Import ArgumentParser

.github/workflows/test.yaml

@@ -34,19 +34,19 @@ jobs:
     - name: Install metl package from metl-pretrained repo
       shell: bash --login {0}
       run: pip install git+https://github.com/gitter-lab/metl-pretrained
-    # Log conda environment contents
+      # Log conda environment contents
     - name: Log conda environment
       shell: bash --login {0}
       run: conda list
-    # Pretrain source model on GFP Rosetta dataset
+      # Pretrain source model on GFP Rosetta dataset
     - name: Pretrain source METL model
       shell: bash --login {0}
       run: python code/train_source_model.py @args/pretrain_avgfp_local.txt --max_epochs 5 --limit_train_batches 5 --limit_val_batches 5 --limit_test_batches 5
-    # Finetune target model on GFP DMS dataset
+      # Finetune target model on GFP DMS dataset
     - name: Finetune target METL model
       shell: bash --login {0}
       run: python code/train_target_model.py @args/finetune_avgfp_local.txt --enable_progress_bar false --enable_simple_progress_messages --max_epochs 50 --unfreeze_backbone_at_epoch 25
-    # Load target model checkpoint and run inference on example variants
+      # Load target model checkpoint and run inference on example variants
     - name: Load and test target METL model
       shell: bash --login {0}
       run: python code/tests.py --checkpoint_path output/training_logs/DgLkMZxu/checkpoints/epoch=49-step=50.ckpt --variants E3K,G102S;T36P,S203T,K207R;V10A,D19G,F25S,E113V --dataset avgfp

code/tests.py

@@ -4,6 +4,8 @@
 import torch
 import utils
 
+from argparse import ArgumentParser
+
 
 def load_checkpoint_run_inference(checkpoint_path, variants, dataset):
     """ loads a finetuned 3D model from a checkpoint and scores variants with the model """