vllm/tests/multimodal/test_processing.py
HAIAI aee76334d9
[amd_dev] branch rebase (#25753)
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1048 lines
32 KiB
Python

# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
from contextlib import nullcontext
from typing import Optional, cast
import numpy as np
import pytest
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 (InputProcessingContext,
PlaceholderFeaturesInfo,
PromptIndexTargets, PromptInsertion,
PromptReplacement, apply_text_matches,
apply_token_matches,
find_mm_placeholders,
iter_token_matches,
replace_token_matches)
# yapf: enable
from vllm.multimodal.profiling import MultiModalProfiler
from vllm.transformers_utils.tokenizer import AnyTokenizer
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],
[],
),
],
)
@pytest.mark.parametrize("start_idx", [0, 4, 8])
# yapf: enable
def test_iter_token_matches(token_ids, match_ids, expected, start_idx):
result = list(iter_token_matches(token_ids, match_ids,
start_idx=start_idx))
# Manually constructed results
assert [item._asdict() for item in result
] == [item for item in expected if item["start_idx"] >= start_idx]
# 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(
("token_ids", "match_ids", "new_ids", "expected"),
[
([], [], [-1], []),
([], [32000], [-1], []),
(
[32000, 32000, 32000],
[32000],
[-1],
[-1, -1, -1],
),
(
[32000, 32000, 32000],
[32000, 32000],
[-1],
[-1, 32000],
),
(
[32000, 32000, 32000],
[32000, 32000, 32000],
[-1],
[-1],
),
(
[9833, 28747, 32000, 32000, 32000, 9833, 28747, 32000, 32000, 918],
[28747, 32000],
[-1],
[9833, -1, 32000, 32000, 9833, -1, 32000, 918],
),
(
[9833, 28747, 32000, 32000, 32000, 9833, 28747, 32000, 32000, 918],
[28747, 32000, 32000, 32000],
[-1],
[9833, -1, 9833, 28747, 32000, 32000, 918],
),
(
[9833, 28747, 32000, 32000, 32000, 9833, 28747, 32000, 32000, 918],
[28747, 0, 32000],
[-1],
[9833, 28747, 32000, 32000, 32000, 9833, 28747, 32000, 32000, 918],
),
],
)
# yapf: enable
def test_replace_token_matches(token_ids, match_ids, new_ids, expected):
result = replace_token_matches(token_ids, match_ids, new_ids)
# Manually constructed results
assert result == expected
# yapf: disable
@pytest.mark.parametrize(
("prompt", "target_by_key", "expected_by_key"),
[
(
[],
{
"pattern_1": [],
"pattern_2": [32000],
"pattern_3": PromptIndexTargets.start(),
"pattern_4": PromptIndexTargets.prefix([32000]),
"pattern_5": PromptIndexTargets.end(),
},
{
"pattern_1": [],
"pattern_2": [],
"pattern_3": [
{ "start_idx": 0, "end_idx": 0 },
],
"pattern_4": [],
"pattern_5": [
{ "start_idx": 0, "end_idx": 0 },
],
},
),
(
[32000, 32000, 32000, 32000],
{
"pattern_1": [32000],
"pattern_2": [32000, 32000],
"pattern_3": [32000, 32000, 32000],
"pattern_4": PromptIndexTargets.start(),
"pattern_5": PromptIndexTargets.prefix([32000]),
"pattern_6": PromptIndexTargets.end(),
},
{
"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 },
],
"pattern_4": [
{ "start_idx": 0, "end_idx": 0 },
],
"pattern_5": [
{ "start_idx": 1, "end_idx": 1 },
],
"pattern_6": [
{ "start_idx": 4, "end_idx": 4 },
],
},
),
(
[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_4": PromptIndexTargets.start(),
"pattern_5": PromptIndexTargets.prefix([28747, 32000]),
"pattern_6": PromptIndexTargets.end(),
},
{
"pattern_1": [
{ "start_idx": 1, "end_idx": 3 },
{ "start_idx": 6, "end_idx": 8 },
],
"pattern_2": [
{ "start_idx": 1, "end_idx": 5 },
