Skip to content

[Misc] Clean up MiniCPM-V/O code #15337

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 8 commits into from
Mar 25, 2025
Merged

[Misc] Clean up MiniCPM-V/O code #15337

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
8 commits
Select commit Hold shift + click to select a range
1dfc902
[Misc] Clean up MiniCPM-V/O code
DarkLight1337 Mar 22, 2025
352c3bc
Fixes
DarkLight1337 Mar 24, 2025
aabed82
Merge branch 'main' into minicpm-cleanup
DarkLight1337 Mar 24, 2025
7f0307a
Fix embeds
DarkLight1337 Mar 24, 2025
1c45aa8
Update
DarkLight1337 Mar 24, 2025
dd999b3
Clean
DarkLight1337 Mar 24, 2025
289619c
Update tests
DarkLight1337 Mar 24, 2025
4789620
Fix OOM
DarkLight1337 Mar 25, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
1 change: 1 addition & 0 deletions examples/offline_inference/vision_language.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -361,6 +361,7 @@ def run_llava_next_video(questions: list[str],
engine_args = EngineArgs(
model="llava-hf/LLaVA-NeXT-Video-7B-hf",
max_model_len=8192,
max_num_seqs=2,
disable_mm_preprocessor_cache=args.disable_mm_preprocessor_cache,
)

Expand Down
65 changes: 45 additions & 20 deletions tests/models/decoder_only/vision_language/test_models.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -163,24 +163,24 @@
marks=[pytest.mark.core_model, pytest.mark.cpu_model],
),
#### Extended model tests
# "aria": VLMTestInfo(
# models=["rhymes-ai/Aria"],
# test_type=(VLMTestType.IMAGE, VLMTestType.MULTI_IMAGE),
# prompt_formatter=lambda img_prompt: f"<|im_start|>user\n{img_prompt}<|im_end|>\n<|im_start|>assistant\n ", # noqa: E501
# img_idx_to_prompt=lambda idx: "<fim_prefix><|img|><fim_suffix>\n",
# max_model_len=4096,
# max_num_seqs=2,
# auto_cls=AutoModelForImageTextToText,
# single_image_prompts=IMAGE_ASSETS.prompts({
# "stop_sign": "<vlm_image>Please describe the image shortly.",
# "cherry_blossom": "<vlm_image>Please infer the season with reason.", # noqa: E501
# }),
# multi_image_prompt="<vlm_image><vlm_image>Describe the two images shortly.", # noqa: E501
# stop_str=["<|im_end|>"],
# image_size_factors=[(0.10, 0.15)],
# max_tokens=64,
# marks=[large_gpu_mark(min_gb=64)],
# ),
"aria": VLMTestInfo(
models=["rhymes-ai/Aria"],
test_type=(VLMTestType.IMAGE, VLMTestType.MULTI_IMAGE),
prompt_formatter=lambda img_prompt: f"<|im_start|>user\n{img_prompt}<|im_end|>\n<|im_start|>assistant\n ", # noqa: E501
img_idx_to_prompt=lambda idx: "<fim_prefix><|img|><fim_suffix>\n",
max_model_len=4096,
max_num_seqs=2,
auto_cls=AutoModelForImageTextToText,
single_image_prompts=IMAGE_ASSETS.prompts({
"stop_sign": "<vlm_image>Please describe the image shortly.",
"cherry_blossom": "<vlm_image>Please infer the season with reason.", # noqa: E501
}),
multi_image_prompt="<vlm_image><vlm_image>Describe the two images shortly.", # noqa: E501
stop_str=["<|im_end|>"],
image_size_factors=[(0.10, 0.15)],
max_tokens=64,
marks=[large_gpu_mark(min_gb=64)],
),
"blip2": VLMTestInfo(
models=["Salesforce/blip2-opt-2.7b"],
test_type=VLMTestType.IMAGE,
Expand Down Expand Up @@ -352,6 +352,7 @@
prompt_formatter=lambda vid_prompt: f"USER: {vid_prompt} ASSISTANT:",
num_video_frames=16,
max_model_len=4096,
max_num_seqs=2,
auto_cls=AutoModelForVision2Seq,
vllm_output_post_proc=model_utils.llava_video_vllm_to_hf_output,
),
Expand Down Expand Up @@ -384,25 +385,49 @@
),
"minicpmo_26": VLMTestInfo(
models=["openbmb/MiniCPM-o-2_6"],
test_type=(VLMTestType.IMAGE, VLMTestType.MULTI_IMAGE),
test_type=(VLMTestType.IMAGE),
prompt_formatter=lambda img_prompt: f"<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\n{img_prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n", # noqa: E501
img_idx_to_prompt=lambda idx: "(<image>./</image>)\n",
max_model_len=4096,
max_num_seqs=2,
get_stop_token_ids=lambda tok: tok.convert_tokens_to_ids(['<|im_end|>', '<|endoftext|>']), # noqa: E501
hf_output_post_proc=model_utils.minicpmv_trunc_hf_output,
patch_hf_runner=model_utils.minicpmo_26_patch_hf_runner,
),
"minicpmo_26_multi_image": VLMTestInfo(
models=["openbmb/MiniCPM-o-2_6"],
test_type=(VLMTestType.MULTI_IMAGE),
prompt_formatter=lambda img_prompt: f"<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\n{img_prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n", # noqa: E501
img_idx_to_prompt=lambda idx: "(<image>./</image>)\n",
max_model_len=4096,
max_num_seqs=2,
get_stop_token_ids=lambda tok: tok.convert_tokens_to_ids(['<|im_end|>', '<|endoftext|>']), # noqa: E501
hf_output_post_proc=model_utils.minicpmv_trunc_hf_output,
patch_hf_runner=model_utils.minicpmo_26_patch_hf_runner,
marks=[large_gpu_mark(min_gb=32)],
),
"minicpmv_26": VLMTestInfo(
models=["openbmb/MiniCPM-V-2_6"],
test_type=(VLMTestType.IMAGE, VLMTestType.MULTI_IMAGE),
test_type=(VLMTestType.IMAGE),
prompt_formatter=lambda img_prompt: f"<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\n{img_prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n", # noqa: E501
img_idx_to_prompt=lambda idx: "(<image>./</image>)\n",
max_model_len=4096,
max_num_seqs=2,
get_stop_token_ids=lambda tok: tok.convert_tokens_to_ids(['<|im_end|>', '<|endoftext|>']), # noqa: E501
hf_output_post_proc=model_utils.minicpmv_trunc_hf_output,
patch_hf_runner=model_utils.minicpmv_26_patch_hf_runner,
),
"minicpmv_26_multi_image": VLMTestInfo(
models=["openbmb/MiniCPM-V-2_6"],
test_type=(VLMTestType.MULTI_IMAGE),
prompt_formatter=lambda img_prompt: f"<|begin_of_text|><|start_header_id|>user<|end_header_id|>\n\n{img_prompt}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n", # noqa: E501
img_idx_to_prompt=lambda idx: "(<image>./</image>)\n",
max_model_len=4096,
max_num_seqs=2,
get_stop_token_ids=lambda tok: tok.convert_tokens_to_ids(['<|im_end|>', '<|endoftext|>']), # noqa: E501
hf_output_post_proc=model_utils.minicpmv_trunc_hf_output,
patch_hf_runner=model_utils.minicpmv_26_patch_hf_runner,
marks=[large_gpu_mark(min_gb=32)],
),
"molmo": VLMTestInfo(
models=["allenai/Molmo-7B-D-0924"],
Expand Down
90 changes: 41 additions & 49 deletions tests/models/multimodal/processing/test_common.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,6 +1,5 @@
# SPDX-License-Identifier: Apache-2.0

