# @package _global_

defaults:
  - data: combined # choose datamodule with `test_dataloader()` for evaluation
  - model: flowdock_fm
  - logger: null
  - strategy: default
  - trainer: default
  - paths: default
  - extras: default
  - hydra: default
  - environment: default
  - _self_

task_name: "eval"

tags: ["eval", "combined", "flowdock_fm"]

# passing checkpoint path is necessary for evaluation
ckpt_path: ???

# seed for random number generators in pytorch, numpy and python.random
seed: null

# model arguments
model:
  cfg:
    mol_encoder:
      from_pretrained: false
    protein_encoder:
      from_pretrained: false
    relational_reasoning:
      from_pretrained: false
    contact_predictor:
      from_pretrained: false
    score_head:
      from_pretrained: false
    confidence:
      from_pretrained: false
    affinity:
      from_pretrained: false
    task:
      freeze_mol_encoder: true
      freeze_protein_encoder: false
      freeze_relational_reasoning: false
      freeze_contact_predictor: false
      freeze_score_head: false
      freeze_confidence: true
      freeze_affinity: false