{
"tests": {
"design_cyclic_oligos": {
"log": "Running design_cyclic_oligos\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_cyclic_oligos.sh\n/home/benchmark/working_dir/tmpnh_z5cop/lib/python3.9/site-packages/hydra/_internal/defaults_list.py:251: UserWarning: In 'symmetry': Defaults list is missing `_self_`. See https://hydra.cc/docs/1.2/upgrades/1.0_to_1.1/default_composition_order for more information\r\n warnings.warn(msg, UserWarning)\r\n[2023-08-22 16:12:11,272][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:12:11,272][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:12:11,272][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:12:11,273][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 22\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:12:39,823][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:12:40,029][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:12:40,313][rfdiffusion.inference.symmetry][INFO] - Initializing cyclic symmetry order 6.\r\n[2023-08-22 16:12:40,344][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/C6_oligo_0\r\n[2023-08-22 16:12:40,350][rfdiffusion.inference.model_runners][INFO] - Using contig: ['480-480']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:12:40,396][rfdiffusion.inference.model_runners][INFO] - Sequence init: ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:13:30,089][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:14:20,098][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:15:10,806][__main__][INFO] - Finished design in 2.51 minutes\r\n",
"state": "passed"
},
"design_dihedral_oligos": {
"log": "Running design_dihedral_oligos\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_dihedral_oligos.sh\n/home/benchmark/working_dir/tmpnh_z5cop/lib/python3.9/site-packages/hydra/_internal/defaults_list.py:251: UserWarning: In 'symmetry': Defaults list is missing `_self_`. See https://hydra.cc/docs/1.2/upgrades/1.0_to_1.1/default_composition_order for more information\r\n warnings.warn(msg, UserWarning)\r\n[2023-08-22 16:15:13,925][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:15:13,925][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:15:13,925][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:15:13,926][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 22\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:15:16,023][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:15:16,235][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:15:16,238][rfdiffusion.inference.symmetry][INFO] - Initializing dihedral symmetry order 2.\r\n[2023-08-22 16:15:16,246][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/D2_oligo_0\r\n[2023-08-22 16:15:16,251][rfdiffusion.inference.model_runners][INFO] - Using contig: ['320-320']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:15:16,286][rfdiffusion.inference.model_runners][INFO] - Sequence init: --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:15:39,634][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:16:02,061][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:16:24,955][__main__][INFO] - Finished design in 1.15 minutes\r\n",
"state": "passed"
},
"design_enzyme": {
"log": "Running design_enzyme\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_enzyme.sh\n[2023-08-22 16:16:28,077][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:16:28,077][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:16:28,077][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\nWARNING: You're overriding the checkpoint path from the defaults. Check that the model you're providing can run with the inputs you're providing.\r\n[2023-08-22 16:16:28,078][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from ../models/ActiveSite_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n../models/ActiveSite_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 22\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:16:35,303][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:16:35,514][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:16:35,701][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_enzyme_0\r\n[2023-08-22 16:16:35,751][rfdiffusion.inference.model_runners][INFO] - Using contig: ['10-100/A1083-1083/10-100/A1051-1051/10-100/A1180-1180/10-100']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:16:35,778][rfdiffusion.inference.model_runners][INFO] - Sequence init: -----------------------------------------------------------K---------------------------------------------------------------Y---------------Y-------------------------------------------\r\n[2023-08-22 16:16:42,646][rfdiffusion.inference.utils][INFO] - Sampled motif RMSD: 0.30\r\n[2023-08-22 16:16:42,654][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: -----------------------------------------------------------K---------------------------------------------------------------Y---------------Y-------------------------------------------\r\n[2023-08-22 16:16:48,655][rfdiffusion.inference.utils][INFO] - Sampled motif RMSD: 0.72\r\n[2023-08-22 16:16:48,664][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: -----------------------------------------------------------K---------------------------------------------------------------Y---------------Y-------------------------------------------\r\n[2023-08-22 16:16:54,854][__main__][INFO] - Finished design in 0.32 minutes\r\n",
"state": "passed"
},
"design_motifscaffolding": {
