input_files:
  - "proteins_A.txt"  # 5 proteins
  - "proteins_B.txt"  # 3 proteins
  - "proteins_C.txt"  # 2 proteins

# Whether the result pickles are going to be gzipped.
  --compress_result_pickles: False

# Whether the result pickles are going to be removed.
  --remove_result_pickles: False

# The models to run the final relaxation step on. If `all`, all models are relaxed, which may be time consuming. If `best`, only the most confident model is relaxed. If `none`, relaxation is not run. Turning off relaxation might result in predictions with distracting stereochemical violations but might help in case you are having issues with the relaxation stage.
  --models_to_relax: None

# Whether to remove aligned_confidence_probs, distogram and masked_msa from pickles.
  --remove_keys_from_pickles: True

# Whether to convert predicted pdb files to modelcif format.
  --convert_to_modelcif: True

# Whether to allow resuming predictions from previous runs or start anew.
  --allow_resume: True

# Number of recycles
  --num_cycle: 3

# Number of predictions per model
  --num_predictions_per_model: 1

# Whether to pair the MSAs when constructing multimer objects.
  --pair_msa: True

# Whether to save features for multimeric object.
  --save_features_for_multimeric_object: False

# Do not use template features when modelling.
  --skip_templates: False

# Run predictions for each model with logarithmically distributed MSA depth.
  --msa_depth_scan: False

# Whether to use multimeric templates.
  --multimeric_template: False

# A list of names of models to use, e.g. model_2_multimer_v3 (default: all models).
  --model_names: None

# Number of sequences to use from the MSA (by default is taken from AF model config).
  --msa_depth: None

# Path to the text file with multimeric template instruction.
  --description_file: None

# Path to directory with multimeric template mmCIF files.
  --path_to_mmt: None

# A desired number of residues to pad.
  --desired_num_res: None

# A desired number of msa to pad.
  --desired_num_msa: None

# Run multiple JAX model evaluations to obtain a timing that excludes the compilation time, which should be more indicative of the time required for inferencing many proteins.
  --benchmark: False

# Choose preset model configuration - the monomer model, the monomer model with extra ensembling, monomer model with pTM head, or multimer model.
  --model_preset: monomer

# Change output directory to include a description of the fold as seen in previous alphapulldown versions
  --use_ap_style: False

# Whether to run Amber relaxation on GPU.
  --use_gpu_relax: True

# Whether to use dropout when inferring for more diverse predictions.
  --dropout: False

# Path to a directory for the JAX compilation cache.
  --jax_compilation_cache_dir: None

# Strictly increasing order of token sizes for which to cache compilations. For any input with more tokens than the largest bucket size, a new bucket is created for exactly that number of tokens.
  --buckets: ['64', '128', '256', '512', '768', '1024', '1280', '1536', '2048', '2560', '3072', '3584', '4096', '4608', '5120']

# Flash attention implementation to use. 'triton' and 'cudnn' uses a Triton and cuDNN flash attention implementation, respectively. The Triton kernel is fastest and has been tested more thoroughly. The Triton and cuDNN kernels require Ampere GPUs or later. 'xla' uses an XLA attention implementation (no flash attention) and is portable across GPU devices.
  --flash_attention_implementation: triton

# Number of diffusion samples to generate.
  --num_diffusion_samples: 5 

# Number of seeds to use for inference. If set, only a single seed must be provided in the input JSON. AlphaFold 3 will then generate random seeds in sequence, starting from the single seed specified in the input JSON. The full input JSON produced by AlphaFold 3 will include the generated random seeds. If not set, AlphaFold 3 will use the seeds as provided in the input JSON.
  --num_seeds: None

# If set, save generated template mmCIFs to templates_debug/ during AF3 input prep.
  --debug_templates: False

# If set, dump featurised MSA arrays and final complex A3M before inference.
  --debug_msas: False

# Number of recycles to use during AF3 inference.
  --num_recycles: 10

# Whether to save final trunk single/pair embeddings in AF3 output.
  --save_embeddings: False

# Whether to save final distogram in AF3 output.
  --save_distogram: False