@ from sglang.srt.speculative.spec_info import SpeculativeAlgorithm
from sglang.srt.speculative.spec_utils import (
detect_nan,
draft_tp_context,
generate_token_bitmask,
load_token_map,
)
from sglang.srt.utils.common import (
@@ -667,7 +668,15 @@ class EAGLEWorkerV2(BaseSpecWorker):
),
)
# Run target verify batch in the main compute stream
# Prepare grammar data on CPU if needed
if batch.has_grammar:
retrieve_next_token_cpu = verify_input.retrive_next_token.cpu()
retrieve_next_sibling_cpu = verify_input.retrive_next_sibling.cpu()
draft_tokens_cpu = verify_input.draft_token.view(
verify_input.retrive_next_token.shape
).cpu()
# Run target verify batch in the main compute stream (GPU compute)
forward_batch_output = self.target_worker.forward_batch_generation(
model_worker_batch=None,
forward_batch=verify_forward_batch,
@@ -676,6 +685,26 @@ class EAGLEWorkerV2(BaseSpecWorker):
)
logits_output = forward_batch_output.logits_output
# Generate vocab mask for constrained decoding
vocab_mask = None
if batch.has_grammar:
# Generate the logit mask for structured output.
vocab_mask = generate_token_bitmask(
batch.reqs,
verify_input,
retrieve_next_token_cpu,
retrieve_next_sibling_cpu,
draft_tokens_cpu,
batch.sampling_info.vocab_size,
)
if vocab_mask is not None:
assert verify_input.grammar is not None
vocab_mask = vocab_mask.to(verify_input.retrive_next_token.device)
# NOTE: otherwise, this vocab mask will be the one from the previous extend stage
# and will be applied to produce wrong results
batch.sampling_info.vocab_mask = None
# Sample
if self.enable_nan_detection:
detect_nan(logits_output)
@@ -683,7 +712,7 @@ class EAGLEWorkerV2(BaseSpecWorker):
predict,
accept_length,
accept_index,
) = verify_input.sample(batch, logits_output)
) = verify_input.sample(batch, logits_output, vocab_mask)
new_seq_lens = batch.seq_lens + accept_length
verify_done = torch.get_device_module(self.device).Event()
verify_done.record()

View File

@@ -24,7 +24,10 @@ class TestJSONConstrainedMixin:
response = requests.post(
self.base_url + "/generate",
json={
"text": "The capital of France is",
"text": (
"Introduce the capital of France. Return in a JSON format. The JSON Schema is: "
+ json.dumps(json_schema)
),
"sampling_params": {
"temperature": 0 if n == 1 else 0.5,
"max_new_tokens": 128,
@@ -69,7 +72,8 @@ class TestJSONConstrainedMixin:
{"role": "system", "content": "You are a helpful AI assistant"},
{
"role": "user",
"content": "Introduce the capital of France. Return in a JSON format.",
"content": "Introduce the capital of France. Return in a JSON format. "
"The JSON Schema is: " + json.dumps(self.json_schema),
},
],
temperature=0,

View File

@@ -7,6 +7,7 @@ from sglang.test.ci.ci_utils import TestFile, run_unittest_files
# NOTE: please sort the test cases alphabetically by the test file name
suites = {
"per-commit-1-gpu": [
TestFile("test_eagle_constrained_decoding.py", 100),
TestFile("debug_utils/test_tensor_dump_forward_hook.py", 15),
TestFile("hicache/test_hicache_storage.py", 127),
TestFile("hicache/test_hicache_variants.py", 393),

View File

@@ -0,0 +1,77 @@
import unittest
from sglang.srt.environ import envs
from sglang.srt.utils import kill_process_tree
from sglang.test.kits.json_constrained_kit import TestJSONConstrainedMixin
from sglang.test.kits.regex_constrained_kit import TestRegexConstrainedMixin
from sglang.test.test_utils import (
DEFAULT_EAGLE_DRAFT_MODEL_FOR_TEST,
DEFAULT_EAGLE_TARGET_MODEL_FOR_TEST,
DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
DEFAULT_URL_FOR_TEST,
CustomTestCase,
popen_launch_server,
)
class TestEagleConstrainedDecoding(
CustomTestCase, TestRegexConstrainedMixin, TestJSONConstrainedMixin
):
max_running_requests = 64
attention_backend = "triton"
spec_steps = 5
spec_topk = 1
spec_draft_tokens = 6
page_size = 1
other_launch_args = []
model = DEFAULT_EAGLE_TARGET_MODEL_FOR_TEST
draft_model = DEFAULT_EAGLE_DRAFT_MODEL_FOR_TEST
grammar_backend = "xgrammar"
eagle_v2 = False
@classmethod
def setUpClass(cls):
cls.base_url = DEFAULT_URL_FOR_TEST
launch_args = [
"--trust-remote-code",
"--attention-backend",
cls.attention_backend,
"--speculative-algorithm",
"EAGLE",
"--speculative-draft-model",
cls.draft_model,
"--speculative-num-steps",
cls.spec_steps,
"--speculative-eagle-topk",
cls.spec_topk,
"--speculative-num-draft-tokens",
cls.spec_draft_tokens,
"--page-size",
str(cls.page_size),
"--mem-fraction-static",
"0.75",
"--max-running-requests",
str(cls.max_running_requests),
"--grammar-backend",
cls.grammar_backend,
]
launch_args.extend(cls.other_launch_args)
with envs.SGLANG_ENABLE_SPEC_V2.override(cls.eagle_v2):
cls.process = popen_launch_server(
cls.model,
cls.base_url,
timeout=DEFAULT_TIMEOUT_FOR_SERVER_LAUNCH,
other_args=launch_args,
)
@classmethod
def tearDownClass(cls):
kill_process_tree(cls.process.pid)
class TestEagleConstrainedDecodingV2(TestEagleConstrainedDecoding):
eagle_v2 = True
if __name__ == "__main__":
unittest.main()