RuntimeError: mat1 and mat2 must have the same dtype, but got Float and Half

[Marc0ai]

Can someone please help me resolve or at least understand where and why this error occurs?
Apparently both "Float and "Half" are used but I can't understand why the problem occurs, since I configured everything exactly as in the instructions.

Right now I'm on Forge and I'm using ControlNet v1.1.455 (the official one, not the Forge Built-in one).

The preprocessors and model work as they give me the preview of the unit.

The problem only occurs when I try to use "instant_id_face_embedding" with "ip-adapter_instant_id_sdxl [eb2d3ec0]".

Forge is up to date, ControlNet is up to date.

I already checked, there are no conflicts with other extensions.

Can anyone help me understand? Thanks in advance.

This is the Error Log.

Traceback (most recent call last):
File "F:\Forge\modules_forge\main_thread.py", line 37, in loop
task.work()
File "F:\Forge\modules_forge\main_thread.py", line 26, in work
self.result = self.func(*self.args, **self.kwargs)
File "F:\Forge\modules\txt2img.py", line 111, in txt2img_function
processed = processing.process_images(p)
File "F:\Forge\modules\processing.py", line 752, in process_images
res = process_images_inner(p)
File "F:\Forge\extensions\sd-webui-controlnet-main\scripts\batch_hijack.py", line 59, in processing_process_images_hijack
return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
File "F:\Forge\modules\processing.py", line 922, 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 "F:\Forge\extensions\sd-webui-controlnet-main\scripts\hook.py", line 470, in process_sample
return process.sample_before_CN_hack(*args, **kwargs)
File "F:\Forge\modules\processing.py", line 1275, in sample
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
File "F:\Forge\modules\sd_samplers_kdiffusion.py", line 251, 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 "F:\Forge\modules\sd_samplers_common.py", line 263, in launch_sampling
return func()
File "F:\Forge\modules\sd_samplers_kdiffusion.py", line 251, 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 "F:\Forge\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "F:\Forge\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "F:\Forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self.call_impl(*args, **kwargs)
File "F:\Forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in call_impl
return forward_call(*args, **kwargs)
File "F:\Forge\modules\sd_samplers_cfg_denoiser.py", line 182, in forward
denoised = forge_sampler.forge_sample(self, denoiser_params=denoiser_params,
File "F:\Forge\modules_forge\forge_sampler.py", line 88, in forge_sample
denoised = sampling_function(model, x, timestep, uncond, cond, cond_scale, model_options, seed)
File "F:\Forge\ldm_patched\modules\samplers.py", line 289, in sampling_function
cond_pred, uncond_pred = calc_cond_uncond_batch(model, cond, uncond, x, timestep, model_options)
File "F:\Forge\ldm_patched\modules\samplers.py", line 258, in calc_cond_uncond_batch
output = model.apply_model(input_x, timestep, **c).chunk(batch_chunks)
File "F:\Forge\ldm_patched\modules\model_base.py", line 90, in apply_model
