diffusers
diffusers copied to clipboard
Published
1 month ago
โข
huggingface
huggingface
Any Wan version crashes
Describe the bug
Running any diffusers Wan example code crashes for me, when running from inside Blender python (everything else in Diffusers has run fine from Blender Python over the years).
Ex. code:
# pip install ftfy
import torch
import numpy as np
from diffusers import AutoModel, WanPipeline
from diffusers.quantizers import PipelineQuantizationConfig
from diffusers.hooks.group_offloading import apply_group_offloading
from diffusers.utils import export_to_video, load_image
from transformers import UMT5EncoderModel
text_encoder = UMT5EncoderModel.from_pretrained("Wan-AI/Wan2.1-T2V-14B-Diffusers", subfolder="text_encoder", torch_dtype=torch.bfloat16)
vae = AutoModel.from_pretrained("Wan-AI/Wan2.1-T2V-14B-Diffusers", subfolder="vae", torch_dtype=torch.float32)
transformer = AutoModel.from_pretrained("Wan-AI/Wan2.1-T2V-14B-Diffusers", subfolder="transformer", torch_dtype=torch.bfloat16)
# group-offloading
onload_device = torch.device("cuda")
offload_device = torch.device("cpu")
apply_group_offloading(text_encoder,
onload_device=onload_device,
offload_device=offload_device,
offload_type="block_level",
num_blocks_per_group=4
)
transformer.enable_group_offload(
onload_device=onload_device,
offload_device=offload_device,
offload_type="leaf_level",
use_stream=True
)
pipeline = WanPipeline.from_pretrained(
"Wan-AI/Wan2.1-T2V-14B-Diffusers",
vae=vae,
transformer=transformer,
text_encoder=text_encoder,
torch_dtype=torch.bfloat16
)
pipeline.to("cuda")
prompt = """
The camera rushes from far to near in a low-angle shot,
revealing a white ferret on a log. It plays, leaps into the water, and emerges, as the camera zooms in
for a close-up. Water splashes berry bushes nearby, while moss, snow, and leaves blanket the ground.
Birch trees and a light blue sky frame the scene, with ferns in the foreground. Side lighting casts dynamic
shadows and warm highlights. Medium composition, front view, low angle, with depth of field.
"""
negative_prompt = """
Bright tones, overexposed, static, blurred details, subtitles, style, works, paintings, images, static, overall gray, worst quality,
low quality, JPEG compression residue, ugly, incomplete, extra fingers, poorly drawn hands, poorly drawn faces, deformed, disfigured,
misshapen limbs, fused fingers, still picture, messy background, three legs, many people in the background, walking backwards
"""
output = pipeline(
prompt=prompt,
negative_prompt=negative_prompt,
num_frames=81,
guidance_scale=5.0,
).frames[0]
export_to_video(output, "output.mp4", fps=16)
Results in:
Loading checkpoint shards: 100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 5/5 [00:08<00:00, 1.60s/it]
Fetching 12 files: 100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 12/12 [00:00<?, ?it/s]
Loading checkpoint shards: 58%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ | 7/12 [00:22<00:17, 3.47s/it]Error : EXCEPTION_ACCESS_VIOLATION
Address : 0x00007FFA24B56EDB
Module : torch_cpu.dll
Thread : 00007254
Writing: C:\Users\peter\AppData\Local\Temp\Dependencies_01.crash.txt
Report: Dependencies_01.crash.txt
Reproduction
Win 11 CUDA 12.4 RTX 4090 Python 3.11
Package Version
---------------------- ------------
absl-py 2.3.1
accelerate 1.11.0
anyio 4.11.0
attrs 25.4.0
autopep8 2.3.1
bitsandbytes 0.48.2
certifi 2025.4.26
charset-normalizer 3.4.1
click 8.3.0
colorama 0.4.6
contourpy 1.3.3
cycler 0.12.1
Cython 3.0.11
diffusers 0.36.0.dev0
einops 0.8.1
en_core_web_md 3.8.0
filelock 3.20.0
flatbuffers 25.9.23
fonttools 4.60.1
fsspec 2025.10.0
gguf 0.17.1
h11 0.16.0
hf-xet 1.2.0
httpcore 1.0.9
httpx 0.28.1
huggingface-hub 0.36.0
idna 3.10
image_gen_aux 0.1.0.dev0
importlib_metadata 8.7.0
jax 0.8.0
jaxlib 0.8.0
Jinja2 3.1.6
kiwisolver 1.4.9
kornia 0.8.2
kornia_rs 0.1.10
MarkupSafe 3.0.3
matplotlib 3.10.7
meson 0.63.0
ml_dtypes 0.5.3
mpmath 1.3.0
networkx 3.5
numpy 1.26.4
opencv-python-headless 4.12.0.88
opt_einsum 3.4.0