"log": "Running design_motifscaffolding\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_motifscaffolding.sh\n[2023-08-22 16:16:57,973][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:16:57,973][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:16:57,973][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:16:57,973][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 22\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:17:00,115][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:17:00,332][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:17:00,555][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_motifscaffolding_0\r\n[2023-08-22 16:17:00,742][rfdiffusion.inference.model_runners][INFO] - Using contig: ['10-40/A163-181/10-40']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:17:00,762][rfdiffusion.inference.model_runners][INFO] - Sequence init: -------------------------------------EVNKIKSALLSTNKAVVSL----------------------\r\n[2023-08-22 16:17:03,256][rfdiffusion.inference.utils][INFO] - Sampled motif RMSD: 0.30\r\n[2023-08-22 16:17:03,258][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: -------------------------------------EVNKIKSALLSTNKAVVSL----------------------\r\n[2023-08-22 16:17:04,953][rfdiffusion.inference.utils][INFO] - Sampled motif RMSD: 0.31\r\n[2023-08-22 16:17:04,955][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: -------------------------------------EVNKIKSALLSTNKAVVSL----------------------\r\n[2023-08-22 16:17:06,756][__main__][INFO] - Finished design in 0.10 minutes\r\n",
"state": "passed"
},
"design_motifscaffolding_inpaintseq": {
"log": "Running design_motifscaffolding_inpaintseq\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_motifscaffolding_inpaintseq.sh\n[2023-08-22 16:17:09,882][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:17:09,883][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:17:09,883][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:17:09,883][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/InpaintSeq_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/InpaintSeq_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 24\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:17:17,040][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:17:17,257][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:17:17,450][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_motifscaffolding_inpaintseq_0\r\n[2023-08-22 16:17:17,635][rfdiffusion.inference.model_runners][INFO] - Using contig: ['10-40/A163-181/10-40']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:17:17,658][rfdiffusion.inference.model_runners][INFO] - Sequence init: -------------------------------------------S--LSTNKAV-SL----------------------\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:17:20,176][rfdiffusion.inference.utils][INFO] - Sampled motif RMSD: 0.21\r\n[2023-08-22 16:17:20,179][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: -------------------------------------------S--LSTNKAV-SL----------------------\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:17:21,792][rfdiffusion.inference.utils][INFO] - Sampled motif RMSD: 0.22\r\n[2023-08-22 16:17:21,795][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: -------------------------------------------S--LSTNKAV-SL----------------------\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:17:23,504][__main__][INFO] - Finished design in 0.10 minutes\r\n",
"state": "passed"
},
"design_nickel": {
"log": "Running design_nickel\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_nickel.sh\n[2023-08-22 16:17:26,641][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:17:26,641][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:17:26,641][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\nWARNING: You're overriding the checkpoint path from the defaults. Check that the model you're providing can run with the inputs you're providing.\r\n[2023-08-22 16:17:26,642][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from ../models/Base_epoch8_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n../models/Base_epoch8_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 22\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:17:34,840][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:17:35,056][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:17:35,060][rfdiffusion.inference.symmetry][INFO] - Initializing cyclic symmetry order 4.\r\n[2023-08-22 16:17:35,130][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_nickel_0\r\n[2023-08-22 16:17:35,131][rfdiffusion.inference.model_runners][INFO] - Using contig: ['50/A2-4/50/0 50/A7-9/50/0 50/A12-14/50/0 50/A17-19/50/0']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:17:35,174][rfdiffusion.inference.model_runners][INFO] - Sequence init: --------------------------------------------------AHA----------------------------------------------------------------------------------------------------AHA----------------------------------------------------------------------------------------------------AHA----------------------------------------------------------------------------------------------------AHA--------------------------------------------------\r\n[2023-08-22 16:18:11,593][rfdiffusion.inference.utils][INFO] - Sampled motif RMSD: 1.24\r\n[2023-08-22 16:18:11,607][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: --------------------------------------------------AHA----------------------------------------------------------------------------------------------------AHA----------------------------------------------------------------------------------------------------AHA----------------------------------------------------------------------------------------------------AHA--------------------------------------------------\r\n[2023-08-22 16:18:48,745][rfdiffusion.inference.utils][INFO] - Sampled motif RMSD: 1.60\r\n[2023-08-22 16:18:48,759][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: --------------------------------------------------AHA----------------------------------------------------------------------------------------------------AHA----------------------------------------------------------------------------------------------------AHA----------------------------------------------------------------------------------------------------AHA--------------------------------------------------\r\n[2023-08-22 16:19:26,382][__main__][INFO] - Finished design in 1.85 minutes\r\n",
