IndexError: too many indices for tensor of dimension 0

I've been running into this issue:

(SE3nv) C:\Users\pc\RFdiffusion>python scripts/run_inference.py inference.output_prefix=outputs/Nav1.7_binder contigmap.contigs='1-100000' inference.input_pdb=C:\Users\pc\Downloads\RFdiffusion\vsdii_domain.pdb inference.num_designs=10
[2025-03-13 18:45:33,906][main][INFO] - Found GPU with device_name NVIDIA GeForce RTX 4060 Ti. Will run RFdiffusion on NVIDIA GeForce RTX 4060 Ti
Reading models from C:\Users\pc\miniconda3\envs\SE3nv\Lib\site-packages\rfdiffusion-1.1.0-py3.9.egg\rfdiffusion\inference/../../models
[2025-03-13 18:45:33,907][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from C:\Users\pc\miniconda3\envs\SE3nv\Lib\site-packages\rfdiffusion-1.1.0-py3.9.egg\rfdiffusion\inference/../../models/Base_ckpt.pt
This is inf_conf.ckpt_path
C:\Users\pc\miniconda3\envs\SE3nv\Lib\site-packages\rfdiffusion-1.1.0-py3.9.egg\rfdiffusion\inference/../../models/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] = 22
USING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44
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
[2025-03-13 18:45:36,627][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.
[2025-03-13 18:45:38,598][rfdiffusion.diffusion][INFO] - Using cached IGSO3.
Successful diffuser init
[2025-03-13 18:45:38,606][main][INFO] - Making design outputs/Nav1.7_binder_0
[2025-03-13 18:45:38,609][rfdiffusion.inference.model_runners][INFO] - Using contig: 1-100000
Error executing job with overrides: ['inference.output_prefix=outputs/Nav1.7_binder', "contigmap.contigs='1-100000'", 'inference.input_pdb=C:\Users\pc\Downloads\RFdiffusion\vsdii_domain.pdb', 'inference.num_designs=10']
Traceback (most recent call last):
File "C:\Users\pc\RFdiffusion\scripts\run_inference.py", line 194, in
main()
File "C:\Users\pc\miniconda3\envs\SE3nv\lib\site-packages\hydra\main.py", line 94, in decorated_main
_run_hydra(
File "C:\Users\pc\miniconda3\envs\SE3nv\lib\site-packages\hydra_internal\utils.py", line 394, in _run_hydra
_run_app(
File "C:\Users\pc\miniconda3\envs\SE3nv\lib\site-packages\hydra_internal\utils.py", line 457, in _run_app
run_and_report(
File "C:\Users\pc\miniconda3\envs\SE3nv\lib\site-packages\hydra_internal\utils.py", line 223, in run_and_report
raise ex
File "C:\Users\pc\miniconda3\envs\SE3nv\lib\site-packages\hydra_internal\utils.py", line 220, in run_and_report
return func()
File "C:\Users\pc\miniconda3\envs\SE3nv\lib\site-packages\hydra_internal\utils.py", line 458, in
lambda: hydra.run(
File "C:\Users\pc\miniconda3\envs\SE3nv\lib\site-packages\hydra_internal\hydra.py", line 132, in run
_ = ret.return_value
File "C:\Users\pc\miniconda3\envs\SE3nv\lib\site-packages\hydra\core\utils.py", line 260, in return_value
raise self._return_value
File "C:\Users\pc\miniconda3\envs\SE3nv\lib\site-packages\hydra\core\utils.py", line 186, in run_job
ret.return_value = task_function(task_cfg)
File "C:\Users\pc\RFdiffusion\scripts\run_inference.py", line 84, in main
x_init, seq_init = sampler.sample_init()
File "C:\Users\pc\miniconda3\envs\SE3nv\lib\site-packages\rfdiffusion-1.1.0-py3.9.egg\rfdiffusion\inference\model_runners.py", line 354, in sample_init
seq_t[contig_map.hal_idx0] = seq_orig[contig_map.ref_idx0]
IndexError: too many indices for tensor of dimension 0

Reproduce the reported command, then inspect scripts/run_inference.py and rfdiffusion/inference/model_runners.py around sample_init, especially the seq_t and seq_orig indexing at line 354. Trace the shapes produced by contig_map and initialization; done means the reported input no longer raises IndexError during inference.