packaging 25.0
peft 0.18.0
pillow 12.0.0
pip 25.3
protobuf 3.20.1
psutil 7.1.3
pycodestyle 2.13.0
pydub 0.25.1
pyparsing 3.2.5
python-dateutil 2.9.0.post0
PyYAML 6.0.3
regex 2025.11.3
reportlab 4.4.4
requests 2.32.5
safetensors 0.6.2
scipy 1.16.3
screenplain 0.11.1
sentencepiece 0.2.1
setuptools 63.2.0
shellingham 1.5.4
six 1.17.0
sniffio 1.3.1
spandrel 0.4.1
sympy 1.13.1
timm 1.0.22
tokenizers 0.22.1
torch 2.6.0+cu124
torchaudio 2.6.0+cu124
torcheval 0.0.7
torchvision 0.21.0+cu124
tqdm 4.67.1
transformers 4.57.1
triton-windows 3.2.0.post21
typer-slim 0.20.0
typing_extensions 4.15.0
urllib3 2.4.0
xformers 0.0.29.post3
zipp 3.23.0
zstandard 0.23.0
Logs
Also linked to above:
# Blender 4.5.5, Commit date: 2025-11-12 13:42, Hash 231f96901b68
bpy.context.scene.generatorai_typeselect = 'movie' # Property
bpy.ops.sequencer.generate_movie() # Operator
Python: Traceback (most recent call last):
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\models\modeling_utils.py", line 1190, in from_pretrained
resolved_model_file = _get_model_file(
^^^^^^^^^^^^^^^^
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\huggingface_hub\utils\_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\utils\hub_utils.py", line 290, in _get_model_file
model_file = hf_hub_download(
^^^^^^^^^^^^^^^^
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\huggingface_hub\utils\_validators.py", line 114, in _inner_fn
return fn(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\huggingface_hub\file_download.py", line 1007, in hf_hub_download
return _hf_hub_download_to_cache_dir(
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\huggingface_hub\file_download.py", line 1168, in _hf_hub_download_to_cache_dir
_download_to_tmp_and_move(
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\huggingface_hub\file_download.py", line 1720, in _download_to_tmp_and_move
xet_get(
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\huggingface_hub\file_download.py", line 626, in xet_get
download_files(
KeyboardInterrupt # Error
# backtrace
Exception Record:
ExceptionCode : EXCEPTION_ACCESS_VIOLATION
Exception Address : 0x00007FFA24B56EDB
Exception Module : torch_cpu.dll
Exception Flags : 0x00000000
Exception Parameters : 0x2
Parameters[0] : 0x0000000000000000
Parameters[1] : 0x0000000000002638
Stack trace:
torch_cpu.dll :0x00007FFA24B56BD0 at::native::_rowwise_prune
torch_cpu.dll :0x00007FFA24B576A0 at::native::_local_scalar_dense_cpu
torch_cpu.dll :0x00007FFA25723510 at::cpu::where_outf
torch_cpu.dll :0x00007FFA256BB250 at::cpu::bucketize_outf
torch_cpu.dll :0x00007FFA2538B660 at::_ops::_local_scalar_dense::redispatch
torch_cpu.dll :0x00007FFA26B33010 torch::autograd::GraphRoot::apply
torch_cpu.dll :0x00007FFA26B33010 torch::autograd::GraphRoot::apply
torch_cpu.dll :0x00007FFA252EA5B0 at::_ops::_local_scalar_dense::call
torch_cpu.dll :0x00007FFA24B57750 at::native::item
torch_cpu.dll :0x00007FFA25A1EDB0 at::compositeimplicitautograd::where
torch_cpu.dll :0x00007FFA259CEBF0 at::compositeimplicitautograd::broadcast_to_symint
torch_cpu.dll :0x00007FFA251A4A50 at::_ops::item::call
torch_cpu.dll :0x00007FFA25E6C8B0 at::Tensor::item<unsigned char>
torch_python.dll :0x00007FFA1E311EA0 pybind11::detail::type_caster<at::Tensor,void>::load
torch_python.dll :0x00007FFA1DEB77F0 isMainPyInterpreter
python311.dll :0x00007FFB69E456D0 PyObject_Call
python311.dll :0x00007FFB69F74820 PyEval_GetFuncDesc
python311.dll :0x00007FFB69F6B020 PyEval_EvalFrameDefault
python311.dll :0x00007FFB69F6B020 PyEval_EvalFrameDefault
python311.dll :0x00007FFB69E45880 PyFunction_Vectorcall
python311.dll :0x00007FFB69EA4CB0 PyTuple_DebugMallocStats
python311.dll :0x00007FFB69EA8060 PyObject_LookupSpecialId
python311.dll :0x00007FFB69EAF9B0 PyType_Ready
torch_python.dll :0x00007FFA1E357A80 torch::utils::getTHPMemoryFormat
torch_python.dll :0x00007FFA1E357A80 torch::utils::getTHPMemoryFormat
torch_python.dll :0x00007FFA1E357A80 torch::utils::getTHPMemoryFormat
