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googlecolab / colabtools

Python libraries for Google Colaboratory
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Stable Diffusion is not running #4824

Closed Shiro-Gallen closed 1 month ago

Shiro-Gallen commented 1 month ago

WARNING[XFORMERS]: xFormers can't load C++/CUDA extensions. xFormers was built for: PyTorch 2.3.0+cu121 with CUDA 1201 (you have 2.4.0+cu121) Python 3.10.14 (you have 3.10.12) Please reinstall xformers (see https://github.com/facebookresearch/xformers#installing-xformers) Memory-efficient attention, SwiGLU, sparse and more won't be available. Set XFORMERS_MORE_DETAILS=1 for more details Loading weights [fa892e66c0] from /content/gdrive/MyDrive/sd/stable-diffusion-webui/models/Stable-diffusion/4_sdxlNijiSpecial_sdxlNijiSE.safetensors Creating model from config: /content/gdrive/MyDrive/sd/stablediffusion/generative-models/configs/inference/sd_xl_base.yaml Running on public URL: https://d074e93d780b110106.gradio.live/ ✔ Connected Startup time: 32.2s (import torch: 19.7s, import gradio: 1.7s, setup paths: 1.8s, initialize shared: 0.2s, other imports: 1.5s, list SD models: 1.7s, load scripts: 1.0s, initialize extra networks: 0.2s, create ui: 1.5s, gradio launch: 1.9s, add APIs: 0.8s). Applying attention optimization: xformers... done. Model loaded in 21.8s (load weights from disk: 3.1s, create model: 1.9s, apply weights to model: 14.5s, move model to device: 0.1s, hijack: 0.4s, load textual inversion embeddings: 0.7s, calculate empty prompt: 0.8s). 0% 0/20 [00:00<?, ?it/s] Error completing request Arguments: ('task(z4p319i8avkc29w)', <gradio.routes.Request object at 0x79bc4bd3ce50>, '1 girl', '', [], 1, 1, 7, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', 'Use same scheduler', '', '', [], 0, 20, 'DPM++ 2M', 'Automatic', False, '', 0.8, -1, False, -1, 0, 0, 0, False, False, 'positive', 'comma', 0, False, False, 'start', '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, False, False, False, 0, False) {} Traceback (most recent call last): File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/call_queue.py", line 74, in f res = list(func(*args, kwargs)) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/call_queue.py", line 53, in f res = func(*args, *kwargs) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/call_queue.py", line 37, in f res = func(args, kwargs) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/txt2img.py", line 109, in txt2img processed = processing.process_images(p) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 847, in process_images res = process_images_inner(p) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 988, in process_images_inner samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 1346, in sample samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x)) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 230, in sample samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, extra_params_kwargs)) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_common.py", line 272, in launch_sampling return func() File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 230, in samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, extra_params_kwargs)) File "/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py", line 116, in decorate_context return func(*args, kwargs) File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/sampling.py", line 594, in sample_dpmpp_2m denoised = model(x, sigmas[i] * s_in, *extra_args) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl return self._call_impl(args, kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1562, in _call_impl return forward_call(*args, kwargs) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_cfg_denoiser.py", line 249, in forward x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict(cond_in, image_cond_in)) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl return self._call_impl(*args, *kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1562, in _call_impl return forward_call(args, kwargs) File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/external.py", line 112, in forward eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), kwargs) File "/content/gdrive/MyDrive/sd/stablediffusion/src/k-diffusion/k_diffusion/external.py", line 138, in get_eps return self.inner_model.apply_model(*args, *kwargs) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_models_xl.py", line 43, in apply_model return self.model(x, t, cond) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl return self._call_impl(args, kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1562, in _call_impl return forward_call(*args, kwargs) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_utils.py", line 22, in setattr(resolved_obj, func_path[-1], lambda *args, *kwargs: self(args, kwargs)) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_utils.py", line 34, in call return self.sub_func(self.orig_func, args, kwargs) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_unet.py", line 50, in apply_model result = orig_func(self, x_noisy.to(devices.dtype_unet), t.to(devices.dtype_unet), cond, kwargs) File "/content/gdrive/MyDrive/sd/stablediffusion/generative-models/sgm/modules/diffusionmodules/wrappers.py", line 28, in forward return self.diffusion_model( File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl return self._call_impl(args, kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1562, in _call_impl return forward_call(*args, *kwargs) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_unet.py", line 91, in UNetModel_forward return original_forward(self, x, timesteps, context, args, kwargs) File "/content/gdrive/MyDrive/sd/stablediffusion/generative-models/sgm/modules/diffusionmodules/openaimodel.py", line 993, in forward h = module(h, emb, context) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl return self._call_impl(*args, kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1562, in _call_impl return forward_call(*args, *kwargs) File "/content/gdrive/MyDrive/sd/stablediffusion/generative-models/sgm/modules/diffusionmodules/openaimodel.py", line 100, in forward x = layer(x, context) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl return self._call_impl(args, kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1562, in _call_impl return forward_call(*args, kwargs) File "/content/gdrive/MyDrive/sd/stablediffusion/generative-models/sgm/modules/attention.py", line 627, in forward x = block(x, context=context[i]) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl return self._call_impl(*args, *kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1562, in _call_impl return forward_call(args, kwargs) File "/content/gdrive/MyDrive/sd/stablediffusion/generative-models/sgm/modules/attention.py", line 459, in forward return checkpoint( File "/content/gdrive/MyDrive/sd/stablediffusion/generative-models/sgm/modules/diffusionmodules/util.py", line 167, in checkpoint return func(inputs) File "/content/gdrive/MyDrive/sd/stablediffusion/generative-models/sgm/modules/attention.py", line 467, in _forward self.attn1( File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl return self._call_impl(args, *kwargs) File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1562, in _call_impl return forward_call(args, **kwargs) File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_optimizations.py", line 497, in xformers_attention_forward out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None, op=get_xformers_flash_attention_op(q, k, v)) File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/init__.py", line 268, in memory_efficient_attention return _memory_efficient_attention( File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/init__.py", line 387, in _memory_efficient_attention return _memory_efficient_attention_forward( File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/init.py", line 403, in _memory_efficient_attention_forward op = _dispatch_fw(inp, False) File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/dispatch.py", line 125, in _dispatch_fw return _run_priority_list( File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/dispatch.py", line 65, in _run_priority_list raise NotImplementedError(msg) NotImplementedError: No operator found for memory_efficient_attention_forward with inputs: query : shape=(2, 1024, 10, 64) (torch.float16) key : shape=(2, 1024, 10, 64) (torch.float16) value : shape=(2, 1024, 10, 64) (torch.float16) attn_bias : <class 'NoneType'> p : 0.0 decoderF is not supported because: xFormers wasn't build with CUDA support attn_bias type is <class 'NoneType'> operator wasn't built - see python -m xformers.info for more info flshattF@0.0.0 is not supported because: xFormers wasn't build with CUDA support requires device with capability > (8, 0) but your GPU has capability (7, 5) (too old) cutlassF is not supported because: xFormers wasn't build with CUDA support operator wasn't built - see python -m xformers.info for more info smallkF is not supported because: max(query.shape[-1] != value.shape[-1]) > 32 xFormers wasn't build with CUDA support dtype=torch.float16 (supported: {torch.float32}) operator wasn't built - see python -m xformers.info for more info unsupported embed per head: 64

cperry-goog commented 1 month ago

I can't tell from this snippet what's going on - if you have a minimal reproducible notebook we can investigate but you'll almost surely want to discuss with the notebook author.