test_processing.py

# SPDX-License-Identifier: Apache-2.0

from contextlib import nullcontext
from types import MethodType
from typing import cast
from unittest.mock import MagicMock

import numpy as np
import pytest
from transformers import ProcessorMixin

from vllm.config import ModelConfig
from vllm.multimodal import MULTIMODAL_REGISTRY
# yapf conflicts with isort for this block
# yapf: disable
from vllm.multimodal.processing import (PlaceholderFeaturesInfo,
                                        PromptReplacement,
                                        find_mm_placeholders,
                                        find_text_matches, find_token_matches,
                                        iter_token_matches,
                                        replace_text_matches,
                                        replace_token_matches)
# yapf: enable
from vllm.multimodal.profiling import MultiModalProfiler
from vllm.transformers_utils.tokenizer import (AnyTokenizer,
                                               cached_tokenizer_from_config)
from vllm.utils import full_groupby

from .utils import random_image


# yapf: disable
@pytest.mark.parametrize(
    ("token_ids", "match_ids", "expected"),
    [
        ([], [], []),
        ([], [32000], []),
        (
            [32000, 32000, 32000],
            [32000],
            [
                { "start_idx": 0, "end_idx": 1 },
                { "start_idx": 1, "end_idx": 2 },
                { "start_idx": 2, "end_idx": 3 },
            ],
        ),
        (
            [32000, 32000, 32000],
            [32000, 32000],
            [{ "start_idx": 0, "end_idx": 2 }],
        ),
        (
            [32000, 32000, 32000],
            [32000, 32000, 32000],
            [{ "start_idx": 0, "end_idx": 3 }],
        ),
        (
            [9833, 28747, 32000, 32000, 32000, 9833, 28747, 32000, 32000, 918],
            [28747, 32000],
            [
                { "start_idx": 1, "end_idx": 3 },
                { "start_idx": 6, "end_idx": 8 },
            ],
        ),
        (
            [9833, 28747, 32000, 32000, 32000, 9833, 28747, 32000, 32000, 918],
            [28747, 32000, 32000, 32000],
            [
                { "start_idx": 1, "end_idx": 5 },
            ],
        ),
        (
            [9833, 28747, 32000, 32000, 32000, 9833, 28747, 32000, 32000, 918],
            [28747, 0, 32000],
            [],
        ),
    ],
)
# yapf: enable
def test_iter_token_matches(token_ids, match_ids, expected):
    result = list(iter_token_matches(token_ids, match_ids))

    # Manually constructed results
    assert [item._asdict() for item in result] == expected

    # Invariants
    match_lens = [end - start for start, end in result]
    print("match_lens:", match_lens)  # Only displayed on error
    assert all(match_len == len(match_ids) for match_len in match_lens)


# yapf: disable
@pytest.mark.parametrize(
    ("prompt", "target_by_key", "expected_by_key"),
    [
        (
            [],
            {
                "pattern_1": [],
                "pattern_2": [32000],
            },
            {
                "pattern_1": [],
                "pattern_2": [],
            }
        ),
        (
            [32000, 32000, 32000, 32000],
            {
                "pattern_1": [32000],
                "pattern_2": [32000, 32000],
                "pattern_3": [32000, 32000, 32000],
            },
            {
                "pattern_1": [
                    { "start_idx": 0, "end_idx": 1 },
                    { "start_idx": 1, "end_idx": 2 },
                    { "start_idx": 2, "end_idx": 3 },
                    { "start_idx": 3, "end_idx": 4 },
                ],
                "pattern_2": [
                    { "start_idx": 0, "end_idx": 2 },
                    { "start_idx": 2, "end_idx": 4 },
                ],
                "pattern_3": [
                    { "start_idx": 0, "end_idx": 3 },
                ],
            },
        ),
        (
            [9833, 28747, 32000, 32000, 32000, 9833, 28747, 32000, 32000, 918],
            {
                "pattern_1": [28747, 32000],
                "pattern_2": [28747, 32000, 32000, 32000],
                "pattern_3": [28747, 0, 32000],
            },
            {
                "pattern_1": [
                    { "start_idx": 1, "end_idx": 3 },
                    { "start_idx": 6, "end_idx": 8 },
                ],
                "pattern_2": [
                    { "start_idx": 1, "end_idx": 5 },
                ],
                "pattern_3": [],
            },
        ),
    ],
)
# yapf: enable
def test_find_token_matches(prompt, target_by_key, expected_by_key):
    # Should not be used since there is nothing to convert to token IDs
    mock_tokenizer = cast(AnyTokenizer, object())