"state": "passed"
},
"design_partialdiffusion": {
"log": "Running design_partialdiffusion\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_partialdiffusion.sh\n[2023-08-22 16:19:29,519][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:19:29,519][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:19:29,519][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:19:29,520][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 22\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\nWARNING: You are changing diffuser.partial_T from the value this model was trained with. Are you sure you know what you are doing?\r\n[2023-08-22 16:19:31,708][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:19:31,925][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:19:31,983][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_partialdiffusion_0\r\n[2023-08-22 16:19:31,992][rfdiffusion.inference.model_runners][INFO] - Using contig: ['79-79']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:19:32,010][rfdiffusion.inference.model_runners][INFO] - Sequence init: -------------------------------------------------------------------------------\r\n[2023-08-22 16:19:34,559][rfdiffusion.inference.model_runners][INFO] - Timestep 10, input to next step: -------------------------------------------------------------------------------\r\n[2023-08-22 16:19:36,175][rfdiffusion.inference.model_runners][INFO] - Timestep 9, input to next step: -------------------------------------------------------------------------------\r\n[2023-08-22 16:19:37,878][__main__][INFO] - Finished design in 0.10 minutes\r\n",
"state": "passed"
},
"design_partialdiffusion_multipleseq": {
"log": "Running design_partialdiffusion_multipleseq\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_partialdiffusion_multipleseq.sh\n[2023-08-22 16:19:41,021][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:19:41,021][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:19:41,021][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:19:41,022][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/InpaintSeq_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/InpaintSeq_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 24\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\nWARNING: You are changing diffuser.partial_T from the value this model was trained with. Are you sure you know what you are doing?\r\n[2023-08-22 16:19:43,251][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:19:43,465][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:19:43,551][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_partialdiffusion_peptidewithmultiplesequence_0\r\n[2023-08-22 16:19:43,585][rfdiffusion.inference.model_runners][INFO] - Using contig: ['172-172/0 34-34']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:19:43,611][rfdiffusion.inference.model_runners][INFO] - Sequence init: ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------SVSEIQ----------------------QDVHNF\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:19:51,091][rfdiffusion.inference.model_runners][INFO] - Timestep 10, input to next step: ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------SVSEIQ----------------------QDVHNF\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:19:57,981][rfdiffusion.inference.model_runners][INFO] - Timestep 9, input to next step: ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------SVSEIQ----------------------QDVHNF\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:20:05,121][__main__][INFO] - Finished design in 0.36 minutes\r\n",
"state": "passed"
},
"design_partialdiffusion_withseq": {
"log": "Running design_partialdiffusion_withseq\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_partialdiffusion_withseq.sh\n[2023-08-22 16:20:08,330][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:20:08,330][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:20:08,330][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:20:08,330][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/InpaintSeq_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/InpaintSeq_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 24\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\nWARNING: You are changing diffuser.partial_T from the value this model was trained with. Are you sure you know what you are doing?\r\n[2023-08-22 16:20:10,500][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:20:10,717][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:20:10,755][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_partialdiffusion_peptidewithsequence_0\r\n[2023-08-22 16:20:10,789][rfdiffusion.inference.model_runners][INFO] - Using contig: ['172-172/0 34-34']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:20:10,816][rfdiffusion.inference.model_runners][INFO] - Sequence init: ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------SVSEIQLMHNLGKHLNSMERVEWLRKKLQDVHNF\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:20:18,666][rfdiffusion.inference.model_runners][INFO] - Timestep 10, input to next step: ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------SVSEIQLMHNLGKHLNSMERVEWLRKKLQDVHNF\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:20:25,625][rfdiffusion.inference.model_runners][INFO] - Timestep 9, input to next step: ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------SVSEIQLMHNLGKHLNSMERVEWLRKKLQDVHNF\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:20:33,026][__main__][INFO] - Finished design in 0.37 minutes\r\n",