model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, **extra_conds).float()
File "F:\Forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "F:\Forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "F:\Forge\extensions\sd-webui-controlnet-main\scripts\hook.py", line 905, in forward_webui
raise e
File "F:\Forge\extensions\sd-webui-controlnet-main\scripts\hook.py", line 902, in forward_webui
return forward(*args, **kwargs)
File "F:\Forge\extensions\sd-webui-controlnet-main\scripts\hook.py", line 800, in forward
emb = self.time_embed(t_emb)
File "F:\Forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "F:\Forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "F:\Forge\venv\lib\site-packages\torch\nn\modules\container.py", line 215, in forward
input = module(input)
File "F:\Forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "F:\Forge\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "F:\Forge\ldm_patched\modules\ops.py", line 98, in forward
return super().forward(*args, **kwargs)
File "F:\Forge\venv\lib\site-packages\torch\nn\modules\linear.py", line 114, in forward
return F.linear(input, self.weight, self.bias)
RuntimeError: mat1 and mat2 must have the same dtype, but got Float and Half
mat1 and mat2 must have the same dtype, but got Float and Half
*** Error completing request
*** Arguments: ('task(b2b0ehyxjn8aeke)', <gradio.routes.Request object at 0x000001F6F10C5AB0>, 'score_9, score_8_up, score_7_up, score_6_up, score_5_up, score_4_up,\nredhead girl, slim body, long hair, portrait, looking at viewer,', '', [], 20, 'Euler a', 1, 1, 4, 832, 1024, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', '', '', [], 0, False, '', 0.8, -1, False, -1, 0, 0, 0, False, False, {'ad_model': 'face_yolov8n.pt', 'ad_model_classes': '', 'ad_tab_enable': True, 'ad_prompt': '', 'ad_negative_prompt': '', 'ad_confidence': 0.75, 'ad_mask_k_largest': 0, 'ad_mask_min_ratio': 0, 'ad_mask_max_ratio': 1, 'ad_x_offset': 0, 'ad_y_offset': 0, 'ad_dilate_erode': 4, 'ad_mask_merge_invert': 'None', 'ad_mask_blur': 4, 'ad_denoising_strength': 0.35, 'ad_inpaint_only_masked': True, 'ad_inpaint_only_masked_padding': 32, 'ad_use_inpaint_width_height': True, 'ad_inpaint_width': 1024, 'ad_inpaint_height': 1024, 'ad_use_steps': False, 'ad_steps': 28, 'ad_use_cfg_scale': False, 'ad_cfg_scale': 7, 'ad_use_checkpoint': False, 'ad_checkpoint': 'Use same checkpoint', 'ad_use_vae': False, 'ad_vae': 'Use same VAE', 'ad_use_sampler': False, 'ad_sampler': 'DPM++ 2M Karras', 'ad_scheduler': 'Use same scheduler', 'ad_use_noise_multiplier': False, 'ad_noise_multiplier': 1, 'ad_use_clip_skip': False, 'ad_clip_skip': 1, 'ad_restore_face': False, 'ad_controlnet_model': 'None', 'ad_controlnet_module': 'None', 'ad_controlnet_weight': 1, 'ad_controlnet_guidance_start': 0, 'ad_controlnet_guidance_end': 1, 'is_api': ()}, ControlNetUnit(is_ui=True, input_mode=<InputMode.SIMPLE: 'simple'>, batch_images='', output_dir='', loopback=False, enabled=True, module='instant_id_face_embedding', model='ip-adapter_instant_id_sdxl [eb2d3ec0]', weight=1.0, image={'image': array([[[ 49, 52, 59],
*** [ 49, 52, 59],
*** [ 49, 52, 59],
*** ...,
*** [234, 237, 244],
*** [238, 239, 244],
*** [238, 239, 244]],

