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Upgrade transformers to v4.50.3 (#13905)

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Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-03-31 16:59:37 +01:00
committed by GitHub
parent 037bcd942c
commit e5ef4fa99a
8 changed files with 68 additions and 49 deletions
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52
tests/models/decoder_only/vision_language/test_models.py
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@@ -8,9 +8,7 @@ from collections import defaultdict
from pathlib import PosixPath
import pytest
from packaging.version import Version
from transformers import AutoModelForImageTextToText, AutoModelForVision2Seq
from transformers import __version__ as TRANSFORMERS_VERSION
from vllm.platforms import current_platform
from vllm.utils import identity
@@ -126,25 +124,6 @@ VLM_TEST_SETTINGS = {
dtype="bfloat16",
marks=[pytest.mark.skip(reason="vLLM does not support PrefixLM attention mask")], # noqa: E501
),
# TODO(ywang96): Move Qwen2-VL out of core models in favor of Qwen2.5-VL
# once we upgraded to transformers>=4.49.0.
"qwen2_vl": VLMTestInfo(
models=["Qwen/Qwen2-VL-2B-Instruct"],
test_type=(
VLMTestType.IMAGE,
VLMTestType.MULTI_IMAGE,
VLMTestType.VIDEO
),
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: "<|vision_start|><|image_pad|><|vision_end|>", # noqa: E501
video_idx_to_prompt=lambda idx: "<|vision_start|><|video_pad|><|vision_end|>", # noqa: E501
max_model_len=4096,
max_num_seqs=2,
auto_cls=AutoModelForVision2Seq,
vllm_output_post_proc=model_utils.qwen2_vllm_to_hf_output,
image_size_factors=[(), (0.25,), (0.25, 0.25, 0.25), (0.25, 0.2, 0.15)],
marks=[pytest.mark.core_model, pytest.mark.cpu_model],
),
"qwen2_5_vl": VLMTestInfo(
models=["Qwen/Qwen2.5-VL-3B-Instruct"],
test_type=(
@@ -218,12 +197,6 @@ VLM_TEST_SETTINGS = {
hf_output_post_proc=model_utils.deepseekvl2_trunc_hf_output,
stop_str=["<｜end▁of▁sentence｜>", "<｜begin▁of▁sentence｜>"], # noqa: E501
image_size_factors=[(), (1.0, ), (1.0, 1.0, 1.0), (0.1, 0.5, 1.0)],
marks=[
pytest.mark.skipif(
Version(TRANSFORMERS_VERSION) >= Version("4.48"),
reason="HF model is not compatible with transformers>=4.48",
)
],
),
"fuyu": VLMTestInfo(
models=["adept/fuyu-8b"],
@@ -336,6 +309,7 @@ VLM_TEST_SETTINGS = {
prompt_formatter=lambda vid_prompt: f"<|im_start|>user\n{vid_prompt}<|im_end|>\n<|im_start|>assistant\n", # noqa: E501
num_video_frames=16,
max_model_len=16384,
hf_model_kwargs=model_utils.llava_onevision_hf_model_kwargs("llava-hf/llava-onevision-qwen2-0.5b-ov-hf"), # noqa: E501
auto_cls=AutoModelForVision2Seq,
vllm_output_post_proc=model_utils.llava_onevision_vllm_to_hf_output,
custom_test_opts=[CustomTestOptions(
@@ -365,12 +339,6 @@ VLM_TEST_SETTINGS = {
auto_cls=AutoModelForImageTextToText,
vllm_output_post_proc=model_utils.mantis_vllm_to_hf_output,
patch_hf_runner=model_utils.mantis_patch_hf_runner,
marks=[
pytest.mark.skipif(
Version(TRANSFORMERS_VERSION) >= Version("4.48"),
reason="HF model is not compatible with transformers>=4.48",
)
],
),
"minicpmv_25": VLMTestInfo(
models=["openbmb/MiniCPM-Llama3-V-2_5"],
@@ -450,6 +418,23 @@ VLM_TEST_SETTINGS = {
vllm_output_post_proc=model_utils.qwen_vllm_to_hf_output,
prompt_path_encoder=model_utils.qwen_prompt_path_encoder,
),
"qwen2_vl": VLMTestInfo(
models=["Qwen/Qwen2-VL-2B-Instruct"],
test_type=(
VLMTestType.IMAGE,
VLMTestType.MULTI_IMAGE,
VLMTestType.VIDEO
),
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: "<|vision_start|><|image_pad|><|vision_end|>", # noqa: E501
video_idx_to_prompt=lambda idx: "<|vision_start|><|video_pad|><|vision_end|>", # noqa: E501
max_model_len=4096,
max_num_seqs=2,
auto_cls=AutoModelForVision2Seq,
vllm_output_post_proc=model_utils.qwen2_vllm_to_hf_output,
image_size_factors=[(), (0.25,), (0.25, 0.25, 0.25), (0.25, 0.2, 0.15)],
marks=[pytest.mark.cpu_model],
),
"skywork_r1v": VLMTestInfo(
models=["Skywork/Skywork-R1V-38B"],
test_type=(VLMTestType.IMAGE, VLMTestType.MULTI_IMAGE),
@@ -515,6 +500,7 @@ VLM_TEST_SETTINGS = {
max_model_len=16384,
max_num_seqs=2,
auto_cls=AutoModelForVision2Seq,
hf_model_kwargs=model_utils.llava_onevision_hf_model_kwargs("llava-hf/llava-onevision-qwen2-0.5b-ov-hf"), # noqa: E501
vllm_output_post_proc=model_utils.llava_onevision_vllm_to_hf_output,
custom_test_opts=[CustomTestOptions(
inputs=custom_inputs.multi_image_multi_aspect_ratio_inputs(