RuntimeError: mat1 and mat2 shapes cannot be multiplied (16x768 and 512x128)

[Thesaltedfish-single]

Data shape for DDIM sampling is (1, 4, 64, 64), eta 0.0
Running DDIM Sampling with 50 timesteps
DDIM Sampler: 0%| | 0/50 [00:00<?, ?it/s]
0it [00:04, ?it/s]| | 0/50 [00:00<?, ?it/s]
Traceback (most recent call last):
File "/root/miniconda3/lib/python3.8/runpy.py", line 194, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/root/miniconda3/lib/python3.8/runpy.py", line 87, in _run_code
exec(code, run_globals)
File "/root/.vscode-server/extensions/ms-python.debugpy-2024.12.0-linux-x64/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/main.py", line 71, in
cli.main()
File "/root/.vscode-server/extensions/ms-python.debugpy-2024.12.0-linux-x64/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/../debugpy/server/cli.py", line 501, in main
run()
File "/root/.vscode-server/extensions/ms-python.debugpy-2024.12.0-linux-x64/bundled/libs/debugpy/adapter/../../debugpy/launcher/../../debugpy/../debugpy/server/cli.py", line 351, in run_file
runpy.run_path(target, run_name="main")
File "/root/.vscode-server/extensions/ms-python.debugpy-2024.12.0-linux-x64/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 310, in run_path
return _run_module_code(code, init_globals, run_name, pkg_name=pkg_name, script_name=fname)
File "/root/.vscode-server/extensions/ms-python.debugpy-2024.12.0-linux-x64/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 127, in _run_module_code
_run_code(code, mod_globals, init_globals, mod_name, mod_spec, pkg_name, script_name)
File "/root/.vscode-server/extensions/ms-python.debugpy-2024.12.0-linux-x64/bundled/libs/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_runpy.py", line 118, in _run_code
exec(code, run_globals)
File "/root/autodl-tmp/UniHuman/code/infer.py", line 488, in
result=process('Pose Transfer',opt.seed,src_image,tgt_image,clothes=None,prompt=None,tryon_cat=None,edit_cat=None,ug_scale=opt.cfg_scale)
File "/root/autodl-tmp/UniHuman/code/infer.py", line 440, in process
results=model.edit_human(batch,ug_scale=ug_scale,task=task,ddim_steps=50)
File "/root/autodl-tmp/UniHuman/code/unihuman.py", line 32, in edit_human
results=self.model.log_images(batch,N=len(batch),sample=False,unconditional_guidance_scale=ug_scale,ddim_steps=ddim_steps,
File "/root/miniconda3/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/root/autodl-tmp/UniHuman/code/cldm/model512.py", line 645, in log_images
samples_cfg, _ = self.sample_log(cond=cond,
File "/root/miniconda3/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/root/autodl-tmp/UniHuman/code/cldm/model512.py", line 661, in sample_log
samples, intermediates = ddim_sampler.sample(ddim_steps, batch_size, shape, cond, verbose=False, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/root/autodl-tmp/UniHuman/code/ldm/models/diffusion/ddim.py", line 106, in sample
samples, intermediates = self.ddim_sampling(conditioning, size,
File "/root/miniconda3/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/root/autodl-tmp/UniHuman/code/ldm/models/diffusion/ddim.py", line 168, in ddim_sampling
outs = self.p_sample_ddim(img, cond, ts, index=index, use_original_steps=ddim_use_original_steps,
File "/root/miniconda3/lib/python3.8/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/root/autodl-tmp/UniHuman/code/ldm/models/diffusion/ddim.py", line 218, in p_sample_ddim
model_uncond, model_t = self.model.apply_model(x_in, t_in, c_in).chunk(2)
File "/root/autodl-tmp/UniHuman/code/cldm/model512.py", line 557, in apply_model
cond_tex=self.encode_tex_images(cond_tex,seg)
File "/root/autodl-tmp/UniHuman/code/cldm/model512.py", line 491, in encode_tex_images
cls_emd=self.control_model.clip_cls_adaptor(cls_emd)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
return forward_call(*input, **kwargs)
File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/linear.py", line 114, in forward
return F.linear(input, self.weight, self.bias)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (16x768 and 512x128)

This error was prompted when I was running infer.py with
parser = argparse.ArgumentParser()
parser.add_argument("--src-img-list", type=str, default='/root/autodl-tmp/UniHuman/code/source_img_paths.txt')
parser.add_argument("--tgt-img-list", type=str, default='/root/autodl-tmp/UniHuman/code/tgt_img_paths.txt')
parser.add_argument("--tgt-clothes-list", type=str, default='')
parser.add_argument("--prompt-list", type=str, default='')
parser.add_argument("--task", type=str, default='reposing')
parser.add_argument("--out-dir", type=str, default='./results')
parser.add_argument("--tryon-cat", type=str, default='upper')
parser.add_argument("--edit-cat", type=str, default='upper')
parser.add_argument("--seed", type=int, default=12345)
parser.add_argument("--cfg_scale", type=int, default=2)
opt = parser.parse_args()