---

*** [[ 49, 52, 59],
*** [ 49, 52, 59],
*** [ 49, 52, 59],
*** ...,
*** [234, 237, 242],
*** [238, 239, 244],
*** [238, 239, 244]],

---

*** [[ 49, 52, 59],
*** [ 49, 52, 59],
*** [ 49, 52, 59],
*** ...,
*** [234, 237, 242],
*** [238, 239, 244],
*** [238, 239, 243]],

---

*** ...,

---

*** [[ 77, 45, 34],
*** [ 67, 37, 27],
*** [ 57, 30, 21],
*** ...,
*** [ 33, 32, 37],
*** [ 32, 33, 37],
*** [ 32, 33, 37]],

---

*** [[ 73, 43, 33],
*** [ 65, 37, 26],
*** [ 57, 30, 21],
*** ...,
*** [ 33, 32, 37],
*** [ 32, 33, 37],
*** [ 32, 33, 37]],

---

*** [[ 71, 41, 31],
*** [ 64, 36, 25],
*** [ 56, 29, 22],
*** ...,
*** [ 33, 32, 37],
*** [ 32, 33, 37],
*** [ 32, 33, 37]]], dtype=uint8), 'mask': array([[[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],

---

*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],

---

*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],

---

*** ...,

---

*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],

---

*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]],

---

*** [[0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0],
*** ...,
*** [0, 0, 0],
*** [0, 0, 0],
*** [0, 0, 0]]], dtype=uint8)}, resize_mode=<ResizeMode.INNER_FIT: 'Crop and Resize'>, low_vram=True, processor_res=512, threshold_a=0.5, threshold_b=0.5, guidance_start=0.0, guidance_end=1.0, pixel_perfect=False, control_mode=<ControlMode.BALANCED: 'Balanced'>, inpaint_crop_input_image=False, hr_option=<HiResFixOption.BOTH: 'Both'>, save_detected_map=True, advanced_weighting=None, effective_region_mask=None, pulid_mode=<PuLIDMode.FIDELITY: 'Fidelity'>, union_control_type=<ControlNetUnionControlType.UNKNOWN: 'Unknown'>, ipadapter_input=None, mask=None, batch_mask_dir=None, animatediff_batch=False, batch_modifiers=[], batch_image_files=[], batch_keyframe_idx=None), ControlNetUnit(is_ui=True, input_mode=<InputMode.SIMPLE: 'simple'>, batch_images='', output_dir='', loopback=False, enabled=False, module='none', model='None', weight=1.0, image=None, resize_mode=<ResizeMode.INNER_FIT: 'Crop and Resize'>, low_vram=False, processor_res=-1, threshold_a=-1.0, threshold_b=-1.0, guidance_start=0.0, guidance_end=1.0, pixel_perfect=False, control_mode=<ControlMode.BALANCED: 'Balanced'>, inpaint_crop_input_image=False, hr_option=<HiResFixOption.BOTH: 'Both'>, save_detected_map=True, advanced_weighting=None, effective_region_mask=None, pulid_mode=<PuLIDMode.FIDELITY: 'Fidelity'>, union_control_type=<ControlNetUnionControlType.UNKNOWN: 'Unknown'>, ipadapter_input=None, mask=None, batch_mask_dir=None, animatediff_batch=False, batch_modifiers=[], batch_image_files=[], batch_keyframe_idx=None), ControlNetUnit(is_ui=True, input_mode=<InputMode.SIMPLE: 'simple'>, batch_images='', output_dir='', loopback=False, enabled=False, module='none', model='None', weight=1.0, image=None, resize_mode=<ResizeMode.INNER_FIT: 'Crop and Resize'>, low_vram=False, processor_res=-1, threshold_a=-1.0, threshold_b=-1.0, guidance_start=0.0, guidance_end=1.0, pixel_perfect=False, control_mode=<ControlMode.BALANCED: 'Balanced'>, inpaint_crop_input_image=False, hr_option=<HiResFixOption.BOTH: 'Both'>, save_detected_map=True, advanced_weighting=None, effective_region_mask=None, pulid_mode=<PuLIDMode.FIDELITY: 'Fidelity'>, union_control_type=<ControlNetUnionControlType.UNKNOWN: 'Unknown'>, ipadapter_input=None, mask=None, batch_mask_dir=None, animatediff_batch=False, batch_modifiers=[], batch_image_files=[], batch_keyframe_idx=None), True, None, False, '0,1,2,3', '0,1,2,3', 'inswapper_128.onnx', 'CodeFormer', 0.9, True, 'None', 1, 1, False, True, 1, 0, 0, False, 1, True, False, 'CUDA', True, 0, 'None', '', None, False, False, 0.5, 0, 'tab_single', False, False, 'positive', 'comma', 0, False, False, 'start', '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, False, False, False, 0, False, None, None, False, None, None, False, None, None, False, 50) {}
Traceback (most recent call last):
File "F:\Forge\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
TypeError: 'NoneType' object is not iterable

[dlsccc]

I got the same problem. Have you solved it ?