RuntimeError: Tensors must have same number of dimensions: got 4 and 3 error

[Joeyd348039]

When I use some of the t2i Adapter scripts I keep running into these type of tensor dimension errors.

Here is the error I get:
Loaded state_dict from [C:\ai\stable-diffusion-webui-ux\extensions\sd-webui-controlnet\annotator\downloads\pidinet\table5_pidinet.pth]
0%| | 0/40 [00:00<?, ?it/s]
Error completing request

Traceback (most recent call last):
File "C:\ai\stable-diffusion-webui-ux\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
File "C:\ai\stable-diffusion-webui-ux\modules\call_queue.py", line 37, in f
res = func(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\modules\txt2img.py", line 57, in txt2img
processed = processing.process_images(p)
File "C:\ai\stable-diffusion-webui-ux\modules\processing.py", line 611, in process_images
res = process_images_inner(p)
File "C:\ai\stable-diffusion-webui-ux\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 "C:\ai\stable-diffusion-webui-ux\modules\processing.py", line 729, 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 "C:\ai\stable-diffusion-webui-ux\extensions\sd-webui-controlnet\scripts\hook.py", line 291, in process_sample
return process.sample_before_CN_hack(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\modules\processing.py", line 977, in sample
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
File "C:\ai\stable-diffusion-webui-ux\modules\sd_samplers_kdiffusion.py", line 383, in sample
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
File "C:\ai\stable-diffusion-webui-ux\modules\sd_samplers_kdiffusion.py", line 257, in launch_sampling
return func()
File "C:\ai\stable-diffusion-webui-ux\modules\sd_samplers_kdiffusion.py", line 383, in
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
File "C:\ai\stable-diffusion-webui-ux\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "C:\ai\stable-diffusion-webui-ux\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\modules\sd_samplers_kdiffusion.py", line 137, in forward
x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict([cond_in], image_cond_in))
File "C:\ai\stable-diffusion-webui-ux\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\repositories\k-diffusion\k_diffusion\external.py", line 112, in forward
eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
File "C:\ai\stable-diffusion-webui-ux\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
return self.inner_model.apply_model(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\modules\sd_hijack_utils.py", line 17, in
setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
File "C:\ai\stable-diffusion-webui-ux\modules\sd_hijack_utils.py", line 28, in call
return self.__orig_func(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
x_recon = self.model(x_noisy, t, **cond)
File "C:\ai\stable-diffusion-webui-ux\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335, in forward
out = self.diffusion_model(x, t, context=cc)
File "C:\ai\stable-diffusion-webui-ux\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\extensions\sd-webui-controlnet\scripts\hook.py", line 587, in forward_webui
return forward(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\extensions\sd-webui-controlnet\scripts\hook.py", line 369, in forward
control = param.control_model(x=x, hint=param.used_hint_cond, timesteps=timesteps, context=context)
File "C:\ai\stable-diffusion-webui-ux\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\extensions\sd-webui-controlnet\scripts\adapter.py", line 104, in forward
self.control = self.control_model(hint_in)
File "C:\ai\stable-diffusion-webui-ux\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\ai\stable-diffusion-webui-ux\extensions\sd-webui-controlnet\scripts\adapter.py", line 324, in forward
x = torch.cat([x, style_embedding], dim=1)
RuntimeError: Tensors must have same number of dimensions: got 4 and 3

---

I also seem to get other weird things going on with the preprocessor preview showing a static noise image too.

[lllyasviel]

From the log, the error is not from the latest version of CN. Please update and make sure you see at least 1.1.214. If problem is still, will reopen

[Joeyd348039]

From the log, the error is not from the latest version of CN. Please update and make sure you see at least 1.1.214. If problem is still, will reopen

I did that. Seemed to fix some and still break others. I get "outside of cache" errors a lot now.
Like "Calling preprocessor clip_vision outside of cache." and the preprocessor image is nothing but black and white noise.

Forgot to mention , I'm still getting that Tensors error on some of the Controlnet scripts, but the preprocessor preview still works properly.

[1998-BossLee]

macbook pro m1.

I has the similar problem, I git pull the newest code. v1.1.224, then I want to preprocess 【depth_leres++】。
First，tip me to download 【https://huggingface.co/lllyasviel/Annotators/resolve/main/res101.pth】，my network can't connect, so I go to huggingface download it, put it in 【/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/downloads/leres/res101.pth】.
Second, I download 【latest_net_G.pth】 in the same way。
Then I get this error【RuntimeError: Input type (MPSFloatType) and weight type (torch.FloatTensor) should be the same】。
Third, I git pull【stable diffusion】this project，restart，can't slove this error。

who can help me? Thanks。
2023-06-13 16:03:17,218 - ControlNet - INFO - Preview Resolution = 512
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/gradio/routes.py", line 422, in run_predict
output = await app.get_blocks().process_api(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/gradio/blocks.py", line 1323, in process_api
result = await self.call_function(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/gradio/blocks.py", line 1051, in call_function
prediction = await anyio.to_thread.run_sync(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/anyio/to_thread.py", line 31, in run_sync
return await get_asynclib().run_sync_in_worker_thread(
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 937, in run_sync_in_worker_thread
return await future
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/anyio/_backends/_asyncio.py", line 867, in run
result = context.run(func, *args)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/controlnet_ui/controlnet_ui_group.py", line 632, in run_annotator
result, is_image = preprocessor(
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/utils.py", line 76, in decorated_func
return cached_func(*args, **kwargs)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/utils.py", line 64, in cached_func
return func(*args, **kwargs)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/global_state.py", line 35, in unified_preprocessor
return preprocessor_modules[preprocessor_name](*args, **kwargs)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/processor.py", line 211, in leres
result = model_leres(img, thr_a, thr_b, boost=boost)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/leres/init.py", line 79, in apply_leres
depth = estimateboost(input_image, model, 0, pix2pixmodel, max(width, height))
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/leres/leres/depthmap.py", line 418, in estimateboost
whole_estimate = doubleestimate(img, net_receptive_field_size, whole_image_optimal_size, pix2pixsize, model, model_type, pix2pixmodel)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/leres/leres/depthmap.py", line 132, in doubleestimate
estimate1 = singleestimate(img, size1, model, net_type)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/leres/leres/depthmap.py", line 156, in singleestimate
return estimateleres(img, model, msize, msize)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/leres/leres/depthmap.py", line 43, in estimateleres
prediction = model.depth_model(img_torch)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/leres/leres/multi_depth_model_woauxi.py", line 32, in forward
lateral_out = self.encoder_modules(x)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/leres/leres/network_auxi.py", line 96, in forward
x = self.encoder(x) # 1/32, 1/16, 1/8, 1/4
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/leres/leres/Resnext_torch.py", line 223, in forward
return self._forward_impl(x)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions/sd-webui-controlnet/annotator/leres/leres/Resnext_torch.py", line 199, in _forward_impl
x = self.conv1(x)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "/Users/liyangjin/Desktop/AIDraw/stable-diffusion-webui/extensions-builtin/Lora/lora.py", line 415, in lora_Conv2d_forward
return torch.nn.Conv2d_forward_before_lora(self, input)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 463, in forward
return self._conv_forward(input, self.weight, self.bias)
File "/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 459, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: Input type (MPSFloatType) and weight type (torch.FloatTensor) should be the same