| _target_: model.denoiser.GemNetTDenoiser |
| hidden_dim: 512 |
| gemnet: |
| _target_: model.common.gemnet.gemnet.GemNetT |
| num_targets: 1 |
| latent_dim: ${eval:'${..hidden_dim} * (1 + len(${..property_embeddings}))'} |
| atom_embedding: |
| _target_: onescience.modules.layer.mattergen.embedding_block.AtomEmbedding |
| emb_size: ${...hidden_dim} |
| with_mask_type: ${eval:'${...denoise_atom_types} and "${...atom_type_diffusion}" == "mask"'} |
| emb_size_atom: ${..hidden_dim} |
| emb_size_edge: ${..hidden_dim} |
| max_neighbors: 50 |
| max_cell_images_per_dim: 5 |
| cutoff: 7. |
| num_blocks: 4 |
| regress_stress: true |
| otf_graph: true |
| scale_file: ${oc.env:PROJECT_ROOT}/common/gemnet/gemnet-dT.json |
| denoise_atom_types: true |
| atom_type_diffusion: mask |
| property_embeddings_adapt: {} |
| property_embeddings: {} |
| defaults: [] # NOTE: to train a conditional model, unccoment entries such as property_embeddings@property_embeddings.chemical_system: chemical_system below and edit/add properties to the defaults list as desired. |
| # see https://stackoverflow.com/questions/71356361/selecting-multiple-configs-from-a-config-group-in-hydra-without-using-an-explici |
| # add via config override: +lightning_module/diffusion_module/model/property_embeddings@lightning_module.diffusion_module.model.property_embeddings.dft_bulk_modulus=dft_bulk_modulus |
| # delete via config override: ~lightning_module/diffusion_module/model/property_embeddings@lightning_module.diffusion_module.model.property_embeddings.chemical_system |
| # - property_embeddings@property_embeddings.chemical_system: chemical_system |
| # - property_embeddings@property_embeddings.dft_bulk_modulus: dft_bulk_modulus |
| |
