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vllm-omni/tests/diffusion/models/hunyuan_image3/test_prompt_utils.py
T
3f63aaf982 [Feature] HunyuanImage-3.0 IT2I: multi-image input + prompt API cleanup (#3444)
Signed-off-by: TaffyOfficial <2324465096@qq.com>
Signed-off-by: TaffyOfficial <wu15922848573@outlook.com>
Signed-off-by: skf1999 <13234016272@163.com>
Signed-off-by: zuiho <2324465096@qq.com>
Signed-off-by: Claude Code <noreply@anthropic.com>
Signed-off-by: zuiho <wu15922848573@outlook.com>
Signed-off-by: TaffyOfficial <2587297563@qq.com>
Co-authored-by: TaffyOfficial <2324465096@qq.com>
Co-authored-by: TaffyOfficial <wu15922848573@outlook.com>
Co-authored-by: skf1999 <13234016272@163.com>
2026-05-14 16:58:40 +08:00

282 lines
10 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from __future__ import annotations
import ast
import os
import pathlib
import pytest
from vllm_omni.diffusion.models.hunyuan_image3.prompt_utils import (
_TASK_PRESETS,
HUNYUAN_IMAGE3_SPECIAL_TOKEN_IDS,
available_bot_tasks,
available_tasks,
build_prompt,
build_prompt_tokens,
resolve_stop_token_ids,
)
pytestmark = [pytest.mark.core_model, pytest.mark.cpu]
class FakeTokenizer:
SPECIAL = {
"<|startoftext|>": 1,
"<img>": 2,
"<think>": 3,
"<recaption>": 4,
"<|endoftext|>": 5,
"</recaption>": 6,
"</answer>": 7,
"<boi>": 8,
"</think>": 9,
**{f"<img_ratio_{i}>": 1000 + i for i in range(33)},
}
def __init__(self) -> None:
self.encode_calls: list[str] = []
self.eos_token_id = self.SPECIAL["<|endoftext|>"]
def convert_tokens_to_ids(self, tok: str) -> int:
return self.SPECIAL.get(tok, 0)
def encode(self, text: str, add_special_tokens: bool = False) -> list[int]:
self.encode_calls.append(text)
return list(range(100, 100 + len(text)))
def test_available_tasks_covers_all_modalities():
assert set(available_tasks()) == {"t2t", "i2t", "it2i", "t2i"}
def test_available_bot_tasks_covers_all_modes():
assert set(available_bot_tasks()) == {None, "think", "recaption", "think_recaption", "vanilla"}
def test_legacy_task_presets_still_available():
assert {
"it2i_think",
"it2i_recaption",
"it2i_think_recaption",
"t2i_think",
"t2i_recaption",
"t2i_vanilla",
} <= set(_TASK_PRESETS)
def test_legacy_base_task_omitted_bot_task_keeps_plain_mode():
prompt = build_prompt("HELLO", task="i2t")
assert prompt.endswith("Assistant: ")
assert not prompt.endswith("<think>")
result = build_prompt_tokens("hi", FakeTokenizer(), task="i2t")
assert result.system_prompt_type == "en_unified"
assert result.token_ids[-1] not in {
FakeTokenizer.SPECIAL["<think>"],
FakeTokenizer.SPECIAL["<recaption>"],
}
def test_legacy_composite_task_with_none_bot_task_keeps_encoded_mode():
prompt = build_prompt("HELLO", task="it2i_think", bot_task=None)
assert prompt.endswith("Assistant: <think>")
result = build_prompt_tokens("hi", FakeTokenizer(), task="it2i_recaption", bot_task=None)
assert result.token_ids[-1] == FakeTokenizer.SPECIAL["<recaption>"]
def test_default_prompt_still_uses_it2i_think_mode():
prompt = build_prompt("HELLO")
assert prompt.endswith("Assistant: <think>")
result = build_prompt_tokens("hi", FakeTokenizer())
assert result.system_prompt_type == "en_unified"
assert result.token_ids[-1] == FakeTokenizer.SPECIAL["<think>"]
def test_resolve_stop_token_ids_image_tasks_stop_on_ratio_range():
"""Image-output tasks stop on any ``<img_ratio_*>`` token.