],
"pattern_3": [],
"pattern_4": [
{ "start_idx": 0, "end_idx": 0 },
],
"pattern_5": [],
"pattern_6": [
{ "start_idx": 10, "end_idx": 10 },
],
},
),
],
)
@pytest.mark.parametrize("update_type", [PromptInsertion, PromptReplacement])
# yapf: enable
def test_find_token_matches(
prompt,
target_by_key,
expected_by_key,
update_type,
):
# Should not be used since there is nothing to convert to token IDs
mock_tokenizer = cast(AnyTokenizer, object())
prompt_updates = {
key: update_type(key, target, []).resolve(0)
for key, target in target_by_key.items()
}
result = {
key: list(update.iter_token_matches(prompt, mock_tokenizer))
for key, update in prompt_updates.items()
}
# Only displayed on error
print("result:", result)
# Manually constructed results
assert {
key: [
dict(start_idx=item.start_idx, end_idx=item.end_idx)
for item in result.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_3": PromptIndexTargets.start(),
"pattern_4": PromptIndexTargets.prefix("<image>"),
"pattern_5": PromptIndexTargets.end(),
},
{
"pattern_1": [{ "start_idx": 0, "end_idx": 0 }],
"pattern_2": [],
"pattern_3": [
{ "start_idx": 0, "end_idx": 0 },
],
"pattern_4": [],
"pattern_5": [
{ "start_idx": 0, "end_idx": 0 },
],
}
),
(
"<image><image><image><image>",
{
"pattern_1": "<image>",
"pattern_2": "<image><image>",
"pattern_3": "<image><image><image>",
"pattern_4": PromptIndexTargets.start(),
"pattern_5": PromptIndexTargets.prefix("<image>"),
"pattern_6": PromptIndexTargets.end(),
},
{
"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 },
],
"pattern_4": [
{ "start_idx": 0, "end_idx": 0 },
],
"pattern_5": [
{ "start_idx": 7, "end_idx": 7 },
],
"pattern_6": [
{ "start_idx": 28, "end_idx": 28 },
],
},
),
(
"Image:<image><image><image>Image:<image><image>!",
{
"pattern_1": "Image:<image>",
"pattern_2": "Image:<image><image><image>",
"pattern_3": "Image:<unk><image>",
"pattern_4": PromptIndexTargets.start(),
"pattern_5": PromptIndexTargets.prefix("Image:<image>"),
"pattern_6": PromptIndexTargets.end(),
},
{
"pattern_1": [
{ "start_idx": 0, "end_idx": 13 },
{ "start_idx": 27, "end_idx": 40 },
],
"pattern_2": [
{ "start_idx": 0, "end_idx": 27 },
],
"pattern_3": [],
"pattern_4": [
{ "start_idx": 0, "end_idx": 0 },
],
"pattern_5": [
{ "start_idx": 13, "end_idx": 13 },
],
"pattern_6": [
{ "start_idx": 48, "end_idx": 48 },
],
},
),
# 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 },
],
},
),
],
)
@pytest.mark.parametrize("update_type", [PromptInsertion, PromptReplacement])
# yapf: enable
def test_find_text_matches(
prompt,
target_by_key,
expected_by_key,
update_type,
):
# Should not be used since there is nothing to convert to text
mock_tokenizer = cast(AnyTokenizer, object())
prompt_updates = {
key: update_type(key, target, []).resolve(0)
for key, target in target_by_key.items()
}
result = {
key: list(update.iter_text_matches(prompt, mock_tokenizer))
for key, update in prompt_updates.items()
}
# Only displayed on error
print("result:", result)
# Manually constructed results
assert {
key: [
dict(start_idx=item.start_idx, end_idx=item.end_idx)
for item in result.get(key, [])
]
for key in expected_by_key
} == expected_by_key
# yapf: disable
@pytest.mark.parametrize(
("prompt", "target_by_key", "repl_by_key", "expected_by_update_type_mm_count"), # noqa: E501
[
(
"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": "?!?",
},
{
PromptInsertion: {