"state": "passed"
},
"design_ppi": {
"log": "Running design_ppi\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_ppi.sh\n[2023-08-22 16:20:36,183][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:20:36,183][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:20:36,183][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:20:36,183][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/Complex_base_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/Complex_base_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 24\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:20:42,970][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:20:43,191][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:20:43,506][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_ppi_0\r\n[2023-08-22 16:20:43,527][rfdiffusion.inference.model_runners][INFO] - Using contig: ['A1-150/0 70-100']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:20:43,560][rfdiffusion.inference.model_runners][INFO] - Sequence init: -------------------------------------------------------------------------------------------------EVCPGMDIRNNLTRLHELENCSVIEGHLQILLMFKTRPEDFRDLSFPKLIMITDYLLLFRVYGLESLKDLFPNLTVIRGSRLFFNYALVIFEMVHLKELGLYNLMNITRGSVRIEKNNELCYLATIDWSRILDSVEDNHIVLNKDDNEEC\r\n[2023-08-22 16:20:54,017][rfdiffusion.inference.utils][INFO] - Sampled motif RMSD: 0.14\r\n[2023-08-22 16:20:54,020][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: -------------------------------------------------------------------------------------------------EVCPGMDIRNNLTRLHELENCSVIEGHLQILLMFKTRPEDFRDLSFPKLIMITDYLLLFRVYGLESLKDLFPNLTVIRGSRLFFNYALVIFEMVHLKELGLYNLMNITRGSVRIEKNNELCYLATIDWSRILDSVEDNHIVLNKDDNEEC\r\n[2023-08-22 16:21:03,389][rfdiffusion.inference.utils][INFO] - Sampled motif RMSD: 0.13\r\n[2023-08-22 16:21:03,392][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: -------------------------------------------------------------------------------------------------EVCPGMDIRNNLTRLHELENCSVIEGHLQILLMFKTRPEDFRDLSFPKLIMITDYLLLFRVYGLESLKDLFPNLTVIRGSRLFFNYALVIFEMVHLKELGLYNLMNITRGSVRIEKNNELCYLATIDWSRILDSVEDNHIVLNKDDNEEC\r\n[2023-08-22 16:21:13,167][__main__][INFO] - Finished design in 0.49 minutes\r\n",
"state": "passed"
},
"design_ppi_scaffolded": {
"log": "Running design_ppi_scaffolded\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_ppi_scaffolded.sh\n[2023-08-22 16:21:16,336][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:21:16,336][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:21:16,336][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:21:16,336][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/Complex_Fold_base_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/Complex_Fold_base_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 28\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 47\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:21:23,068][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:21:23,291][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:21:23,460][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_ppi_scaffolded_0\r\nError executing job with overrides: ['scaffoldguided.target_path=input_pdbs/insulin_target.pdb', 'inference.output_prefix=/home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/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=1', 'denoiser.noise_scale_ca=0', 'denoiser.noise_scale_frame=0', 'inference.deterministic=True', 'inference.final_step=48']\r\nTraceback (most recent call last):\r\n File \"/home/benchmark/rosetta/tests/../scripts/run_inference.py\", line 84, in main\r\n x_init, seq_init = sampler.sample_init()\r\n File \"/home/benchmark/rosetta/rfdiffusion/inference/model_runners.py\", line 776, in sample_init\r\n self.L, self.ss, self.adj = self.blockadjacency.get_scaffold()\r\n File \"/home/benchmark/rosetta/rfdiffusion/inference/utils.py\", line 891, in get_scaffold\r\n item = random.choice(self.scaffold_list)\r\n File \"/home/benchmark/prefix/nobu-4/ubuntu-20.04/python-3.9.gcc/99a1a29fd465f86265a7c5b92d75dbcd/lib/python3.9/random.py\", line 346, in choice\r\n return seq[self._randbelow(len(seq))]\r\nIndexError: list index out of range\r\n\r\nSet the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.\r\n",
"state": "failed"
},
"design_tetrahedral_oligos": {
"log": "Running design_tetrahedral_oligos\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_tetrahedral_oligos.sh\n/home/benchmark/working_dir/tmpnh_z5cop/lib/python3.9/site-packages/hydra/_internal/defaults_list.py:251: UserWarning: In 'symmetry': Defaults list is missing `_self_`. See https://hydra.cc/docs/1.2/upgrades/1.0_to_1.1/default_composition_order for more information\r\n warnings.warn(msg, UserWarning)\r\n[2023-08-22 16:21:26,939][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:21:26,939][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:21:26,939][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:21:26,940][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 22\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:21:29,215][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:21:29,438][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:21:29,441][rfdiffusion.inference.symmetry][INFO] - Initializing tetrahedral symmetry order.\r\n[2023-08-22 16:21:29,498][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/tetrahedral_oligo_0\r\n[2023-08-22 16:21:29,503][rfdiffusion.inference.model_runners][INFO] - Using contig: ['1200-1200']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:21:29,599][rfdiffusion.inference.model_runners][INFO] - Sequence init: ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:27:10,461][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:32:40,052][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:38:11,235][__main__][INFO] - Finished design in 16.70 minutes\r\n",