Mirrors upstream ``modeling_hunyuan_image_3.py::generate_image``
(line 3289-3303): when ``need_ratio`` is true,
``final_stop_tokens = list(range(start_ratio, end_ratio + 1)) +
ratio_token_other_slices``. AR stops AT the ratio token sampled
after ``<img_size_*>``; the bridge then strips the trailing ratio
token before passing the cot to DiT.
"""
tok = FakeTokenizer()
start = HUNYUAN_IMAGE3_SPECIAL_TOKEN_IDS["<img_ratio_0>"]
end = HUNYUAN_IMAGE3_SPECIAL_TOKEN_IDS["<img_ratio_32>"]
other_start = HUNYUAN_IMAGE3_SPECIAL_TOKEN_IDS["<img_ratio_33>"]
other_end = HUNYUAN_IMAGE3_SPECIAL_TOKEN_IDS["<img_ratio_36>"]
expected = list(range(start, end + 1)) + list(range(other_start, other_end + 1))
# Image-output: t2i / it2i stop on the full ratio token range.
for bot in ("think", "recaption", "think_recaption", "vanilla"):
assert resolve_stop_token_ids(task="t2i", bot_task=bot, tokenizer=tok) == expected
assert resolve_stop_token_ids(task="it2i", bot_task=bot, tokenizer=tok) == expected
# Text-output: i2t / t2t comprehension stops on <answer> (response sits inside).
answer_id = HUNYUAN_IMAGE3_SPECIAL_TOKEN_IDS["<answer>"]
assert resolve_stop_token_ids(task="i2t", bot_task=None, tokenizer=tok) == [answer_id]
assert resolve_stop_token_ids(task="t2t", bot_task=None, tokenizer=tok) == [answer_id]
@pytest.mark.parametrize(
"task,bot_task",
[
("t2t", None),
("i2t", None),
("it2i", "think"),
("it2i", "recaption"),
("it2i", "think_recaption"),
("t2i", "think"),
("t2i", "recaption"),
("t2i", "think_recaption"),
],
)
def test_build_prompt_string_structure_chat_template(task: str, bot_task: str | None):
s = build_prompt("HELLO", task=task, bot_task=bot_task)
assert s.startswith("<|startoftext|>")
assert "User: " in s
assert "Assistant: " in s
assert s.index("User: ") < s.index("HELLO") < s.index("Assistant: ")
if task in ("i2t", "it2i"):
assert s.index("User: ") < s.index("<img>") < s.index("HELLO")
else:
assert "<img>" not in s
if bot_task in ("think", "think_recaption"):
assert s.endswith("Assistant: <think>")
elif bot_task == "recaption":
assert s.endswith("Assistant: <recaption>")
elif bot_task is None:
assert s.endswith("Assistant: ")
def test_build_prompt_vanilla_uses_pretrain_template():
s = build_prompt("HELLO", task="t2i", bot_task="vanilla")
assert s.startswith("<|startoftext|>")
assert "User: " not in s
assert "Assistant: " not in s
assert s.endswith("HELLO")
def test_build_prompt_vanilla_rejects_non_t2i_task():
with pytest.raises(ValueError, match="bot_task='vanilla'"):
build_prompt("x", task="it2i", bot_task="vanilla")
with pytest.raises(ValueError, match="bot_task='vanilla'"):
build_prompt_tokens("x", FakeTokenizer(), task="i2t", bot_task="vanilla")
def test_build_prompt_unknown_task_raises():
with pytest.raises(ValueError, match="Unknown task"):
build_prompt("x", task="bogus")
with pytest.raises(ValueError, match="Unknown task"):
build_prompt_tokens("x", FakeTokenizer(), task="bogus")
def test_build_prompt_unknown_bot_task_raises():
with pytest.raises(ValueError, match="Unknown bot_task"):
build_prompt("x", task="t2i", bot_task="bogus")
with pytest.raises(ValueError, match="Unknown bot_task"):
build_prompt_tokens("x", FakeTokenizer(), task="t2i", bot_task="bogus")
def test_build_prompt_tokens_segments_each_boundary():
tok = FakeTokenizer()
build_prompt_tokens("写诗。", tok, task="i2t", bot_task=None)
assert "User: " in tok.encode_calls
