vllm/tests/multimodal/test_utils.py
Peter Salas 6c0b7f548d
[Core][VLM] Add precise multi-modal placeholder tracking (#8346)
Signed-off-by: Peter Salas <peter@fixie.ai>
2024-11-01 16:21:10 -07:00

149 lines
5.1 KiB
Python

import base64
import mimetypes
from tempfile import NamedTemporaryFile
from typing import Dict, Tuple
import numpy as np
import pytest
from PIL import Image
from transformers import AutoConfig, AutoTokenizer
from vllm.multimodal.utils import (async_fetch_image, fetch_image,
repeat_and_pad_placeholder_tokens)
# Test different image extensions (JPG/PNG) and formats (gray/RGB/RGBA)
TEST_IMAGE_URLS = [
"https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg",
"https://upload.wikimedia.org/wikipedia/commons/f/fa/Grayscale_8bits_palette_sample_image.png",
"https://upload.wikimedia.org/wikipedia/commons/thumb/9/91/Venn_diagram_rgb.svg/1280px-Venn_diagram_rgb.svg.png",
"https://upload.wikimedia.org/wikipedia/commons/0/0b/RGBA_comp.png",
]
@pytest.fixture(scope="module")
def url_images() -> Dict[str, Image.Image]:
return {image_url: fetch_image(image_url) for image_url in TEST_IMAGE_URLS}
def get_supported_suffixes() -> Tuple[str, ...]:
# We should at least test the file types mentioned in GPT-4 with Vision
OPENAI_SUPPORTED_SUFFIXES = ('.png', '.jpeg', '.jpg', '.webp', '.gif')
# Additional file types that are supported by us
EXTRA_SUPPORTED_SUFFIXES = ('.bmp', '.tiff')
return OPENAI_SUPPORTED_SUFFIXES + EXTRA_SUPPORTED_SUFFIXES
def _image_equals(a: Image.Image, b: Image.Image) -> bool:
return (np.asarray(a) == np.asarray(b.convert(a.mode))).all()
@pytest.mark.asyncio
@pytest.mark.parametrize("image_url", TEST_IMAGE_URLS)
async def test_fetch_image_http(image_url: str):
image_sync = fetch_image(image_url)
image_async = await async_fetch_image(image_url)
assert _image_equals(image_sync, image_async)
@pytest.mark.asyncio
@pytest.mark.parametrize("image_url", TEST_IMAGE_URLS)
@pytest.mark.parametrize("suffix", get_supported_suffixes())
async def test_fetch_image_base64(url_images: Dict[str, Image.Image],
image_url: str, suffix: str):
url_image = url_images[image_url]
try:
mime_type = Image.MIME[Image.registered_extensions()[suffix]]
except KeyError:
try:
mime_type = mimetypes.types_map[suffix]
except KeyError:
pytest.skip('No MIME type')
with NamedTemporaryFile(suffix=suffix) as f:
try:
url_image.save(f.name)
except Exception as e:
if e.args[0] == 'cannot write mode RGBA as JPEG':
pytest.skip('Conversion not supported')
raise
base64_image = base64.b64encode(f.read()).decode("utf-8")
data_url = f"data:{mime_type};base64,{base64_image}"
data_image_sync = fetch_image(data_url)
if _image_equals(url_image, Image.open(f)):
assert _image_equals(url_image, data_image_sync)
else:
pass # Lossy format; only check that image can be opened
data_image_async = await async_fetch_image(data_url)
assert _image_equals(data_image_sync, data_image_async)
@pytest.mark.parametrize("model", ["llava-hf/llava-v1.6-mistral-7b-hf"])
def test_repeat_and_pad_placeholder_tokens(model):
config = AutoConfig.from_pretrained(model)
image_token_id = config.image_token_index
tokenizer = AutoTokenizer.from_pretrained(model)
test_cases = [
(
"<image>",
2,
"<image><image>",
[32000, 32000],
[{ "offset": 0, "length": 2 }],
),
(
"<image><image>",
2,
"<image><image><image>",
[32000, 32000, 32000],
[{ "offset": 0, "length": 2 }]),
(
"<image><image>",
[3, 2],
"<image><image><image><image><image>",
[32000, 32000, 32000, 32000, 32000],
[{ "offset": 0, "length": 3 }, { "offset": 3, "length": 2 }],
),
(
"Image:<image>Image:<image>!",
[3, 2],
"Image:<image><image><image>Image:<image><image>!",
[9833, 28747, 32000, 32000, 32000, 9833, 28747, 32000, 32000, 918],
[{ "offset": 2, "length": 3 }, { "offset": 7, "length": 2 }],
),
(
"<image>",
[3, 2],
"<image><image><image>",
[32000, 32000, 32000],
[{ "offset": 0, "length": 3 }],
),
] # yapf: disable
for (
prompt,
repeat_count,
expected_prompt,
expected_token_ids,
expected_ranges,
) in test_cases:
new_prompt, new_token_ids, ranges = repeat_and_pad_placeholder_tokens(
tokenizer=tokenizer,
prompt=prompt,
prompt_token_ids=tokenizer.encode(prompt,
add_special_tokens=False),
placeholder_token_id=image_token_id,
repeat_count=repeat_count,
)
assert new_prompt == expected_prompt
assert new_token_ids == expected_token_ids
assert ranges == expected_ranges