"state": "passed"
},
"design_timbarrel": {
"log": "Running design_timbarrel\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_timbarrel.sh\n[2023-08-22 16:38:14,386][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:38:14,386][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:38:14,386][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:38:14,386][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/Complex_Fold_base_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/Complex_Fold_base_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 28\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 47\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:38:16,610][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:38:16,821][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:38:16,980][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_tim_barrel_0\r\nScaffold constrained based on file: 6WVS\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:38:25,771][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:38:34,139][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------\r\nWARNING: you're using a model trained on complexes and hotspot residues, without specifying hotspots. If you're doing monomer diffusion this is fine\r\n[2023-08-22 16:38:43,027][__main__][INFO] - Finished design in 0.43 minutes\r\n",
"state": "passed"
},
"design_unconditional": {
"log": "Running design_unconditional\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_unconditional.sh\n[2023-08-22 16:38:46,318][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:38:46,318][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:38:46,318][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:38:46,319][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 22\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:38:48,674][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:38:48,902][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:38:48,913][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_unconditional_0\r\n[2023-08-22 16:38:48,919][rfdiffusion.inference.model_runners][INFO] - Using contig: ['100-200']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:38:48,943][rfdiffusion.inference.model_runners][INFO] - Sequence init: -----------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:38:53,915][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: -----------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:38:58,040][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: -----------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:39:02,379][__main__][INFO] - Finished design in 0.22 minutes\r\n",
"state": "passed"
},
"design_unconditional_w_contact_potential": {
"log": "Running design_unconditional_w_contact_potential\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_unconditional_w_contact_potential.sh\n[2023-08-22 16:39:05,753][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:39:05,753][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:39:05,753][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:39:05,753][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 22\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:39:08,113][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:39:08,335][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:39:08,346][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_unconditional_w_contact_potential_0\r\n[2023-08-22 16:39:08,352][rfdiffusion.inference.model_runners][INFO] - Using contig: ['100-200']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:39:08,376][rfdiffusion.inference.model_runners][INFO] - Sequence init: -----------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:39:13,643][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: -----------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:39:17,832][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: -----------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:39:22,190][__main__][INFO] - Finished design in 0.23 minutes\r\n",
"state": "passed"
},
"design_unconditional_w_monomer_ROG": {