torch_python.dll :0x00007FFA1DF1A750 THPPointer<PyCodeObject>::THPPointer<PyCodeObject>
python311.dll :0x00007FFB69E8B3D0 PyCFunction_GetFlags
python311.dll :0x00007FFB69E456D0 PyObject_Call
_safetensors_rust.pyd:0x00007FFBA334A701 Symbols not available
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# Python backtrace
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\torch\storage.py", line 469 in __getitem__
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\safetensors\torch.py", line 383 in load_file
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\models\model_loading_utils.py", line 177 in load_state_dict
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\models\model_loading_utils.py", line 358 in _load_shard_file
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\models\modeling_utils.py", line 1667 in _load_pretrained_model
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\models\modeling_utils.py", line 1285 in from_pretrained
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\huggingface_hub\utils\_validators.py", line 114 in _inner_fn
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\models\auto_model.py", line 223 in from_pretrained
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\huggingface_hub\utils\_validators.py", line 114 in _inner_fn
File "C:\Users\peter\Documents\Dependencies_01.blend\Text.002", line 12 in <module>
System Info
Win 11 CUDA 12.4 RTX 4090 Python 3.11 diffusers 0.36.0.dev0
Who can help?
No response
hi @tin2tin how much RAM do you have? using your code, you will need at least 64GB of free RAM, if you don't have it, maybe that's the reason. Since that crash doesn't have a really helpful message, we can just guess though.
Processor AMD Ryzen 9 7900X 12-Core Processor (4.70 GHz) Installed RAM 32,0 GB (31,2 GB usable) System type 64-bit operating system, x64-based processor
Is the offloading to RAM hard-coded in Diffusers? It works fine when using Wan on ComfyUI.
Is there anything I can do to get it to work via Diffusers?
when you use group_offloading with leaf and cuda streams in diffusers is very different than ComfyUI, this technique is very fast because it prefetch the next layer while the current one is running at the cost of higher RAM usage.
If I remember correctly, ComfyUI just offloads the layers/blocks that don't fit in the GPU, not sure if it moves or clones them, but anyways, ComfyUI does a lot of stuff without the user knowing at the cost of speed and abstraction, with diffusers, you have total control of what you can do but you need the knowledge/experience to be able to do it, but we can help with that too.
You have several options:
- you can add
low_cpu_mem_usage=Trueat the cost of inference speed. - you can offload to a fast SSD instead of RAM with
offload_to_disk_path=path - you can switch from
leaftoblock_level - you can use layerwise casting.
- you can use quantization
I did try quantization with bitsandbytes and that didn't work either. What are the ram/vram needs for those other solutions? Any examples?
I did try quantization with bitsandbytes and that didn't work either.
what do you mean with "it didn't work"? had the same EXCEPTION_ACCESS_VIOLATION error? If it is, that really doesn't help, I test diffusers under windows quite often and I never get that generic error, so I really don't know what causes it. I'm guessing is something in your environment and the way you use it inside blender.
What are the ram/vram needs for those other solutions?
it varies with each solution, sadly I don't have the bandwidth right now to do them all with all the possible combinations and see how much VRAM and RAM they use. I'm starting to compile examples and create a repo so I can share it in the future with people like you so you can just copy & paste the code.
Any examples?
Each one is properly documented in the docs here and here with examples on how to use them.
I tried DiffStudio, their default solution, it workied but took 30 mins. for a single 81 frames video on a RTX 4090+32 GB RAM.
