| # Configuration for inference on SE(3) diffusion experiments. | |
| defaults: | |
| - base | |
| - _self_ | |
| inference: | |
| # Use this to write with date-time stamp. | |
| name: run_${now:%Y-%m-%d}_${now:%H-%M} | |
| seed: 123 | |
| ckpt_path: ckpt/se3-fm/dnmt-full-unconditioned/2024-09-26_00-42-38/epoch29.ckpt | |
| #output_dir: inference_outputs/dnmt-guided-tests-fixed-residues/ | |
| output_dir: inference_outputs/more-sample/ | |
| # Directories | |
| pmpnn_dir: ./ProteinMPNN/ | |
| use_gpu: True | |
| num_gpus: 1 | |
| interpolant: | |
| min_t: 1e-2 | |
| rots: | |
| corrupt: True | |
| sample_schedule: exp | |
| exp_rate: 10 | |
| trans: | |
| corrupt: True | |
| sample_schedule: linear | |
| sampling: | |
| num_timesteps: 100 | |
| self_condition: True | |
| samples: | |
| # Number of backbone samples per sequence length. | |
| samples_per_length: 1000 | |
| # Minimum sequence length to sample. | |
| min_length: 196 | |
| # Maximum sequence length to sample. | |
| max_length: 286 | |
| # gap between lengths to sample. i.e. this script will sample all lengths | |
| # in range(min_length, max_length, length_step) | |
| length_step: 1 | |
| # Subset of lengths to sample. If null, sample all targets. | |
| # length_subset: [60, 80, 100, 112, 128, 196, 256, 512] | |
| length_subset: [196, 256, 286] | |
| # ESM and ProteinMPNN samples | |
| seq_per_sample: 8 | |
| overwrite: False | |
| classifier: | |
| ckpt_path: classifier_ckpt/se3-classifier/new-classifier-full/2025-02-24_01-37-28/epoch=90-step=728000.ckpt | |
| node_embed_size: 128 | |
| edge_embed_size: 128 | |
| symmetric: false | |
| node_features: | |
| c_s: ${model.node_embed_size} | |
| c_pos_emb: 128 | |
| c_timestep_emb: 128 | |
| embed_diffuse_mask: false | |
| max_num_res: 2000 | |
| timestep_int: 1000 | |
| edge_features: | |
| single_bias_transition_n: 2 | |
| c_s: ${model.node_embed_size} | |
| c_p: ${model.edge_embed_size} | |
| relpos_k: 64 | |
| use_rbf: true | |
| num_rbf: 32 | |
| feat_dim: 64 | |
| num_bins: 22 | |
| self_condition: true | |
| ipa: | |
| c_s: ${model.node_embed_size} | |
| c_z: ${model.edge_embed_size} | |
| c_hidden: 128 | |
| no_heads: 4 | |
| no_qk_points: 4 | |
| no_v_points: 2 | |
| seq_tfmr_num_heads: 2 | |
| seq_tfmr_num_layers: 1 | |
| num_blocks: 2 | |
| fixed_inference: | |
| flag: True | |
| input_pdb: 6F57_A.pdb | |
| #fixed_residues: [639,640,641,642,643,644,645,646,647,664,665,686,687,688,888,889,890,891,892,893,894,895] | |
| fixed_residues: [639, 640, 641, 642, 643, 644, 645, 646, 647, 648, 649, 650, 651, 652, 653, 654, 655, 656, 657, 658, 659, 660, 661, 662, 663, 664, 665, 666, 667, 668, 669, 670, 671, 672, 673, 674, 675, 676, 677, 678, 679, 680, 681, 682, 683, 684, 685, 686, 687, 688, 689, 690, 691, 692, 693, 694, 695, 696, 697, 698, 699, 700, 701, 702, 703, 704, 705, 706, 707, 708, 709, 710, 711, 712, 713, 714, 715, 716, 717, 718, 719, 720, 721, 722, 723, 724, 725, 726, 727, 728, 729, 730, 731, 732, 733, 734, 735, 736, 737, 738, 739, 740, 741, 742, 743, 744, 745, 746, 747, 748, 749, 750, 751, 752, 753, 754, 755, 756, 757, 758, 759, 760, 761, 762, 763, 764, 765, 766, 767, 768, 769, 770, 771, 772, 773, 774, 775, 776, 777, 778, 779, 780, 781, 782, 783, 784, 785, 786, 787, 788, 789, 790, 791, 792, 793, 794, 795, 796, 797, 798, 799, 800, 801, 802, 803, 804, 805, 806, 807, 808, 809, 810, 811, 812, 813, 814, 815, 816, 817, 818, 819, 820, 821, 822, 823, 824, 825, 826, 827, 828, 829, 830] | |
| num_samples: 5 |