"log": "Running design_unconditional_w_monomer_ROG\nCommand line: bash /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/design_unconditional_w_monomer_ROG.sh\n[2023-08-22 16:39:25,591][__main__][INFO] - ////////////////////////////////////////////////\r\n[2023-08-22 16:39:25,591][__main__][INFO] - ///// NO GPU DETECTED! Falling back to CPU /////\r\n[2023-08-22 16:39:25,591][__main__][INFO] - ////////////////////////////////////////////////\r\nReading models from /home/benchmark/rosetta/rfdiffusion/inference/../../models\r\n[2023-08-22 16:39:25,591][rfdiffusion.inference.model_runners][INFO] - Reading checkpoint from /home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nThis is inf_conf.ckpt_path\r\n/home/benchmark/rosetta/rfdiffusion/inference/../../models/Base_ckpt.pt\r\nAssembling -model, -diffuser and -preprocess configs from checkpoint\r\nUSING MODEL CONFIG: self._conf[model][n_extra_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_main_block] = 32\r\nUSING MODEL CONFIG: self._conf[model][n_ref_block] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_msa] = 256\r\nUSING MODEL CONFIG: self._conf[model][d_msa_full] = 64\r\nUSING MODEL CONFIG: self._conf[model][d_pair] = 128\r\nUSING MODEL CONFIG: self._conf[model][d_templ] = 64\r\nUSING MODEL CONFIG: self._conf[model][n_head_msa] = 8\r\nUSING MODEL CONFIG: self._conf[model][n_head_pair] = 4\r\nUSING MODEL CONFIG: self._conf[model][n_head_templ] = 4\r\nUSING MODEL CONFIG: self._conf[model][d_hidden] = 32\r\nUSING MODEL CONFIG: self._conf[model][d_hidden_templ] = 32\r\nUSING MODEL CONFIG: self._conf[model][p_drop] = 0.15\r\nUSING 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}\r\nUSING 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}\r\nUSING MODEL CONFIG: self._conf[model][freeze_track_motif] = False\r\nUSING MODEL CONFIG: self._conf[model][use_motif_timestep] = True\r\nUSING MODEL CONFIG: self._conf[diffuser][T] = 50\r\nUSING MODEL CONFIG: self._conf[diffuser][b_0] = 0.01\r\nUSING MODEL CONFIG: self._conf[diffuser][b_T] = 0.07\r\nUSING MODEL CONFIG: self._conf[diffuser][schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_type] = igso3\r\nUSING MODEL CONFIG: self._conf[diffuser][crd_scale] = 0.25\r\nUSING MODEL CONFIG: self._conf[diffuser][so3_schedule_type] = linear\r\nUSING MODEL CONFIG: self._conf[diffuser][min_b] = 1.5\r\nUSING MODEL CONFIG: self._conf[diffuser][max_b] = 2.5\r\nUSING MODEL CONFIG: self._conf[diffuser][min_sigma] = 0.02\r\nUSING MODEL CONFIG: self._conf[diffuser][max_sigma] = 1.5\r\nUSING MODEL CONFIG: self._conf[preprocess][sidechain_input] = False\r\nUSING MODEL CONFIG: self._conf[preprocess][motif_sidechain_input] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t1d] = 22\r\nUSING MODEL CONFIG: self._conf[preprocess][d_t2d] = 44\r\nUSING MODEL CONFIG: self._conf[preprocess][prob_self_cond] = 0.5\r\nUSING MODEL CONFIG: self._conf[preprocess][str_self_cond] = True\r\nUSING MODEL CONFIG: self._conf[preprocess][predict_previous] = False\r\n[2023-08-22 16:39:28,027][rfdiffusion.inference.model_runners][INFO] - Loading checkpoint.\r\n[2023-08-22 16:39:28,250][rfdiffusion.diffusion][INFO] - Using cached IGSO3.\r\nSuccessful diffuser __init__\r\n[2023-08-22 16:39:28,261][__main__][INFO] - Making design /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_monomer_ROG_unconditional_0\r\n[2023-08-22 16:39:28,267][rfdiffusion.inference.model_runners][INFO] - Using contig: ['100-200']\r\nWith this beta schedule (linear schedule, beta_0 = 0.04, beta_T = 0.28), alpha_bar_T = 0.00013696050154976547\r\n[2023-08-22 16:39:28,290][rfdiffusion.inference.model_runners][INFO] - Sequence init: -----------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:39:33,430][rfdiffusion.inference.model_runners][INFO] - Timestep 50, input to next step: -----------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:39:37,790][rfdiffusion.inference.model_runners][INFO] - Timestep 49, input to next step: -----------------------------------------------------------------------------------------------------------------------------------------------------\r\n[2023-08-22 16:39:42,265][__main__][INFO] - Finished design in 0.23 minutes\r\n",
"state": "passed"
},
"pdb-diff.C6_oligo_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/C6_oligo_0.pdb passed",
"state": "passed"
},
"pdb-diff.D2_oligo_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/D2_oligo_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_enzyme_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_enzyme_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_monomer_ROG_unconditional_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_monomer_ROG_unconditional_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_motifscaffolding_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_motifscaffolding_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_motifscaffolding_inpaintseq_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_motifscaffolding_inpaintseq_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_nickel_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_nickel_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_partialdiffusion_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_partialdiffusion_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_partialdiffusion_peptidewithmultiplesequence_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_partialdiffusion_peptidewithmultiplesequence_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_partialdiffusion_peptidewithsequence_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_partialdiffusion_peptidewithsequence_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_ppi_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_ppi_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_tim_barrel_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_tim_barrel_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_unconditional_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_unconditional_0.pdb passed",
"state": "passed"
},
"pdb-diff.design_unconditional_w_contact_potential_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/design_unconditional_w_contact_potential_0.pdb passed",
"state": "passed"
},
"pdb-diff.tetrahedral_oligo_0.pdb": {
"log": "Subtest /home/benchmark/rosetta/tests/tests_2023_08_22_16_12_06/example_outputs/tetrahedral_oligo_0.pdb passed",
"state": "passed"
}
}
}