    prompt_repls = [
        PromptReplacement(key, target, []).bind(mock_tokenizer)
        for key, target in target_by_key.items()
    ]
    result = find_token_matches(prompt, prompt_repls)

    # Only displayed on error
    print("result:", result)

    # Manually constructed results
    result_groups = dict(full_groupby(result, key=lambda x: x.modality))
    assert {
        key: [
            dict(start_idx=item.start_idx, end_idx=item.end_idx)
            for item in result_groups.get(key, [])
        ]
        for key in expected_by_key
    } == expected_by_key


# yapf: disable
@pytest.mark.parametrize(
    ("prompt", "target_by_key", "expected_by_key"),
    [
        # Detokenized test cases of `test_find_token_matches`
        # using the vocab of llava-hf/llava-v1.6-mistral-7b-hf
        (
            "",
            {
                "pattern_1": "",
                "pattern_2": "<image>",
            },
            {
                "pattern_1": [{ "start_idx": 0, "end_idx": 0 }],
                "pattern_2": [],
            }
        ),
        (
            "<image><image><image><image>",
            {
                "pattern_1": "<image>",
                "pattern_2": "<image><image>",
                "pattern_3": "<image><image><image>",
            },
            {
                "pattern_1": [
                    { "start_idx": 0, "end_idx": 7 },
                    { "start_idx": 7, "end_idx": 14 },
                    { "start_idx": 14, "end_idx": 21 },
                    { "start_idx": 21, "end_idx": 28 },
                ],
                "pattern_2": [
                    { "start_idx": 0, "end_idx": 14 },
                    { "start_idx": 14, "end_idx": 28 },
                ],
                "pattern_3": [
                    { "start_idx": 0, "end_idx": 21 },
                ],
            },
        ),
        (
            "Image:<image><image><image>Image:<image><image>!",
            {
                "pattern_1": "Image:<image>",
                "pattern_2": "Image:<image><image><image>",
                "pattern_3": "Image:<unk><image>",
            },
            {
                "pattern_1": [
                    { "start_idx": 0, "end_idx": 13 },
                    { "start_idx": 27, "end_idx": 40 },
                ],
                "pattern_2": [
                    { "start_idx": 0, "end_idx": 27 },
                ],
                "pattern_3": [],
            },
        ),
        # Test regex escape
        (
            "<|image|><image><|image|><image>",
            {
                "pattern_1": "<|image|>",
                "pattern_2": "<|image|><image>",
                "pattern_3": "<|image|><image><|image|>",
            },
            {
                "pattern_1": [
                    { "start_idx": 0, "end_idx": 9 },
                    { "start_idx": 16, "end_idx": 25 },
                ],
                "pattern_2": [
                    { "start_idx": 0, "end_idx": 16 },
                    { "start_idx": 16, "end_idx": 32 },
                ],
                "pattern_3": [
                    { "start_idx": 0, "end_idx": 25 },
                ],
            },
        ),
    ],
)
# yapf: enable
def test_find_text_matches(prompt, target_by_key, expected_by_key):
    # Should not be used since there is nothing to convert to text
    mock_tokenizer = cast(AnyTokenizer, object())

    prompt_repls = [
        PromptReplacement(key, target, []).bind(mock_tokenizer)
        for key, target in target_by_key.items()
    ]
    result = find_text_matches(prompt, prompt_repls)

    # Only displayed on error
    print("result:", result)

    # Manually constructed results
    result_groups = dict(full_groupby(result, key=lambda x: x.modality))
    assert {
        key: [
            dict(start_idx=item.start_idx, end_idx=item.end_idx)
            for item in result_groups.get(key, [])
        ]
        for key in expected_by_key
    } == expected_by_key


