[HELP]:Only black images are generated.

hello everyone
Please help me
I'm a beginner.　
Please let me know if any files are missing.
I'll add them.

Checklist

• The issue exists after disabling all extensions
• The issue exists on a clean installation of webui
• The issue is caused by an extension, but I believe it is caused by a bug in the webui
• The issue exists in the current version of the webui
• The issue has not been reported before recently
• The issue has been reported before but has not been fixed yet

What happened?
Only a pitch-black image is generated.
Settings→VAE→VAE type for decoding→TAESD generates image but resolution is reduced
And the A1111 does not cause the same problem.

spec
4070TI

Version
version: [f2.0.1v1.10.1-previous-518-gc3366a76]
python: 3.10.6
torch: 2.3.1+cu121
xformers: 0.0.27
gradio: 4.40.0
checkpoint: [196f87e50e]

What do you want to be?
Images are generated normally.

Console logs
`venv "D:\stable-diffusion-webui-forge\venv\Scripts\Python.exe"
Python 3.10.6 (tags/v3.10.6:9c7b4bd, Aug 1 2022, 21:53:49) [MSC v.1932 64 bit (AMD64)]
Version: f2.0.1v1.10.1-previous-518-gc3366a76
Commit hash: c3366a7689427751d08e4ee30842bde4c9a83ce6
Installing xformers
Launching Web UI with arguments: --xformers --ckpt-dir D:/stable-diffusion-webui/models/Stable-diffusion --hypernetwork-dir D:/stable-diffusion-webui/models/hypernetworks --embeddings-dir D:/stable-diffusion-webui/embeddings --lora-dir D:/stable-diffusion-webui/models/Lora --vae-dir D:/stable-diffusion-webui/models/VAE
Total VRAM 12282 MB, total RAM 65246 MB
pytorch version: 2.3.1+cu121
WARNING:xformers:A matching Triton is not available, some optimizations will not be enabled
Traceback (most recent call last):
File "D:\stable-diffusion-webui-forge\venv\lib\site-packages\xformers_init_.py", line 57, in _is_triton_available
import triton # noqa
ModuleNotFoundError: No module named 'triton'
xformers version: 0.0.27
Set vram state to: NORMAL_VRAM
Device: cuda:0 NVIDIA GeForce RTX 4070 Ti : native
Hint: your device supports --cuda-malloc for potential speed improvements.
VAE dtype preferences: [torch.bfloat16, torch.float32] -> torch.bfloat16
CUDA Using Stream: False
Using xformers cross attention
Using xformers attention for VAE
ControlNet preprocessor location: D:\stable-diffusion-webui-forge\models\ControlNetPreprocessor
2024-09-08 12:06:24,821 - ControlNet - INFO - ControlNet UI callback registered.
Model selected: {'checkpoint_info': {'filename': 'D:\stable-diffusion-webui\models\Stable-diffusion\matrixHentaiPony_v160b.safetensors', 'hash': 'eebca96d'}, 'additional_modules': ['D:\stable-diffusion-webui\models\VAE\sdxl.vae.safetensors'], 'unet_storage_dtype': None}
Using online LoRAs in FP16: False
Running on local URL: http://127.0.0.1:7860

To create a public link, set share=True in launch().
Startup time: 23.2s (prepare environment: 4.9s, import torch: 14.8s, other imports: 0.3s, load scripts: 1.0s, create ui: 1.5s, gradio launch: 0.7s).
Environment vars changed: {'stream': False, 'inference_memory': 1024.0, 'pin_shared_memory': False}
[GPU Setting] You will use 91.66% GPU memory (11257.00 MB) to load weights, and use 8.34% GPU memory (1024.00 MB) to do matrix computation.
Loading Model: {'checkpoint_info': {'filename': 'D:\stable-diffusion-webui\models\Stable-diffusion\matrixHentaiPony_v160b.safetensors', 'hash': 'eebca96d'}, 'additional_modules': ['D:\stable-diffusion-webui\models\VAE\sdxl.vae.safetensors'], 'unet_storage_dtype': None}
[Unload] Trying to free all memory for cuda:0 with 0 models keep loaded ... Done.
StateDict Keys: {'unet': 1680, 'vae': 250, 'text_encoder': 197, 'text_encoder_2': 518, 'ignore': 0}
Working with z of shape (1, 4, 32, 32) = 4096 dimensions.
IntegratedAutoencoderKL Unexpected: ['model_ema.decay', 'model_ema.num_updates']
K-Model Created: {'storage_dtype': torch.float16, 'computation_dtype': torch.float16}
Model loaded in 0.7s (unload existing model: 0.1s, forge model load: 0.5s).
[Unload] Trying to free 3051.58 MB for cuda:0 with 0 models keep loaded ... Done.
[Memory Management] Target: JointTextEncoder, Free GPU: 11025.90 MB, Model Require: 1559.68 MB, Previously Loaded: 0.00 MB, Inference Require: 1024.00 MB, Remaining: 8442.22 MB, All loaded to GPU.
Moving model(s) has taken 0.55 seconds
[Unload] Trying to free 1024.00 MB for cuda:0 with 1 models keep loaded ... Current free memory is 9216.19 MB ... Done.
[Unload] Trying to free 7656.40 MB for cuda:0 with 0 models keep loaded ... Current free memory is 9215.34 MB ... Done.
[Memory Management] Target: KModel, Free GPU: 9215.34 MB, Model Require: 4897.05 MB, Previously Loaded: 0.00 MB, Inference Require: 1024.00 MB, Remaining: 3294.29 MB, All loaded to GPU.
Moving model(s) has taken 1.80 seconds
100%|██████████████████████████████████████████████████████████████████████████████████| 20/20 [00:05<00:00, 4.00it/s]
[Unload] Trying to free 4495.36 MB for cuda:0 with 0 models keep loaded ... Current free memory is 4178.18 MB ... Unload model JointTextEncoder Current free memory is 5938.54 MB ... Done.
[Memory Management] Target: IntegratedAutoencoderKL, Free GPU: 5938.54 MB, Model Require: 159.56 MB, Previously Loaded: 0.00 MB, Inference Require: 1024.00 MB, Remaining: 4754.98 MB, All loaded to GPU.
Moving model(s) has taken 0.39 seconds
D:\stable-diffusion-webui-forge\modules\processing.py:1010: RuntimeWarning: invalid value encountered in cast
x_sample = x_sample.astype(np.uint8)
Total progress: 100%|██████████████████████████████████████████████████████████████████| 20/20 [00:05<00:00, 3.74it/s]
Total progress: 100%|██████████████████████████████████████████████████████████████████| 20/20 [00:05<00:00, 4.22it/s]
`

Start with modules/processing.py at line 1010, where the console reports invalid values while converting the generated sample to uint8. Reproduce the black-image result with the listed Forge, Python, PyTorch, GPU, checkpoint, and VAE settings, then compare normal VAE decoding with TAESD decoding. Done means images generate normally without relying on reduced-resolution TAESD output.