Fix presets field in ModelUpdate

Dockerfile

@@ -14,7 +14,7 @@ RUN apt-get update && apt-get install -y \
 
 # Install miniforge
 RUN wget -P /tmp \
-    "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh" \
+    "https://github.com/conda-forge/miniforge/releases/download/25.3.1-0/Miniforge3-Linux-x86_64.sh" \
     && bash /tmp/Miniforge3-Linux-x86_64.sh -b -p /opt/conda \
     && rm /tmp/Miniforge3-Linux-x86_64.sh
 

docs/source/kernels.md

@@ -15,7 +15,7 @@ Then, to enable these kernels via the runner.yaml, add the following:
 
 ```yaml
 model_update:
-  preset: 
+  presets: 
     - "predict"
     - "pae_enabled"  # if using PAE enabled model
     - "low_mem"  # for lower memory systems

examples/example_runner_yamls/cuequivariance.yml

@@ -1,5 +1,5 @@
 model_update:
-  preset: 
+  presets: 
     - predict
     - pae_enabled  # to use the PAE enabled model
     - low_mem  # to use low memory settings

openfold3/entry_points/experiment_runner.py

@@ -636,6 +636,8 @@ def remove_completed_queries_from_query_set(self, inference_query_set):
     def setup(self) -> None:
         """Set up environment and load checkpoints."""
         super().setup()
+        self._log_experiment_config()
+        self._log_model_config()
         logger.info(f"Loading weights from {self.ckpt_path}")
         ckpt = load_checkpoint(self.ckpt_path)
         state_dict = get_state_dict_from_checkpoint(ckpt, init_from_ema_weights=True)
@@ -644,8 +646,6 @@ def setup(self) -> None:
     def run(self, inference_query_set) -> None:
         """Set up the experiment environment."""
         self.inference_query_set = inference_query_set
-        self._log_experiment_config()
-        self._log_model_config()
         if self.experiment_config.experiment_settings.skip_existing:
             inference_query_set = self.remove_completed_queries_from_query_set(
                 inference_query_set

openfold3/projects/of3_all_atom/project_entry.py

@@ -19,13 +19,15 @@
 
 from ml_collections import ConfigDict
 from pydantic import BaseModel
+from pydantic import ConfigDict as PydanticConfigDict
 
 from openfold3.core.config.config_utils import load_yaml
 from openfold3.projects.of3_all_atom.config.model_config import model_config
 from openfold3.projects.of3_all_atom.runner import OpenFold3AllAtom
 
 
 class ModelUpdate(BaseModel):
+    model_config = PydanticConfigDict(extra="forbid")
     presets: list[str] = []
     custom: dict = {}
 

openfold3/run_openfold.py

@@ -19,7 +19,6 @@
 """
 # ruff: noqa: F821
 
-import json
 import logging
 from pathlib import Path
 
@@ -168,10 +167,6 @@ def predict(
         output_dir,
     )
 
-    # Dump experiment runner
-    with open(expt_runner.output_dir / "experiment_config.json", "w") as f:
-        json.dump(expt_config.model_dump_json(indent=2), f)
-
     # Load inference query set
     query_set = InferenceQuerySet.from_json(query_json)