Unfortunately, I didn't save my bitsandbytes code. However, running this code of yours: https://github.com/huggingface/diffusers/issues/12613#issuecomment-3513272423
I get similar errors:
Loading pipeline components...: 17%|โโโโโโโโโ | 1/6 [00:02<00:11, 2.33s/it]`torch_dtype` is deprecated! Use `dtype` instead!
Loading checkpoint shards: 100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 3/3 [00:00<00:00, 35.61it/s]
Loading checkpoint shards: 100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 12/12 [00:31<00:00, 2.64s/it]
Loading pipeline components...: 83%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ | 5/6 [00:35<00:07, 7.47s/it]Error : EXCEPTION_ACCESS_VIOLATIONโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ | 8/12 [00:34<00:21, 5.36s/it]
Address : 0x00007FFA14226EDB
Module : torch_cpu.dll
Thread : 0000a03c
Writing: C:\Users\peter\AppData\Local\Temp\Dependencies_01.crash.txt
# Blender 4.5.5, Commit date: 2025-11-12 13:42, Hash 231f96901b68
# backtrace
Exception Record:
ExceptionCode : EXCEPTION_ACCESS_VIOLATION
Exception Address : 0x00007FFA14226EDB
Exception Module : torch_cpu.dll
Exception Flags : 0x00000000
Exception Parameters : 0x2
Parameters[0] : 0x0000000000000000
Parameters[1] : 0x0000000000002508
Stack trace:
torch_cpu.dll :0x00007FFA14226BD0 at::native::_rowwise_prune
torch_cpu.dll :0x00007FFA142276A0 at::native::_local_scalar_dense_cpu
torch_cpu.dll :0x00007FFA14DF3510 at::cpu::where_outf
torch_cpu.dll :0x00007FFA14D8B250 at::cpu::bucketize_outf
torch_cpu.dll :0x00007FFA14A5B660 at::_ops::_local_scalar_dense::redispatch
torch_cpu.dll :0x00007FFA16203010 torch::autograd::GraphRoot::apply
torch_cpu.dll :0x00007FFA16203010 torch::autograd::GraphRoot::apply
torch_cpu.dll :0x00007FFA149BA5B0 at::_ops::_local_scalar_dense::call
torch_cpu.dll :0x00007FFA14227750 at::native::item
torch_cpu.dll :0x00007FFA150EEDB0 at::compositeimplicitautograd::where
torch_cpu.dll :0x00007FFA1509EBF0 at::compositeimplicitautograd::broadcast_to_symint
torch_cpu.dll :0x00007FFA14874A50 at::_ops::item::call
torch_cpu.dll :0x00007FFA1553C8B0 at::Tensor::item<unsigned char>
torch_python.dll :0x00007FFB19A41EA0 pybind11::detail::type_caster<at::Tensor,void>::load
torch_python.dll :0x00007FFB195E77F0 isMainPyInterpreter
python311.dll :0x00007FFB6AEE56D0 PyObject_Call
python311.dll :0x00007FFB6B014820 PyEval_GetFuncDesc
python311.dll :0x00007FFB6B00B020 PyEval_EvalFrameDefault
python311.dll :0x00007FFB6B00B020 PyEval_EvalFrameDefault
python311.dll :0x00007FFB6AEE5880 PyFunction_Vectorcall
python311.dll :0x00007FFB6AF44CB0 PyTuple_DebugMallocStats
python311.dll :0x00007FFB6AF48060 PyObject_LookupSpecialId
python311.dll :0x00007FFB6AF4F9B0 PyType_Ready
torch_python.dll :0x00007FFB19A87A80 torch::utils::getTHPMemoryFormat
torch_python.dll :0x00007FFB19A87A80 torch::utils::getTHPMemoryFormat
torch_python.dll :0x00007FFB19A87A80 torch::utils::getTHPMemoryFormat
torch_python.dll :0x00007FFB1964A750 THPPointer<PyCodeObject>::THPPointer<PyCodeObject>
python311.dll :0x00007FFB6AF2B3D0 PyCFunction_GetFlags
python311.dll :0x00007FFB6AEE56D0 PyObject_Call
_safetensors_rust.pyd:0x00007FFBA31CA701 Symbols not available
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# Python backtrace
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\torch\storage.py", line 469 in __getitem__
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\safetensors\torch.py", line 383 in load_file
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\models\model_loading_utils.py", line 177 in load_state_dict
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\models\model_loading_utils.py", line 358 in _load_shard_file
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\models\modeling_utils.py", line 1667 in _load_pretrained_model
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\models\modeling_utils.py", line 1285 in from_pretrained
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\huggingface_hub\utils\_validators.py", line 114 in _inner_fn
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\pipelines\pipeline_loading_utils.py", line 876 in load_sub_model
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\diffusers\pipelines\pipeline_utils.py", line 1021 in from_pretrained
File "C:\Users\peter\blender-4.5.5\blender-4.5.5\4.5\python\Lib\site-packages\huggingface_hub\utils\_validators.py", line 114 in _inner_fn
File "C:\Users\peter\Documents\Dependencies_01.blend\Text.004", line 12 in <module>
that code works for 48GB GPUs only, WAN is a big model, using group offloading made the denoise inference time to go over 50m using half precision, so probably don't expect short times without quantization and distilled loras. That's why I was asking what problem did you have with it, since I know it works with quantization without problems.