# yapf: disable
@pytest.mark.parametrize(
    ("prompt", "target_by_key", "repl_by_key"),
    [
        (
            "Image:<image>Image:<image><image>!",
            {
                # We use `<image>` before `Image:` to test matches that
                # occur out of order
                "pattern_1": "<image>",
                "pattern_2": "Image:",
                "pattern_3": "!",
            },
            {
                # Test whether target is confused with replacement
                "pattern_1": "<image><image>",
                # Test empty replacement
                "pattern_2": "",
                # Test dynamic replacement (beyond the form of `unit * count`)
                "pattern_3": "?!?",
            },
        ),
    ]
)
@pytest.mark.parametrize(
    ("mm_count", "expected"),
    [
        (0, "Image:<image>Image:<image><image>!"),
        (1, "<image><image>Image:<image><image>?!?"),
        (2, "<image><image><image><image><image>?!?"),
    ]
)
# yapf: enable
def test_find_replace_text(
    prompt,
    target_by_key,
    repl_by_key,
    mm_count,
    expected,
):
    # Should not be used since there is nothing to convert to text
    mock_tokenizer = cast(AnyTokenizer, object())

    mm_prompt_repls = {
        key: [
            PromptReplacement(key, target,
                              repl_by_key[key]).bind(mock_tokenizer)
        ]
        for key, target in target_by_key.items()
    }
    mm_matches = {
        key: find_text_matches(prompt, prompt_repls)
        for key, prompt_repls in mm_prompt_repls.items()
    }

    result = replace_text_matches(
        prompt,
        mm_matches,
        {key: mm_count
         for key in repl_by_key},
    )

    # Only displayed on error
    print("mm_matches:", mm_matches)
    print("result:", result)

    # Manually constructed results
    assert result == expected


# yapf: disable
@pytest.mark.parametrize(
    ("prompt", "target_by_key", "repl_by_key"),
    [
        # Tokenized test cases of `test_find_replace_text`
        # using the vocab of llava-hf/llava-v1.6-mistral-7b-hf
        (
            [1, 9833, 28747, 32000, 9833, 28747, 32000, 32000, 918],
            {
                # We use `<image>` before `Image:` to test matches that
                # occur out of order
                "pattern_1": [32000],
                "pattern_2": [9833, 28747],
                "pattern_3": [918],
            },
            {
                # Test whether target is confused with replacement
                "pattern_1": [32000, 32000],
                # Test empty replacement
                "pattern_2": [],
                # Test dynamic replacement (beyond the form of `unit * count`)
                "pattern_3": [1550, 918, 1550],
            },
        ),
    ]
)
@pytest.mark.parametrize(
    ("mm_count", "expected"),
    [
        (0, [1, 9833, 28747, 32000, 9833, 28747, 32000, 32000, 918]),
        (1, [1, 32000, 32000, 9833, 28747, 32000, 32000, 1550, 918, 1550]),
        (2, [1, 32000, 32000, 32000, 32000, 32000, 1550, 918, 1550]),
    ]
)
# yapf: enable
def test_find_replace_tokens(
    prompt,
    target_by_key,
    repl_by_key,
    mm_count,
    expected,
):
    # Should not be used since there is nothing to convert to tokens
    mock_tokenizer = cast(AnyTokenizer, object())

    mm_prompt_repls = {
        key: [
            PromptReplacement(key, target,
                              repl_by_key[key]).bind(mock_tokenizer)
        ]
        for key, target in target_by_key.items()
    }
    mm_matches = {
        key: find_token_matches(prompt, prompt_repls)
        for key, prompt_repls in mm_prompt_repls.items()
    }

    result = replace_token_matches(
        prompt,
        mm_matches,
        {key: mm_count
         for key in repl_by_key},
    )

