Problem about design_ppi_scaffolded.sh in the example

Hi! I met a problem when I tried to run the design_ppi_scaffolded.sh in the example directory:
/RFdiffusion/rfdiffusion/util.py:253: UserWarning: Using torch.cross without specifying the dim arg is deprecated.
Please either pass the dim explicitly or simply use torch.linalg.cross.
The default value of dim will change to agree with that of linalg.cross in a future release. (Triggered internally at ../aten/src/ATen/native/Cross.cpp:62.)
Z = torch.cross(Xn, Yn)
[2024-08-28 18:18:40,402][main][INFO] - Found GPU with device_name NVIDIA RTX A6000. Will run RFdiffusion on NVIDIA RTX A6000
Reading models from /home/gaon/biosoftware/RFdiffusion/rfdiffusion/inference/../../models
[2024-08-28 18:18:40,403][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/gaon/biosoftware/RFdiffusion/rfdiffusion/inference/../../models/Complex_Fold_base_ckpt.pt
This is inf_conf.ckpt_path
/home/gaon/biosoftware/RFdiffusion/rfdiffusion/inference/../../models/Complex_Fold_base_ckpt.pt
Assembling -model, -diffuser and -preprocess configs from checkpoint
USING MODEL CONFIG: self._conf[model][n_extra_block] = 4
USING MODEL CONFIG: self._conf[model][n_main_block] = 32
USING MODEL CONFIG: self._conf[model][n_ref_block] = 4
USING MODEL CONFIG: self._conf[model][d_msa] = 256
USING MODEL CONFIG: self._conf[model][d_msa_full] = 64
USING MODEL CONFIG: self._conf[model][d_pair] = 128
USING MODEL CONFIG: self._conf[model][d_templ] = 64
USING MODEL CONFIG: self._conf[model][n_head_msa] = 8
USING MODEL CONFIG: self._conf[model][n_head_pair] = 4
USING MODEL CONFIG: self._conf[model][n_head_templ] = 4
USING MODEL CONFIG: self._conf[model][d_hidden] = 32
USING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32
USING MODEL CONFIG: self._conf[model][p_drop] = 0.15
USING MODEL CONFIG: self._conf[model][SE3_param_full] = {'num_layers': 1, 'num_channels': 32, 'num_degrees': 2, 'n_heads': 4, 'div': 4, 'l0_in_features': 8, 'l0_out_features': 8, 'l1_in_features': 3, 'l1_out_features': 2, 'num_edge_features': 32}
USING MODEL CONFIG: self._conf[model][SE3_param_topk] = {'num_layers': 1, 'num_channels': 32, 'num_degrees': 2, 'n_heads': 4, 'div': 4, 'l0_in_features': 64, 'l0_out_features': 64, 'l1_in_features': 3, 'l1_out_features': 2, 'num_edge_features': 64}
USING MODEL CONFIG: self._conf[model][freeze_track_motif] = False
USING MODEL CONFIG: self._conf[model][use_motif_timestep] = True
USING MODEL CONFIG: self._conf[diffuser][T] = 50
USING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01
USING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07
USING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear
USING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3
USING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25
USING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear
USING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5
USING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5
USING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02
USING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5
USING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False
USING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True
USING MODEL CONFIG: self._conf[preprocess][d_t1d] = 28
USING MODEL CONFIG: self._conf[preprocess][d_t2d] = 47
USING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5
USING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True
USING MODEL CONFIG: self._conf[preprocess][predict_previous] = False
[2024-08-28 18:19:15,161][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.
[2024-08-28 18:19:15,337][rfdiffusion.diffusion][INFO] - Using cached IGSO3.
Successful diffuser init
Error executing job with overrides: ['scaffoldguided.target_path=input_pdbs/insulin_target.pdb', 'inference.output_prefix=example_outputs/design_ppi_scaffolded', 'scaffoldguided.scaffoldguided=True', 'ppi.hotspot_res=[A59,A83,A91]', 'scaffoldguided.target_pdb=True', 'scaffoldguided.target_ss=target_folds/insulin_target_ss.pt', 'scaffoldguided.target_adj=target_folds/insulin_target_adj.pt', 'scaffoldguided.scaffold_dir=./ppi_scaffolds/', 'inference.num_designs=10', 'denoiser.noise_scale_ca=0', 'denoiser.noise_scale_frame=0']
Traceback (most recent call last):
File "/home/gaon/biosoftware/RFdiffusion/examples/../scripts/run_inference.py", line 54, in main
sampler = iu.sampler_selector(conf)
File "/home/gaon/biosoftware/RFdiffusion/rfdiffusion/inference/utils.py", line 506, in sampler_selector
sampler = model_runners.ScaffoldedSampler(conf)
File "/home/gaon/biosoftware/RFdiffusion/rfdiffusion/inference/model_runners.py", line 751, in init
self.blockadjacency = iu.BlockAdjacency(conf.scaffoldguided, conf.inference.num_designs)
File "/home/gaon/biosoftware/RFdiffusion/rfdiffusion/inference/utils.py", line 694, in init
if self.conf.scaffoldguided.scaffold_list is not None:
AttributeError: 'bool' object has no attribute 'scaffold_list'
Could anyone please help me about this problem? Thank you!

Start by running examples/design_ppi_scaffolded.sh and reading scripts/run_inference.py, rfdiffusion/inference/utils.py, and rfdiffusion/inference/model_runners.py around ScaffoldedSampler and BlockAdjacency. Trace the scaffoldguided configuration passed during sampler initialization; done means the example gets past the reported AttributeError and produces its requested designs.