Can't use Conditioning (Combine) when latent batch 1

It's fine when latent batch more then 1, It's fine when only one CLIPTextEncode.

But when i use two CLIPTextEncode combine pass Conditioning will crash:

Error occurred when executing KSampler:

shape '[3, -1, 8, 40]' is invalid for input of size 2560

File "/home/h3c/Documents/ComfyUI/execution.py", line 152, in recursive_execute output_data, output_ui = get_output_data(obj, input_data_all) File "/home/h3c/Documents/ComfyUI/execution.py", line 82, in get_output_data return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True) File "/home/h3c/Documents/ComfyUI/execution.py", line 75, in map_node_over_list results.append(getattr(obj, func)(slice_dict(input_data_all, i))) File "/home/h3c/Documents/ComfyUI/nodes.py", line 1236, in sample return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise) File "/home/h3c/Documents/ComfyUI/nodes.py", line 1206, in common_ksampler samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, File "/home/h3c/Documents/ComfyUI/custom_nodes/ComfyUI-Impact-Pack/modules/impact/hacky.py", line 22, in informative_sample raise e File "/home/h3c/Documents/ComfyUI/custom_nodes/ComfyUI-Impact-Pack/modules/impact/hacky.py", line 9, in informative_sample return original_sample(*args, *kwargs) File "/home/h3c/Documents/ComfyUI/comfy/sample.py", line 93, in sample samples = sampler.sample(noise, positive_copy, negative_copy, cfg=cfg, latent_image=latent_image, start_step=start_step, last_step=last_step, force_full_denoise=force_full_denoise, denoise_mask=noise_mask, sigmas=sigmas, callback=callback, disable_pbar=disable_pbar, seed=seed) File "/home/h3c/Documents/ComfyUI/comfy/samplers.py", line 742, in sample samples = getattr(k_diffusionsampling, "sample{}".format(self.sampler))(self.model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar) File "/home/h3c/.local/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context return func(args, kwargs) File "/home/h3c/Documents/ComfyUI/comfy/k_diffusion/sampling.py", line 580, in sample_dpmpp_2m denoised = model(x, sigmas[i] * s_in, extra_args) File "/home/h3c/.local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, *kwargs) File "/home/h3c/Documents/ComfyUI/comfy/samplers.py", line 323, in forward out = self.inner_model(x, sigma, cond=cond, uncond=uncond, cond_scale=cond_scale, cond_concat=cond_concat, model_options=model_options, seed=seed) File "/home/h3c/.local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(args, kwargs) File "/home/h3c/Documents/ComfyUI/comfy/k_diffusion/external.py", line 125, in forward eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), kwargs) File "/home/h3c/Documents/ComfyUI/comfy/k_diffusion/external.py", line 151, in get_eps return self.inner_model.apply_model(args, kwargs) File "/home/h3c/Documents/ComfyUI/comfy/samplers.py", line 311, in apply_model out = sampling_function(self.inner_model.apply_model, x, timestep, uncond, cond, cond_scale, cond_concat, model_options=model_options, seed=seed) File "/home/h3c/Documents/ComfyUI/comfy/samplers.py", line 289, in sampling_function cond, uncond = calc_cond_uncond_batch(model_function, cond, uncond, x, timestep, max_total_area, cond_concat, model_options) File "/home/h3c/Documents/ComfyUI/comfy/samplers.py", line 265, in calc_cond_uncond_batch output = model_function(inputx, timestep, c).chunk(batch_chunks) File "/home/h3c/Documents/ComfyUI/comfy/model_base.py", line 63, in apply_model return self.diffusion_model(xc, t, context=context, y=c_adm, control=control, transformer_options=transformer_options).float() File "/home/h3c/.local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(args, kwargs) File "/home/h3c/Documents/ComfyUI/comfy/ldm/modules/diffusionmodules/openaimodel.py", line 626, in forward h = forward_timestep_embed(module, h, emb, context, transformer_options) File "/home/h3c/Documents/ComfyUI/comfy/ldm/modules/diffusionmodules/openaimodel.py", line 56, in forward_timestep_embed x = layer(x, context, transformer_options) File "/home/h3c/.local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, *kwargs) File "/home/h3c/Documents/ComfyUI/comfy/ldm/modules/attention.py", line 693, in forward x = block(x, context=context[i], transformer_options=transformer_options) File "/home/h3c/.local/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(args, *kwargs) File "/home/h3c/Documents/ComfyUI/comfy/ldm/modules/attention.py", line 525, in forward return checkpoint(self._forward, (x, context, transformer_options), self.parameters(), self.checkpoint) File "/home/h3c/Documents/ComfyUI/comfy/ldm/modules/diffusionmodules/util.py", line 123, in checkpoint return func(inputs) File "/home/h3c/Documents/ComfyUI/comfy/ldm/modules/attention.py", line 622, in _forward n = attn2_replace_patch[block_attn2](n, context_attn2, value_attn2, extra_options) File "/home/h3c/Documents/ComfyUI/custom_nodes/IPAdapter-ComfyUI/ip_adapter.py", line 287, in call ip_out = attention(q, ip_k, ip_v, extra_options) File "/home/h3c/Documents/ComfyUI/custom_nodes/IPAdapter-ComfyUI/ip_adapter.py", line 42, in attention q, k, v = map( File "/home/h3c/Documents/ComfyUI/custom_nodes/IPAdapter-ComfyUI/ip_adapter.py", line 43, in lambda t: t.view(b, -1, extra_options["n_heads"], extra_options["dim_head"]).transpose(1, 2),

laksjdjf / IPAdapter-ComfyUI

Can't use Conditioning (Combine) when latent batch 1 #31