    # Only displayed on error
    print("mm_matches:", mm_matches)
    print("result:", result)

    # Manually constructed results
    assert result == expected


# yapf: disable
@pytest.mark.parametrize(
    "repl_by_key",
    [
        {
            "pattern_1": [32000, 32000],
            "pattern_2": [],
            "pattern_3": [1550, 918, 1550],
            # Test different modalities having the same tokens (32000)
            "pattern_4": [32000],
        },
    ],
)
@pytest.mark.parametrize(
    ("prompt", "expected"),
    [
        (
            [1, 9833, 28747, 32000, 9833, 28747, 32000, 32000, 918],
            {
                "pattern_1": [
                    PlaceholderFeaturesInfo(
                        modality="pattern_1",
                        item_idx=0,
                        start_idx=6,
                        tokens=[32000, 32000],
                    ),
                ],
                "pattern_4": [
                    PlaceholderFeaturesInfo(
                        modality="pattern_4",
                        item_idx=0,
                        start_idx=3,
                        tokens=[32000],
                    ),
                ],
            }

        ),
        (
            [1, 32000, 32000, 9833, 28747, 32000, 32000, 1550, 918, 1550],
            {
                "pattern_1": [
                    PlaceholderFeaturesInfo(
                        modality="pattern_1",
                        item_idx=0,
                        start_idx=1,
                        tokens=[32000, 32000],
                    ),
                    PlaceholderFeaturesInfo(
                        modality="pattern_1",
                        item_idx=1,
                        start_idx=5,
                        tokens=[32000, 32000],
                    ),
                ],
                "pattern_3": [
                    PlaceholderFeaturesInfo(
                        modality="pattern_3",
                        item_idx=0,
                        start_idx=7,
                        tokens=[1550, 918, 1550],
                    ),
                ],
                # No match for pattern_4 as it has lower priority than pattern_1
            }
        ),
        (
            [1, 32000, 32000, 32000, 32000, 32000, 1550, 918, 1550],
            {
                "pattern_1": [
                    PlaceholderFeaturesInfo(
                        modality="pattern_1",
                        item_idx=0,
                        start_idx=1,
                        tokens=[32000, 32000],
                    ),
                    PlaceholderFeaturesInfo(
                        modality="pattern_1",
                        item_idx=1,
                        start_idx=3,
                        tokens=[32000, 32000],
                    ),
                ],
                "pattern_4": [
                    PlaceholderFeaturesInfo(
                        modality="pattern_4",
                        item_idx=0,
                        start_idx=5,
                        tokens=[32000],
                    ),
                ],
                "pattern_3": [
                    PlaceholderFeaturesInfo(
                        modality="pattern_3",
                        item_idx=0,
                        start_idx=6,
                        tokens=[1550, 918, 1550],
                    ),
                ],
            }
        ),
    ]
)
# yapf: enable
def test_find_mm_placeholders(
    repl_by_key,
    prompt,
    expected,
):
    # Should not be used since there is nothing to convert to tokens
    mock_tokenizer = cast(AnyTokenizer, object())

    mm_prompt_repls = {
        key: [PromptReplacement(key, [], repl).bind(mock_tokenizer)]
        for key, repl in repl_by_key.items()
    }

    result = find_mm_placeholders(
        mm_prompt_repls,
        prompt,
        # Effectively match all occurrences in the prompt
        {key: 3
         for key in repl_by_key},
    )

    # Only displayed on error
    print("result:", result)

    # Manually constructed results
    assert result == expected


@pytest.mark.parametrize("model_id", ["llava-hf/llava-v1.6-mistral-7b-hf"])
@pytest.mark.parametrize(
    ("limit", "num_supported", "is_valid"),
    [(0, 0, True), (0, 1, True), (1, 0, False), (1, 1, True), (1, 2, True),
     (2, 1, False), (2, 2, True)],
)
def test_limit_mm_per_prompt_dummy(model_id, limit, num_supported, is_valid):
    limit_mm_per_prompt = {"image": limit}

    model_config = ModelConfig(
        model=model_id,
        task="auto",
        tokenizer=model_id,
        tokenizer_mode="auto",
        trust_remote_code=False,
        seed=0,
        dtype="half",
        revision=None,
        limit_mm_per_prompt=limit_mm_per_prompt,
    )

