Can't generate any photos? #2691
edwardk1234
started this conversation in
General
Replies: 1 comment
-
fixed |
Beta Was this translation helpful? Give feedback.
0 replies
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Uh oh!
There was an error while loading. Please reload this page.
-
Not sure what's the issue but I can't seem to be generating any photos. Can you please let me know how to fix it?
Thanks!
*** Error completing request
*** Arguments: ('task(djlibqzxlfpltib)', 'realistic portrait photo of beautiful woman ', '', [], 20, 'DPM++ 2M Karras', 1, 1, 7, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], <gradio.routes.Request object at 0x7bb6a0ead4e0>, 0, False, '', 0.8, -1, False, -1, 0, 0, 0, False, False, 'positive', 'comma', 0, False, False, 'start', '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0, False) {}
Traceback (most recent call last):
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/call_queue.py", line 36, in f
res = func(*args, **kwargs)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/txt2img.py", line 55, in txt2img
processed = processing.process_images(p)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 734, in process_images
res = process_images_inner(p)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/processing.py", line 868, 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 1142, 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 235, 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 261, in launch_sampling
return func()
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 235, 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 115, 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 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_samplers_cfg_denoiser.py", line 169, 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 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, 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_hijack_utils.py", line 17, 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 26, 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 48, in apply_model
return orig_func(self, x_noisy.to(devices.dtype_unet), t.to(devices.dtype_unet), cond, **kwargs).float()
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/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **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/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, 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/ldm/modules/diffusionmodules/openaimodel.py", line 776, in forward
h = module(h, emb, context)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/openaimodel.py", line 84, in forward
x = layer(x, context)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **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/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/attention.py", line 269, in forward
return checkpoint(self._forward, (x, context), self.parameters(), self.checkpoint)
File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/util.py", line 114, in checkpoint
return CheckpointFunction.apply(func, len(inputs), *args)
File "/usr/local/lib/python3.10/dist-packages/torch/autograd/function.py", line 539, in apply
return super().apply(*args, **kwargs) # type: ignore[misc]
File "/content/gdrive/MyDrive/sd/stablediffusion/ldm/modules/diffusionmodules/util.py", line 129, in forward
output_tensors = ctx.run_function(*ctx.input_tensors)
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/python3.10/dist-packages/torch/nn/modules/module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/usr/local/lib/python3.10/dist-packages/torch/nn/modules/module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "/content/gdrive/MyDrive/sd/stable-diffusion-webui/modules/sd_hijack_optimizations.py", line 496, 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 223, in memory_efficient_attention
return _memory_efficient_attention(
File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/init.py", line 321, in _memory_efficient_attention
return _memory_efficient_attention_forward(
File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/init.py", line 337, in _memory_efficient_attention_forward
op = _dispatch_fw(inp, False)
File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/dispatch.py", line 120, in _dispatch_fw
return _run_priority_list(
File "/usr/local/lib/python3.10/dist-packages/xformers/ops/fmha/dispatch.py", line 63, in _run_priority_list
raise NotImplementedError(msg)
NotImplementedError: No operator found for
memory_efficient_attention_forward
with inputs:query : shape=(2, 4096, 8, 40) (torch.float16)
key : shape=(2, 4096, 8, 40) (torch.float16)
value : shape=(2, 4096, 8, 40) (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 infoflshattF@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)
operator wasn't built - see
python -m xformers.info
for more infotritonflashattF
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)
operator wasn't built - see
python -m xformers.info
for more infotriton is not available
requires GPU with sm80 minimum compute capacity, e.g., A100/H100/L4
Only work on pre-MLIR triton for now
cutlassF
is not supported because:xFormers wasn't build with CUDA support
operator wasn't built - see
python -m xformers.info
for more infosmallkF
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 infounsupported embed per head: 40
Beta Was this translation helpful? Give feedback.
All reactions