Still crashing the same way with bitsandbytes 32 GB RAM, 64 GB paging file, RTX 4090 24 GB VRAM.
import torch
import numpy as np
from diffusers import WanImageToVideoPipeline, WanTransformer3DModel
from diffusers.utils import export_to_video, load_image
from transformers import BitsAndBytesConfig
model_id = "FastDM/Wan2.2-I2V-A14B-Merge-Lightning-V1.0-Diffusers"
dtype = torch.bfloat16
quant_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=dtype
)
transformer = WanTransformer3DModel.from_pretrained(
model_id,
subfolder="transformer",
quantization_config=quant_config,
torch_dtype=dtype
)
pipe = WanImageToVideoPipeline.from_pretrained(
model_id,
transformer=transformer,
torch_dtype=dtype
)
pipe.enable_model_cpu_offload()
pipe.vae.enable_tiling()
image = load_image(
"https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/wan_i2v_input.JPG"
)
max_area = 480 * 832
aspect_ratio = image.height / image.width
mod_value = pipe.vae_scale_factor_spatial * pipe.transformer.config.patch_size[1]
height = round(np.sqrt(max_area * aspect_ratio)) // mod_value * mod_value
width = round(np.sqrt(max_area / aspect_ratio)) // mod_value * mod_value
image = image.resize((width, height))
prompt = "Summer beach vacation style, a white cat wearing sunglasses sits on a surfboard. The fluffy-furred feline gazes directly at the camera with a relaxed expression. Blurred beach scenery forms the background featuring crystal-clear waters, distant green hills, and a blue sky dotted with white clouds. The cat assumes a naturally relaxed posture, as if savoring the sea breeze and warm sunlight. A close-up shot highlights the feline's intricate details and the refreshing atmosphere of the seaside."
negative_prompt = "่ฒ่ฐ่ณไธฝ๏ผ่ฟๆ๏ผ้ๆ๏ผ็ป่ๆจก็ณไธๆธ
๏ผๅญๅน๏ผ้ฃๆ ผ๏ผไฝๅ๏ผ็ปไฝ๏ผ็ป้ข๏ผ้ๆญข๏ผๆดไฝๅ็ฐ๏ผๆๅทฎ่ดจ้๏ผไฝ่ดจ้๏ผJPEGๅ็ผฉๆฎ็๏ผไธ้็๏ผๆฎ็ผบ็๏ผๅคไฝ็ๆๆ๏ผ็ปๅพไธๅฅฝ็ๆ้จ๏ผ็ปๅพไธๅฅฝ็่ธ้จ๏ผ็ธๅฝข็๏ผๆฏๅฎน็๏ผๅฝขๆ็ธๅฝข็่ขไฝ๏ผๆๆ่ๅ๏ผ้ๆญขไธๅจ็็ป้ข๏ผๆไนฑ็่ๆฏ๏ผไธๆก่
ฟ๏ผ่ๆฏไบบๅพๅค๏ผๅ็่ตฐ"
generator = torch.Generator(device="cuda").manual_seed(0)
output = pipe(
image=image,
prompt=prompt,
negative_prompt=negative_prompt,
height=height,
width=width,
num_frames=81,
guidance_scale=1.0,
num_inference_steps=4,
generator=generator,
).frames[0]
export_to_video(output, "i2v_output.mp4", fps=16)
The error EXCEPTION_ACCESS_VIOLATION inside _sentencepiece.cp311-win_amd64.pyd confirms that the SentencePiece library (used for the T5 Tokenizer) is crashing. The Fix: bypass the crashing sentencepiece library entirely by switching to the "Fast" Tokenizer (which is written in Rust and uses a different library, tokenizers).
