No such operator xformers::efficient_attention_forward_cutlass

Traceback (most recent call last): File “/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/call_queue.py”, line 45, in f res = list(func(*args, **kwargs)) File “/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/call_queue.py”, line 28, in f res = func(*args, **kwargs) File “/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/txt2img.py”, line 49, in txt2img processed = process_images(p) File “/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py”, line 430, in process_images res = process_images_inner(p) File “/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py”, line 531, in process_images_inner samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts) File “/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py”, line 664, 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.py”, line 507, in sample samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={ File “/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers.py”, line 422, in launch_sampling return func() File “/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers.py”, line 507, in <lambda> samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={ File “/usr/local/lib/python3.8/dist-packages/torch/autograd/grad_mode.py”, line 27, 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/python3.8/dist-packages/torch/nn/modules/module.py”, line 1190, in _call_impl return forward_call(*input, **kwargs) File “/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers.py”, line 315, in forward x_out = self.inner_model(x_in, sigma_in, cond={“c_crossattn”: [cond_in], “c_concat”: [image_cond_in]}) File “/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py”, line 1190, in _call_impl return forward_call(*input, **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/stablediffusion/ldm/models/diffusion/ddpm.py”, line 858, in apply_model x_recon = self.model(x_noisy, t, **cond) File “/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py”, line 1190, in _call_impl return forward_call(*input, **kwargs) File “/content/gdrive/MyDrive/sd/stablediffusion/ldm/models/diffusion/ddpm.py”, line 1329, in forward out = self.diffusion_model(x, t, context=cc) File “/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py”, line 1190, in _call_impl return forward_call(*input, **kwargs) File “/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/openaimodel.py”, line 776, in forward h = module(h, emb, context) File “/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py”, line 1190, in _call_impl return forward_call(*input, **kwargs) File “/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/openaimodel.py”, line 84, in forward x = layer(x, context) File “/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py”, line 1190, in _call_impl return forward_call(*input, **kwargs) File “/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/attention.py”, line 334, in forward x = block(x, context=context[i]) File “/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py”, line 1190, in _call_impl return forward_call(*input, **kwargs) File “/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_checkpoint.py”, line 4, in BasicTransformerBlock_forward return checkpoint(self._forward, x, context) File “/usr/local/lib/python3.8/dist-packages/torch/utils/checkpoint.py”, line 249, in checkpoint return CheckpointFunction.apply(function, preserve, *args) File “/usr/local/lib/python3.8/dist-packages/torch/utils/checkpoint.py”, line 107, in forward outputs = run_function(*args) File “/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/attention.py”, line 272, in _forward x = self.attn1(self.norm1(x), context=context if self.disable_self_attn else None) + x File “/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py”, line 1190, in _call_impl return forward_call(*input, **kwargs) File “/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_optimizations.py”, line 227, in xformers_attention_forward out = xformers.ops.memory_efficient_attention(q, k, v, attn_bias=None) File “/usr/local/lib/python3.8/dist-packages/xformers/ops/memory_efficient_attention.py”, line 967, in memory_efficient_attention return op.forward_no_grad( File “/usr/local/lib/python3.8/dist-packages/xformers/ops/memory_efficient_attention.py”, line 343, in forward_no_grad return cls.FORWARD_OPERATOR( File “/usr/local/lib/python3.8/dist-packages/xformers/ops/common.py”, line 11, in no_such_operator raise RuntimeError( RuntimeError: No such operator xformers::efficient_attention_forward_cutlass - did you forget to build xformers with python setup.py develop?

[TheLastBen]

fixed (for the T4 at least), re-run the requirements cell

[brian6091]

I’ve put the xformers wheels compiled by facebookresearch here:

https://github.com/brian6091/xformers-wheels/releases

This works on Google Colab for Tesla T4 (free) and A100 (premium).

Drop this in whatever cell you’re running the xformers install:

!pip install https://github.com/brian6091/xformers-wheels/releases/download/0.0.15.dev0%2B4c06c79/xformers-0.0.15.dev0+4c06c79.d20221205-cp38-cp38-linux_x86_64.whl