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[V0][V1][Core] Add outlines integration for V1, and update V0 integration. (#15975)

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Signed-off-by: Nathan Hoos <thwackyy.y@gmail.com>
This commit is contained in:
Nathan Hoos
2025-07-10 14:30:26 -05:00
committed by GitHub
parent 5e53c89a74
commit d6902ce79f
13 changed files with 804 additions and 461 deletions
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30
tests/model_executor/test_guided_processors.py
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@@ -46,20 +46,15 @@ def test_guided_logits_processors(zephyr_7B_tokenzer, sample_regex,
whitespace_pattern=None,
reasoner=None)
token_ids = zephyr_7B_tokenzer.encode(
f"Give an example IPv4 address with this regex: {sample_regex}")
tensor = torch.rand(32000)
original_tensor = torch.clone(tensor)
regex_LP(token_ids, tensor)
tensor = regex_LP([], tensor)
assert tensor.shape == original_tensor.shape
assert not torch.allclose(tensor, original_tensor)
token_ids = zephyr_7B_tokenzer.encode(
f"Give an employee profile that fits this schema: {sample_json_schema}"
)
tensor = torch.rand(32000)
original_tensor = torch.clone(tensor)
json_LP(token_ids, tensor)
tensor = json_LP([], tensor)
assert tensor.shape == original_tensor.shape
assert not torch.allclose(tensor, original_tensor)
@@ -81,8 +76,6 @@ async def test_guided_logits_processor_black_box(backend: str, is_local: bool,
seed=0,
dtype="bfloat16",
)
token_ids = zephyr_7B_tokenzer.encode(
f"Give an example IPv4 address with this regex: {sample_regex}")
regex_request = GuidedDecodingParams(regex=sample_regex, backend=backend)
regex_lp = get_local_guided_decoding_logits_processor(
@@ -92,13 +85,11 @@ async def test_guided_logits_processor_black_box(backend: str, is_local: bool,
assert regex_lp is not None
tensor = torch.rand(32000)
original_tensor = torch.clone(tensor)
tensor = regex_lp(token_ids, tensor)
# allowed tokens at state 0
tensor = regex_lp([], tensor)
assert tensor.shape == original_tensor.shape
assert not torch.allclose(tensor, original_tensor)
token_ids = zephyr_7B_tokenzer.encode(
f"Give an employee profile that fits this schema: {sample_json_schema}"
)
json_request = GuidedDecodingParams(json=sample_json_schema,
backend=backend)
json_lp = await get_guided_decoding_logits_processor(
@@ -106,7 +97,7 @@ async def test_guided_logits_processor_black_box(backend: str, is_local: bool,
assert json_lp is not None
tensor = torch.rand(32000)
original_tensor = torch.clone(tensor)
tensor = json_lp(token_ids, tensor)
tensor = json_lp([], tensor)
assert tensor.shape == original_tensor.shape
assert not torch.allclose(tensor, original_tensor)
@@ -130,7 +121,6 @@ async def test_guided_logits_processor_with_reasoning(
dtype="bfloat16",
)
token_ids = deepseek_r1_qwen_tokenizer.encode(
f"Give an example IPv4 address with this regex: {sample_regex}."
"<think>here is the thinking process")
regex_request = GuidedDecodingParams(regex=sample_regex, backend=backend)
@@ -141,14 +131,13 @@ async def test_guided_logits_processor_with_reasoning(
regex_request, deepseek_r1_qwen_tokenizer, config,
reasoning_backend)
assert regex_lp is not None
tensor = torch.rand(32000)
tensor = torch.rand(151664)
original_tensor = torch.clone(tensor)
tensor = regex_lp(token_ids, tensor)
assert tensor.shape == original_tensor.shape
assert torch.allclose(tensor, original_tensor)
token_ids = deepseek_r1_qwen_tokenizer.encode(
f"Give an employee profile that fits this schema: {sample_json_schema}."
"<think>here is the thinking process")
json_request = GuidedDecodingParams(json=sample_json_schema,
backend=backend)
@@ -158,7 +147,7 @@ async def test_guided_logits_processor_with_reasoning(
await get_guided_decoding_logits_processor(
json_request, deepseek_r1_qwen_tokenizer, config, reasoning_backend)
assert json_lp is not None
tensor = torch.rand(32000)
tensor = torch.rand(151664)
original_tensor = torch.clone(tensor)
tensor = json_lp(token_ids, tensor)
assert tensor.shape == original_tensor.shape
@@ -166,8 +155,7 @@ async def test_guided_logits_processor_with_reasoning(
# Thinking is over, so the tensor should change.
token_ids = deepseek_r1_qwen_tokenizer.encode(
f"Give an employee profile that fits this schema: {sample_json_schema}."
"<think>here is the thinking process</think> Then")
"<think>here is the thinking process</think>")
json_request = GuidedDecodingParams(json=sample_json_schema,
backend=backend)
json_lp = get_local_guided_decoding_logits_processor(
@@ -176,7 +164,7 @@ async def test_guided_logits_processor_with_reasoning(
await get_guided_decoding_logits_processor(
json_request, deepseek_r1_qwen_tokenizer, config, reasoning_backend)
assert json_lp is not None
tensor = torch.rand(32000)
tensor = torch.rand(151664)
original_tensor = torch.clone(tensor)
tensor = json_lp(token_ids, tensor)
assert tensor.shape == original_tensor.shape