This is the closest I got to getting it rendering(no crash), but the image of the video is completely broken:
import torch
import gc
import numpy as np
from diffusers import WanImageToVideoPipeline, WanTransformer3DModel, AutoencoderKLWan
from diffusers.schedulers import UniPCMultistepScheduler
from transformers import T5EncoderModel, AutoTokenizer, BitsAndBytesConfig
from diffusers.utils import export_to_video, load_image
gc.collect()
torch.cuda.empty_cache()
model_id = "FastDM/Wan2.2-I2V-A14B-Merge-Lightning-V1.0-Diffusers"
dtype = torch.bfloat16
quant_config = BitsAndBytesConfig(
load_in_4bit=True,
bnb_4bit_quant_type="nf4",
bnb_4bit_compute_dtype=dtype
)
print("--- Step 1: Loading Tokenizer (Fast Mode) ---")
try:
tokenizer = AutoTokenizer.from_pretrained(model_id, subfolder="tokenizer", use_fast=True)
except:
tokenizer = AutoTokenizer.from_pretrained("google/t5-v1_1-xxl", use_fast=True)
print("--- Step 2: Loading Text Encoder (4-bit) ---")
text_encoder = T5EncoderModel.from_pretrained(
model_id,
subfolder="text_encoder",
quantization_config=quant_config,
torch_dtype=dtype
)
print("--- Step 3: Loading VAE (bfloat16) ---")
vae = AutoencoderKLWan.from_pretrained(
model_id,
subfolder="vae",
torch_dtype=dtype
)
print("--- Step 4: Loading Transformer (4-bit) ---")
transformer = WanTransformer3DModel.from_pretrained(
model_id,
subfolder="transformer",
quantization_config=quant_config,
torch_dtype=dtype
)
print("--- Step 5: Loading Scheduler ---")
scheduler = UniPCMultistepScheduler.from_pretrained(model_id, subfolder="scheduler")
print("--- Step 6: Assembling Pipeline ---")
pipe = WanImageToVideoPipeline(
vae=vae,
text_encoder=text_encoder,
tokenizer=tokenizer,
transformer=transformer,
scheduler=scheduler
)
print("--- Step 7: Optimizing Memory ---")
pipe.enable_model_cpu_offload()
pipe.vae.enable_tiling()
print("--- Processing Input Image ---")
image_url = "https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/wan_i2v_input.JPG"
image = load_image(image_url)
max_area = 480 * 832
aspect_ratio = image.height / image.width
mod_value = 16
height = round(np.sqrt(max_area * aspect_ratio)) // mod_value * mod_value
width = round(np.sqrt(max_area / aspect_ratio)) // mod_value * mod_value
image = image.resize((width, height))
prompt = "Summer beach vacation style, a white cat wearing sunglasses sits on a surfboard. The fluffy-furred feline gazes directly at the camera with a relaxed expression."
negative_prompt = "low quality, bad anatomy, distorted, blurry, ugly, text, watermark"
print("--- Generating Video ---")
output = pipe(
image=image,
prompt=prompt,
negative_prompt=negative_prompt,
height=height,
width=width,
num_frames=81,
guidance_scale=1.0,
num_inference_steps=4,
).frames[0]
print("--- Saving Video ---")
export_to_video(output, "i2v_output_manual.mp4", fps=16)
print("Done!")
https://github.com/user-attachments/assets/770291bc-1643-48d0-a362-93579159467b
I'll try to take a look today, you have 32GB of RAM and 24GB of VRAM but since you're using this inside blender and with windows, can you tell me the real FREE values you have, I'm guessing is more like 20GB of RAM and 20 of VRAM, ideally this should work without using the page file or the shared VRAM that the nvidia driver uses by default.
Also do you happen to have a fast nvme drive?
maybe the flow shift.
pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config, flow_shift=3.0)
I know this fused lighting model works when quantized and offloaded. But i only quant the text encoder to 8bit and only use the transformers from it magespace/Wan2.2-I2V-A14B-Lightning-Diffusers
I have some example code here if it helps atall https://github.com/JoeGaffney/deferred-diffusion/blob/main/workers/videos/local/wan_2.py
Possibly also lifting the code out of blender would be good to figure out any issues there or contention of memory.