    processor = MULTIMODAL_REGISTRY.create_processor(
        model_config,
        tokenizer=cached_tokenizer_from_config(model_config),
    )
    profiler = MultiModalProfiler(processor)

    mock_supported_mm_limits = MagicMock(return_value={"image": num_supported})
    processor.info.get_supported_mm_limits = mock_supported_mm_limits

    if is_valid:
        exc_ctx = nullcontext()
    else:
        exc_ctx = pytest.raises(ValueError, match="this model only supports")

    with exc_ctx:
        profiler.get_dummy_data(model_config.max_model_len)


@pytest.mark.parametrize("model_id", ["llava-hf/llava-v1.6-mistral-7b-hf"])
@pytest.mark.parametrize(
    ("num_images", "limit", "is_valid"),
    [(0, 0, True), (0, 1, True), (1, 0, False), (1, 1, True), (1, 2, True),
     (2, 1, False), (2, 2, True)],
)
def test_limit_mm_per_prompt_apply(model_id, num_images, limit, is_valid):
    limit_mm_per_prompt = {"image": limit}

    model_config = ModelConfig(
        model=model_id,
        task="auto",
        tokenizer=model_id,
        tokenizer_mode="auto",
        trust_remote_code=False,
        seed=0,
        dtype="half",
        revision=None,
        limit_mm_per_prompt=limit_mm_per_prompt,
    )

    processor = MULTIMODAL_REGISTRY.create_processor(
        model_config,
        tokenizer=cached_tokenizer_from_config(model_config),
    )

    rng = np.random.RandomState(0)
    image = random_image(rng, min_wh=128, max_wh=256)
    if num_images == 0:
        mm_data = {}
    elif num_images == 1:
        mm_data = {"image": image}
    else:
        mm_data = {"image": [image] * num_images}

    if is_valid:
        exc_ctx = nullcontext()
    else:
        exc_ctx = pytest.raises(ValueError, match=f"passed {num_images} image")

    with exc_ctx:
        processor.apply(
            "<image>" * num_images,
            mm_data=mm_data,
            hf_processor_mm_kwargs={},
        )


class _ProcessorProxy:

    def __init__(self, processor: ProcessorMixin) -> None:
        super().__init__()

        self.__processor = processor

    def __getattr__(self, key: str):
        return getattr(self.__processor, key)

    def __call__(
        self,
        text=None,
        images=None,
        videos=None,
        exists=None,
        return_tensors=None,
    ):
        return dict(exists=exists)


@pytest.mark.parametrize("model_id", ["Qwen/Qwen2-VL-2B-Instruct"])  # Dummy
# yapf: disable
@pytest.mark.parametrize(
    ("call_kwargs", "expected_kwargs"),
    [
        # Should ignore invalid kwargs
        ({"does_not_exist": 100}, {"exists": None}),
        ({"exists": 1}, {"exists": 1}),
        ({"does_not_exist": 100, "exists": 1}, {"exists": 1}),
    ],
)
# yapf: enable
def test_hf_processor_kwargs(model_id, call_kwargs, expected_kwargs):
    model_config = ModelConfig(
        model=model_id,
        task="auto",
        tokenizer=model_id,
        tokenizer_mode="auto",
        trust_remote_code=False,
        seed=0,
        dtype="half",
        revision=None,
    )

    processor = MULTIMODAL_REGISTRY.create_processor(
        model_config,
        tokenizer=cached_tokenizer_from_config(model_config),
    )
    orig_get_hf_processor = processor.info.get_hf_processor

    def get_hf_processor(self, **kwargs):
        assert kwargs == call_kwargs
        return _ProcessorProxy(orig_get_hf_processor())

    processor.info.get_hf_processor = MethodType(get_hf_processor,
                                                 processor.info)

    out_kwargs = processor._call_hf_processor(
        prompt="",
        mm_data={},
        mm_kwargs=call_kwargs,
    )

    assert out_kwargs == expected_kwargs