Comments (2)
additionally, the config is as follows, our gpu is a100, 80g memory
prep_model self.opt is {'alpha': 2.0, 'cmap_cutoff': 10.0, 'con': {'binary': False, 'cutoff': 14.0, 'num': 2, 'num_pos': inf, 'seqsep': 9}, 'dropout': True, 'fape_cutoff': 10.0, 'fix_pos': ar
ray([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19, 20, 21, 22, 23]), 'hard': 0.0, 'i_con': {'binary': False, 'cutoff': 21.6875, 'num': 1, 'num_pos': inf}, 'learning_rate': 0.1, 'norm_seq_grad': True, 'num_models': 1, 'num_recycles': 0, 'pos': array([ 242, 244, 247, 249, 251, 267, 268, 270, 271, 981, 982, 985, 986, 988, 989, 1035, 1036, 1039, 1043, 1044, 1045, 1046,
1047, 1048]), 'sample_models': True, 'soft': 0.0, 'temp': 1.0, 'template': {'dropout': 0.0, 'rm_ic': False}, 'use_pssm': False, 'weights': {'con': 1.0, 'dgram_cce': 1.0, 'exp_res': 0.0
, 'fape': 0.0, 'helix': 0.0, 'pae': 0.0, 'plddt': 0.0, 'rmsd': 0.0, 'seq_ent': 0.0}}
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As you see, it tries to allocate 206 GB of GPU memory. Generally speaking going beyond 600AAs is not possible for Gradient-based optimisation. You can try the semigreedy protocol, this should work.
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Related Issues (20)
- MPNN designed sequence not separated correctly with multiple targets and multiple binders HOT 2
- Patch fix_partial_contigs when residue numbering in PDB has a gap HOT 2
- Allow to select the Complex_beta_ckpt model in RFdiffusion colab?
- Translate colab for RFdiffusion to a jupyter notebook?
- How to get PAE files when running RFdiffusion
- Is it possible to bypass the design step of AfDesign?
- Do the soft iterations in pssm_semigreedy obey the bias matrix
- fix_pos in af/fixbb HOT 2
- Partially folding a structure using AF
- How to continue a design run?
- Contigs messed up with partial diffusion and manual symmetry
- Can af_cyc_design generate cyclic pepitide with D-Amino acid HOT 1
- Is the "i_pae" score in the designability_test.py the same as pAE_interaction?
- Locally Run ColabDesign
- XlaRuntimeError: FAILED_PRECONDITION: DNN library initialization failed. HOT 1
- converting other MPNN checkpoints for support in ColabDesign and JAX HOT 8
- mk_af_model: refolding a sequence of a experimental structure using said structure as a template performs miserably HOT 2
- af_model.predict failing HOT 2
- Is it preferable for the "con" metric to have a smaller value during the optimization process?
- binders designed don't binds at the hotspots of the target chain.
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