import copy
from functools import partial
from typing import Optional, Union

Expand Down Expand Up @@ -29,7 +28,7 @@ def _test_processing_correctness(
hit_rate: float,
num_batches: int,
simplify_rate: float,
ignore_mm_keys: Optional[list[str]] = None,
ignore_mm_keys: Optional[set[str]] = None,
):
model_info = HF_EXAMPLE_MODELS.find_hf_info(model_id)
model_info.check_available_online(on_fail="skip")
Expand Down Expand Up @@ -145,7 +144,7 @@ def _test_processing_correctness_hf(
baseline_processor: BaseMultiModalProcessor,
cached_processor: BaseMultiModalProcessor,
batch_idx: int,
ignore_mm_keys: Optional[list[str]] = None,
ignore_mm_keys: Optional[set[str]] = None,
):
if model_config.hf_config.model_type in ("mllama", "whisper", "ultravox"):
# For some multimodal models, tokenizer will always add bos_token
Expand All @@ -167,35 +166,38 @@ def _test_processing_correctness_hf(
hf_processor_mm_kwargs={},
)

assert _inputs_equal(
_assert_inputs_equal(
baseline_result,
cached_result,
ignore_mm_keys,
), f"Failed ({batch_idx=}, {prompt=}, {mm_data=})"
ignore_mm_keys=ignore_mm_keys,
msg=f"Failed ({batch_idx=}, {prompt=}, {mm_data=})",
)

baseline_tokenized_result = baseline_processor.apply(
token_prompt,
mm_data=mm_data,
hf_processor_mm_kwargs={},
)

assert _inputs_equal(
_assert_inputs_equal(
baseline_result,
baseline_tokenized_result,
ignore_mm_keys,
), f"Failed ({batch_idx=}, {prompt=}, {mm_data=})"
ignore_mm_keys=ignore_mm_keys,
msg=f"Failed ({batch_idx=}, {prompt=}, {mm_data=})",
)