0: "Image:<image>Image:<image><image>!",
1: "Image:<image><image><image>Image:<image><image>!?!?",
2: "Image:<image><image><image><image><image>Image:<image><image>!?!??!?", # noqa: E501
},
PromptReplacement: {
0: "Image:<image>Image:<image><image>!",
1: "<image><image>Image:<image><image>?!?",
2: "<image><image><image><image><image>?!?",
},
},
),
# Test index targets
(
"",
{
"pattern_1": PromptIndexTargets.start(),
"pattern_2": PromptIndexTargets.prefix("<image>"),
"pattern_3": PromptIndexTargets.end(),
},
{
"pattern_1": "1",
"pattern_2": "2",
"pattern_3": "3",
},
{
PromptInsertion: {
0: "",
1: "13",
2: "1133",
},
PromptReplacement: {
0: "",
1: "13",
2: "1133",
},
},
),
(
"<image>",
{
"pattern_1": PromptIndexTargets.start(),
"pattern_2": PromptIndexTargets.prefix("<image>"),
"pattern_3": PromptIndexTargets.end(),
},
{
"pattern_1": "1",
"pattern_2": "2",
"pattern_3": "3",
},
{
PromptInsertion: {
0: "<image>",
1: "1<image>23",
2: "11<image>2233",
},
PromptReplacement: {
0: "<image>",
1: "1<image>23",
2: "11<image>2233",
},
},
),
# Test different replacement per item
(
"<image><image><image>",
{
"pattern_1": "<image>",
},
{
"pattern_1": lambda idx: str(idx + 1),
},
{
PromptInsertion: {
0: "<image><image><image>",
1: "<image>1<image><image>",
2: "<image>12<image><image>",
},
PromptReplacement: {
0: "<image><image><image>",
1: "1<image><image>",
2: "12<image>",
},
},
),
(
"<image><image><image>",
{
"pattern_1": PromptIndexTargets.prefix("<image>"),
},
{
"pattern_1": lambda idx: str(idx + 1),
},
{
PromptInsertion: {
0: "<image><image><image>",
1: "<image>1<image><image>",
2: "<image>12<image><image>",
},
PromptReplacement: {
0: "<image><image><image>",
1: "<image>1<image><image>",
2: "<image>12<image><image>",
},
},
),
]
)
# yapf: enable
def test_find_update_text(
prompt,
target_by_key,
repl_by_key,
expected_by_update_type_mm_count,
):
# Should not be used since there is nothing to convert to text
mock_tokenizer = cast(AnyTokenizer, object())
for (
update_type,
expected_by_mm_count,
) in expected_by_update_type_mm_count.items():
for mm_count, expected in expected_by_mm_count.items():
mm_prompt_updates = {
key: [[update_type(key, target, repl_by_key[key]).resolve(i)]
for i in range(mm_count)]
for key, target in target_by_key.items()
}
new_prompt, result = apply_text_matches(
prompt,
mm_prompt_updates,
mock_tokenizer,
)
# Only displayed on error
print("update_type:", update_type)
print("mm_count:", mm_count)
print("mm_prompt_updates:", mm_prompt_updates)
print("new_prompt:", new_prompt)
print("result:", result)
# Manually constructed results
assert new_prompt == expected
# yapf: disable
@pytest.mark.parametrize(
("prompt", "target_by_key", "repl_by_key", "expected_by_update_type_mm_count"), # noqa: E501
[
# Tokenized test cases of `test_find_update_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],
},
{
PromptInsertion: {
0: [1, 9833, 28747, 32000, 9833, 28747, 32000, 32000, 918],
1: [1, 9833, 28747, 32000, 32000, 32000, 9833, 28747, 32000, 32000, 918, 1550, 918, 1550], # noqa: E501
2: [1, 9833, 28747, 32000, 32000, 32000, 32000, 32000, 9833, 28747, 32000, 32000, 918, 1550, 918, 1550, 1550, 918, 1550], # noqa: E501
},
PromptReplacement: {
0: [1, 9833, 28747, 32000, 9833, 28747, 32000, 32000, 918],
1: [1, 32000, 32000, 9833, 28747, 32000, 32000, 1550, 918, 1550], # noqa: E501
2: [1, 32000, 32000, 32000, 32000, 32000, 1550, 918, 1550],