assert "写诗。" in tok.encode_calls
assert "\n\nAssistant: " in tok.encode_calls
for call in tok.encode_calls:
if call != "写诗。":
assert "写诗。" not in call
def test_build_prompt_tokens_image_placeholder_present_for_image_tasks():
tok = FakeTokenizer()
result = build_prompt_tokens("hi", tok, task="i2t", bot_task=None)
ids = result.token_ids
assert ids[0] == FakeTokenizer.SPECIAL["<|startoftext|>"]
assert FakeTokenizer.SPECIAL["<img>"] in ids
def test_build_prompt_tokens_no_image_for_text_only_tasks():
tok = FakeTokenizer()
result = build_prompt_tokens("hi", tok, task="t2t", bot_task=None)
ids = result.token_ids
assert FakeTokenizer.SPECIAL["<img>"] not in ids
@pytest.mark.parametrize(
"task,bot_task,trigger_id",
[
("it2i", "think", FakeTokenizer.SPECIAL["<think>"]),
("t2i", "think", FakeTokenizer.SPECIAL["<think>"]),
("t2i", "think_recaption", FakeTokenizer.SPECIAL["<think>"]),
("it2i", "recaption", FakeTokenizer.SPECIAL["<recaption>"]),
("t2i", "recaption", FakeTokenizer.SPECIAL["<recaption>"]),
("it2i_think", None, FakeTokenizer.SPECIAL["<think>"]),
("it2i_recaption", None, FakeTokenizer.SPECIAL["<recaption>"]),
],
)
def test_build_prompt_tokens_trigger_is_last_token(task: str, bot_task: str | None, trigger_id: int):
tok = FakeTokenizer()
result = build_prompt_tokens("hi", tok, task=task, bot_task=bot_task)
assert result.token_ids[-1] == trigger_id
def test_build_prompt_tokens_no_trigger_for_plain_tasks():
tok = FakeTokenizer()
result = build_prompt_tokens("hi", tok, task="t2t", bot_task=None)
assert result.token_ids[-1] not in {
FakeTokenizer.SPECIAL["<think>"],
FakeTokenizer.SPECIAL["<recaption>"],
}
def _repo_root() -> pathlib.Path:
return pathlib.Path(__file__).resolve().parents[4]
def test_end2end_routes_through_shared_prompt_utils():
end2end_path = _repo_root() / "examples" / "offline_inference" / "hunyuan_image3" / "end2end.py"
tree = ast.parse(end2end_path.read_text(encoding="utf-8"))
local_func_names = {n.name for n in ast.walk(tree) if isinstance(n, ast.FunctionDef)}
assert not (local_func_names & {"build_prompt", "build_prompt_tokens"})
imported_from_prompt_utils: set[str] = set()
for node in ast.walk(tree):
if isinstance(node, ast.ImportFrom) and node.module and node.module.endswith("hunyuan_image3.prompt_utils"):
imported_from_prompt_utils.update(alias.name for alias in node.names)
expected_imports = {"build_prompt_tokens", "resolve_stop_token_ids", "resolve_sys_type"}
assert expected_imports <= imported_from_prompt_utils
_HUNYUAN_MODEL_ID = "tencent/HunyuanImage-3.0-Instruct"
def _hf_cached(model_id: str) -> bool:
hf_home = os.environ.get("HF_HOME") or os.path.expanduser("~/.cache/huggingface")
snap_dir = os.path.join(hf_home, "hub", f"models--{model_id.replace('/', '--')}", "snapshots")
return os.path.isdir(snap_dir) and any(os.scandir(snap_dir))
@pytest.mark.skipif(not _hf_cached(_HUNYUAN_MODEL_ID), reason=f"{_HUNYUAN_MODEL_ID} tokenizer not in HF cache")
def test_segment_tokenize_diverges_from_full_string_encode():
from transformers import AutoTokenizer
tok = AutoTokenizer.from_pretrained(_HUNYUAN_MODEL_ID, trust_remote_code=True)
user_prompt = "写一首关于夜的诗。"
result = build_prompt_tokens(user_prompt, tok, task="i2t", bot_task=None)
seg_ids = result.token_ids
full_ids = tok.encode(build_prompt(user_prompt, task="i2t", bot_task=None), add_special_tokens=False)
assert seg_ids != full_ids
assert len(seg_ids) >= len(full_ids)