cached_tokenized_result = cached_processor.apply(
token_prompt,
mm_data=mm_data,
hf_processor_mm_kwargs={},
)

assert _inputs_equal(
_assert_inputs_equal(
cached_result,
cached_tokenized_result,
ignore_mm_keys,
), f"Failed ({batch_idx=}, {prompt=}, {mm_data=})"
ignore_mm_keys=ignore_mm_keys,
msg=f"Failed ({batch_idx=}, {prompt=}, {mm_data=})",
)


def _test_processing_correctness_mistral(
Expand All @@ -206,7 +208,7 @@ def _test_processing_correctness_mistral(
baseline_processor: BaseMultiModalProcessor,
cached_processor: BaseMultiModalProcessor,
batch_idx: int,
ignore_mm_keys: Optional[list[str]] = None,
ignore_mm_keys: Optional[set[str]] = None,
):
images = mm_data.get("image", [])
if not isinstance(images, list):
Expand All @@ -233,11 +235,12 @@ def _test_processing_correctness_mistral(
hf_processor_mm_kwargs={},
)

assert _inputs_equal(
_assert_inputs_equal(
baseline_tokenized_result,
cached_tokenized_result,
ignore_mm_keys,
), f"Failed ({batch_idx=}, {prompt=}, {mm_data=})"
ignore_mm_keys=ignore_mm_keys,
msg=f"Failed ({batch_idx=}, {prompt=}, {mm_data=})",
)


# yapf: disable
Expand All @@ -261,6 +264,7 @@ def _test_processing_correctness_mistral(
"TIGER-Lab/Mantis-8B-siglip-llama3",
"mistralai/Pixtral-12B-2409",
"mistral-community/pixtral-12b",
"openbmb/MiniCPM-Llama3-V-2_5",
Copy link
Member Author

@DarkLight1337 DarkLight1337 Mar 22, 2025 •
edited
Loading

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Need this to test the else branch in _base_call_hf_processor

"openbmb/MiniCPM-o-2_6",
"openbmb/MiniCPM-V-2_6",
"allenai/Molmo-7B-D-0924",
Expand Down Expand Up @@ -290,7 +294,7 @@ def test_processing_correctness(
# In Ultravox, the audio_features can be different depending on padding
# The slight difference should not be a problem though, since
# attention_mask lets us ignore the difference.
ignore_mm_keys = ['audio_features']
ignore_mm_keys = {"audio_features"}

_test_processing_correctness(
model_id,
Expand Down Expand Up @@ -328,38 +332,26 @@ def test_processing_correctness_phi3v(
)


def _inputs_equal(
def _assert_inputs_equal(
a: MultiModalInputs,
b: MultiModalInputs,
ignore_mm_keys: Optional[list[str]] = None,
*,
ignore_mm_keys: Optional[set[str]] = None,
msg: str = "",
):
return _drop_mm_kwargs_keys(a, ignore_mm_keys) == _drop_mm_kwargs_keys(
b, ignore_mm_keys)


def _drop_mm_kwargs_keys(
result: MultiModalInputs,
ignore_mm_keys: Optional[list[str]] = None,
) -> MultiModalInputs:
"""Drop specified keys from result['mm_kwargs'].

This is mainly to avoid doing exact match of audio_features in ultravox.

Args:
result: Result to drop keys from
ignore_mm_keys: List of keys to ignore, e.g. ['audio_features']
"""
if not ignore_mm_keys:
return result

if 'mm_kwargs' in result:
result = copy.deepcopy(result)
mm_kwargs = result['mm_kwargs']
for key in ignore_mm_keys:
mm_kwargs.pop(key, None)
for items in mm_kwargs._items_by_modality.values():
for item in items:
for key in ignore_mm_keys:
item.pop(key, None)

return result
if ignore_mm_keys is None:
ignore_mm_keys = set()

if msg is None:
assert "mm_kwargs" in a and "mm_kwargs" in b
else:
assert "mm_kwargs" in a and "mm_kwargs" in b, msg

for key in ignore_mm_keys:
a["mm_kwargs"].pop(key, None)
b["mm_kwargs"].pop(key, None)

if msg is None:
assert a == b
else:
assert a == b, msg
Copy link
Member Author

@DarkLight1337 DarkLight1337 Mar 22, 2025 •
edited
Loading

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

These changes are to let pytest show the non-matching items in more detail

2 changes: 0 additions & 2 deletions vllm/model_executor/models/gemma3_mm.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -295,8 +295,6 @@ def _call_hf_processor(

# HF processor pops the `num_crops` kwarg, which is needed by vLLM
if (images := mm_data.get("images")) is not None:
assert isinstance(images, list)

Comment on lines -298 to -299
Copy link
Member Author

@DarkLight1337 DarkLight1337 Mar 22, 2025

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Unnecessary check since the data is parsed in the next line

parsed_images = (self._get_data_parser().parse_mm_data({
"image":
images
Expand Down
Loading