},
},
),
# Test index targets
(
[],
{
"pattern_1": PromptIndexTargets.start(),
"pattern_2": PromptIndexTargets.prefix([32000]),
"pattern_3": PromptIndexTargets.end(),
},
{
"pattern_1": [-1],
"pattern_2": [-2],
"pattern_3": [-3],
},
{
PromptInsertion: {
0: [],
1: [-1, -3],
2: [-1, -1, -3, -3],
},
PromptReplacement: {
0: [],
1: [-1, -3],
2: [-1, -1, -3, -3],
},
},
),
(
[32000],
{
"pattern_1": PromptIndexTargets.start(),
"pattern_2": PromptIndexTargets.prefix([32000]),
"pattern_3": PromptIndexTargets.end(),
},
{
"pattern_1": [-1],
"pattern_2": [-2],
"pattern_3": [-3],
},
{
PromptInsertion: {
0: [32000],
1: [-1, 32000, -2, -3],
2: [-1, -1, 32000, -2, -2, -3, -3],
},
PromptReplacement: {
0: [32000],
1: [-1, 32000, -2, -3],
2: [-1, -1, 32000, -2, -2, -3, -3],
},
},
),
# Test different replacement per item
(
[32000, 32000, 32000],
{
"pattern_1": [32000],
},
{
"pattern_1": lambda idx: [-(idx + 1)],
},
{
PromptInsertion: {
0: [32000, 32000, 32000],
1: [32000, -1, 32000, 32000],
2: [32000, -1, -2, 32000, 32000],
},
PromptReplacement: {
0: [32000, 32000, 32000],
1: [-1, 32000, 32000],
2: [-1, -2, 32000],
},
},
),
(
[32000, 32000, 32000],
{
"pattern_1": PromptIndexTargets.prefix([32000]),
},
{
"pattern_1": lambda idx: [-(idx + 1)],
},
{
PromptInsertion: {
0: [32000, 32000, 32000],
1: [32000, -1, 32000, 32000],
2: [32000, -1, -2, 32000, 32000],
},
PromptReplacement: {
0: [32000, 32000, 32000],
1: [32000, -1, 32000, 32000],
2: [32000, -1, -2, 32000, 32000],
},
},
),
]
)
# yapf: enable
def test_find_update_tokens(
prompt,
target_by_key,
repl_by_key,
expected_by_update_type_mm_count,
):
# Should not be used since there is nothing to convert to tokens
mock_tokenizer = cast(AnyTokenizer, object())
for (
update_type,
expected_by_mm_count,
) in expected_by_update_type_mm_count.items():
for mm_count, expected in expected_by_mm_count.items():
mm_prompt_updates = {
key: [[update_type(key, target, repl_by_key[key]).resolve(i)]
for i in range(mm_count)]
for key, target in target_by_key.items()
}
new_prompt, result = apply_token_matches(
prompt,
mm_prompt_updates,
mock_tokenizer,
)
# Only displayed on error
print("update_type:", update_type)
print("mm_count:", mm_count)
print("mm_prompt_updates:", mm_prompt_updates)
print("new_prompt:", new_prompt)
print("result:", result)
# Manually constructed results
assert new_prompt == 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],
is_embed=None,
),
],
"pattern_4": [
PlaceholderFeaturesInfo(
modality="pattern_4",
item_idx=0,
start_idx=3,
tokens=[32000],
is_embed=None,
),
],
}
),
(
[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],
is_embed=None,
),
PlaceholderFeaturesInfo(
modality="pattern_1",
item_idx=1,
start_idx=5,
tokens=[32000, 32000],
is_embed=None,
),
],
"pattern_3": [
PlaceholderFeaturesInfo(
modality="pattern_3",
item_idx=0,
start_idx=7,
tokens=[1550, 918, 1550],
is_embed=None,
),
],
# 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],
is_embed=None,
),
PlaceholderFeaturesInfo(
modality="pattern_1",
item_idx=1,
start_idx=3,
tokens=[32000, 32000],
is_embed=None,
),
],
"pattern_4": [
PlaceholderFeaturesInfo(
modality="pattern_4",
item_idx=0,
start_idx=5,
tokens=[32000],
is_embed=None,
),
],
"pattern_3": [
PlaceholderFeaturesInfo(
modality="pattern_3",
item_idx=0,
start_idx=6,
tokens=[1550, 918, 1550],
is_embed=None,
),
],
}
),
]
)
@pytest.mark.parametrize("update_type", [PromptInsertion, PromptReplacement])
