python: 3.10.6 โโขโ torch: 2.0.0+cu118 โโขโ xformers: 0.0.19 โโขโ gradio: 3.28.1
Microsoft Edge
fc79eef
[--opt-sdp-attention is OK.]
Total progress: 22it [02:29, 3.52s/it]
Will process 1 images, generating 1 new images for each.
Found 1 face(s) in <PIL.Image.Image image mode=RGB size=944x944 at 0x1A77AB4C9A0>
100%|โโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ| 11/11 [00:01<00:00, 10.01it/s]
Found 1 faces in 1 images in 0.953125 seconds.
Error completing request
Arguments: ('task(f4zd02y7lcvqlui)', 0, '', '', [], <PIL.Image.Image image mode=RGBA size=944x944 at 0x1A77AB4F070>, None, None, None, None, None, None, 20, 0, 4, 0, 1, False, False, 1, 1, 7, 1.5, 0.75, -1.0, -1.0, 0, 0, 0, False, 0, 512, 512, 1, 0, 0, 32, 0, '', '', '', [], 0, True, 'img2img', False, '', '', False, 'Euler a', False, '2339HalfTheFishWas_v10.safetensors [7bf8da1368]', True, 0.5, True, 4, True, 32, '', False, 1, 'Both โฆ', False, '', False, True, True, False, False, False, False, 1, False, '', '', '', 'generateMasksTab', 1, 4, 2.5, 30, 1.03, 1, 1, 5, 0.5, 5, False, True, False, 20, False, 'MultiDiffusion', False, 10, 1, 1, 64, False, True, 1024, 1024, 96, 96, 48, 1, 'None', 2, False, False, False, False, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, 0.4, 0.4, 0.2, 0.2, '', '', 'Background', 0.2, -1.0, False, True, True, True, False, 1536, 96, <controlnet.py.UiControlNetUnit object at 0x000001A77AD5A0E0>, '
\nCFG Scale
should be 2 or lower. \n
\n', True, True, '', '', True, 50, True, 1, 0, False, 4, 0.5, 'Linear', 'None', '
Recommended settings: Sampling Steps: 80-100, Sampler: Euler a, Denoising strength: 0.8
', 128, 8, ['left', 'right', 'up', 'down'], 1, 0.05, 128, 4, 0, ['left', 'right', 'up', 'down'], False, False, 'positive', 'comma', 0, False, False, '', '
Will upscale the image by the selected scale factor; use width and height sliders to set tile size
', 64, 0, 2, 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, 1.6, 0.97, 0.4, 0.15, 20, 0, 0, '', False, False, False, None, False, 50, 'dynamic_thresholding;dynamic_prompting', True, True, True, 2, 'Original', 32, 5, 512, 512, 0.1, True, True, 'Inner', 'Original', 'sam_vit_b_01ec64.pth', 'groundingdino_swint_ogc.pth', True, 32, 4, '', '', '', '', '', '', 0.4, 0.4, 0, 0, 0, 0, True, True, 16, 16, 'Text', 'Center', None, 100, 100, '', None, 'Trebuchet MS', 50, 10, 0.4, '') {}
Traceback (most recent call last):
File "D:\StabilityAI\stable-diffusion-webui\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
File "D:\StabilityAI\stable-diffusion-webui\modules\call_queue.py", line 37, in f
res = func(*args, **kwargs)
File "D:\StabilityAI\stable-diffusion-webui\modules\img2img.py", line 181, in img2img
processed = process_images(p)
File "D:\StabilityAI\stable-diffusion-webui\modules\processing.py", line 515, in process_images
res = process_images_inner(p)
File "D:\StabilityAI\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 42, in processing_process_images_hijack
return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
File "D:\StabilityAI\stable-diffusion-webui\modules\processing.py", line 604, in process_images_inner
p.init(p.all_prompts, p.all_seeds, p.all_subseeds)
File "D:\StabilityAI\stable-diffusion-webui\modules\processing.py", line 1084, in init
self.init_latent = self.sd_model.get_first_stage_encoding(self.sd_model.encode_first_stage(image))
File "D:\StabilityAI\stable-diffusion-webui\modules\sd_hijack_utils.py", line 17, in
setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
File "D:\StabilityAI\stable-diffusion-webui\modules\sd_hijack_utils.py", line 28, in
call
return self.__orig_func(*args, **kwargs)
File "D:\StabilityAI\stable-diffusion-webui\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "D:\StabilityAI\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 830, in encode_first_stage
return self.first_stage_model.encode(x)
File "D:\StabilityAI\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\autoencoder.py", line 83, in encode
h = self.encoder(x)
File "D:\StabilityAI\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "D:\StabilityAI\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\model.py", line 536, in forward
h = self.mid.attn_1(h)
File "D:\StabilityAI\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in
call_impl
return forward_call(*args, **kwargs)
File "D:\StabilityAI\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\model.py", line 258, in forward
out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None, op=self.attention_op)
File "D:\StabilityAI\stable-diffusion-webui\venv\lib\site-packages\xformers\ops\fmha_init.py", line 192, in memory_efficient_attention
return
memory_efficient_attention(
File "D:\StabilityAI\stable-diffusion-webui\venv\lib\site-packages\xformers\ops\fmha_init.py", line 290, in _memory_efficient_attention
return
memory_efficient_attention_forward(
File "D:\StabilityAI\stable-diffusion-webui\venv\lib\site-packages\xformers\ops\fmha_init.py", line 310, in
memory_efficient_attention_forward
out, * = op.apply(inp, needs_gradient=False)
File "D:\StabilityAI\stable-diffusion-webui\venv\lib\site-packages\xformers\ops\fmha\cutlass.py", line 175, in apply
out, lse, rng_seed, rng_offset = cls.OPERATOR(
File "D:\StabilityAI\stable-diffusion-webui\venv\lib\site-packages\torch_ops.py", line 502, in
call
return self._op(*args, **kwargs or {})
RuntimeError: CUDA error: invalid configuration argument
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with
TORCH_USE_CUDA_DSA
to enable device-side assertions.