# yapf: enable
def test_find_mm_placeholders(
repl_by_key,
prompt,
expected,
update_type,
):
# Should not be used since there is nothing to convert to tokens
mock_tokenizer = cast(AnyTokenizer, object())
mm_prompt_updates = {
key: [[update_type(key, [], repl).resolve(i)] for i in range(3)]
for key, repl in repl_by_key.items()
}
result = find_mm_placeholders(prompt, mm_prompt_updates, mock_tokenizer)
# 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,
limit_mm_per_prompt=limit_mm_per_prompt,
)
processor = MULTIMODAL_REGISTRY.create_processor(model_config)
processor._supported_mm_limits = {"image": num_supported}
profiler = MultiModalProfiler(processor)
if is_valid:
exc_ctx = nullcontext()
else:
exc_ctx = pytest.raises(ValueError, match="At most")
with exc_ctx:
profiler.get_decoder_dummy_data(
model_config.max_model_len,
mm_counts=limit_mm_per_prompt,
)
@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,
limit_mm_per_prompt=limit_mm_per_prompt,
)
processor = MULTIMODAL_REGISTRY.create_processor(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="At most")
with exc_ctx:
processor.apply(
"<image>" * num_images,
mm_data=mm_data,
hf_processor_mm_kwargs={},
)
class DummyProcessor:
def __init__(self, a: int = 0, b: int = 0) -> None:
super().__init__()
self.a = a
self.b = b
def __call__(
self,
a: int = 0,
c: int = 0,
return_tensors: Optional[str] = None,
) -> dict[str, int]:
return dict(a=a, c=c)
# yapf: disable
@pytest.mark.parametrize("model_id", ["Qwen/Qwen2-VL-2B-Instruct"]) # Dummy
@pytest.mark.parametrize(
("config_kwargs", "inference_kwargs", "expected_kwargs"),
[
({"a": 1}, {}, {"a": 1, "b": 0}),
({}, {"a": 1}, {"a": 1, "b": 0}),
# inference_kwargs should take precedence
({"a": 1}, {"a": 2}, {"a": 2, "b": 0}),
# Should ignore extra kwargs
({"a": 1, "c": 1}, {}, {"a": 1, "b": 0}),
({"b": 1, "c": 1}, {}, {"a": 0, "b": 1}),
],
)
# yapf: enable
def test_hf_processor_init_kwargs(
model_id,
config_kwargs,
inference_kwargs,
expected_kwargs,
):
# Should not be used since there is nothing to convert to tokens
mock_tokenizer = cast(AnyTokenizer, object())
ctx = InputProcessingContext(
model_config=ModelConfig(model_id, mm_processor_kwargs=config_kwargs),
tokenizer=mock_tokenizer,
)
processor = ctx.get_hf_processor(
DummyProcessor, # type: ignore[arg-type]
**inference_kwargs,
)
for k, v in expected_kwargs.items():
assert getattr(processor, k) == v
# yapf: disable
@pytest.mark.parametrize("model_id", ["Qwen/Qwen2-VL-2B-Instruct"]) # Dummy
@pytest.mark.parametrize(
("config_kwargs", "inference_kwargs", "expected_kwargs"),
[
({"a": 1}, {}, {"a": 1, "c": 0}),
({}, {"a": 1}, {"a": 1, "c": 0}),
# inference_kwargs should take precedence
({"a": 1}, {"a": 2}, {"a": 2, "c": 0}),
# Should ignore extra kwargs
({"a": 1, "c": 1}, {}, {"a": 1, "c": 1}),
({"b": 1, "c": 1}, {}, {"a": 0, "c": 1}),
],
)
# yapf: enable
def test_hf_processor_call_kwargs(
model_id,
config_kwargs,
inference_kwargs,
expected_kwargs,
):
# Should not be used since there is nothing to convert to tokens
mock_tokenizer = cast(AnyTokenizer, object())
ctx = InputProcessingContext(
model_config=ModelConfig(model_id, mm_processor_kwargs=config_kwargs),
tokenizer=mock_tokenizer,
)
processor = ctx.get_hf_processor(DummyProcessor) # type: ignore[arg-type]
result = ctx.call_hf_processor(processor, {}, inference_kwargs)
assert result == expected_kwargs