Renaming verb from predict to infer.

src/fibad/config_utils.py

@@ -268,7 +268,7 @@ def resolve_runtime_config(runtime_config_filepath: Union[Path, str, None] = Non
 def create_results_dir(config: ConfigDict, postfix: Union[Path, str]) -> Path:
     """Creates a results directory for this run.
 
-    Postfix is the verb name of the run e.g. (predict, train, etc)
+    Postfix is the verb name of the run e.g. (infer, train, etc)
 
     The directory is created within the results dir (set with config results_dir)
     and follows the pattern <timestamp>-<postfix>

src/fibad/fibad.py

@@ -14,7 +14,7 @@ class Fibad:
     CLI functions in fibad_cli are implemented by calling this class
     """
 
-    verbs = ["train", "predict", "download", "prepare", "rebuild_manifest"]
+    verbs = ["train", "infer", "download", "prepare", "rebuild_manifest"]
 
     def __init__(self, *, config_file: Union[Path, str] = None, setup_logging: bool = True):
         """Initialize fibad. Always applies the default config, and merges it with any provided config file.
@@ -170,11 +170,11 @@ def download(self, **kwargs):
         downloader = Downloader(config=self.config)
         return downloader.run(**kwargs)
 
-    def predict(self, **kwargs):
+    def infer(self, **kwargs):
         """
-        See Fibad.predict.run()
+        See Fibad.infer.run()
         """
-        from .predict import run
+        from .infer import run
 
         return run(config=self.config, **kwargs)
 

src/fibad/fibad_default_config.toml

@@ -148,7 +148,7 @@ batch_size = 32
 shuffle = false
 num_workers = 2
 
-[predict]
+[infer]
 model_weights_file = false
 batch_size = 32
 split = "test"

src/fibad/predict.py → src/fibad/infer.py

@@ -16,21 +16,21 @@
 
 
 def run(config: ConfigDict):
-    """Run Prediction
+    """Run inference on a model using a dataset
 
     Parameters
     ----------
     config : ConfigDict
         The parsed config file as a nested dict
     """
 
-    data_set = setup_dataset(config, split=config["predict"]["split"])
+    data_set = setup_dataset(config, split=config["infer"]["split"])
     model = setup_model(config, data_set)
     logger.info(f"data set has length {len(data_set)}")
     data_loader = dist_data_loader(data_set, config)
 
     # Create a results directory and dump our config there
-    results_dir = create_results_dir(config, "predict")
+    results_dir = create_results_dir(config, "infer")
     log_runtime_config(config, results_dir)
     load_model_weights(config, model)
 
@@ -69,13 +69,13 @@ def load_model_weights(config: ConfigDict, model):
         The model class to load weights into
 
     """
-    weights_file = config["predict"]["model_weights_file"]
+    weights_file = config["infer"]["model_weights_file"]
 
     if not weights_file:
-        # TODO: Look at the last predict run from the rundir
+        # TODO: Look at the last infer (or train) run from the rundir
         # use config["model"]["weights_filename"] to find the weights
         # Proceed with those weights
-        raise RuntimeError("Must define pretrained_model in the predict section of fibad config.")
+        raise RuntimeError("Must define model_weights_file in the [infer] section of fibad config.")
 
     weights_file = Path(weights_file)
 

tests/fibad/test_config_utils.py

@@ -56,7 +56,7 @@ def test_get_runtime_config():
             "model_class": "new_thing.cool_model.CoolModel",
             "model": {"model_weights_filepath": "final_best.pth", "layers": 3},
         },
-        "predict": {"batch_size": 8},
+        "infer": {"batch_size": 8},
     }
 
     assert runtime_config == expected

tests/fibad/test_data/test_default_config.toml

@@ -9,5 +9,5 @@ model_class = "new_thing.cool_model.CoolModel" # Use a custom model
 model_weights_filepath = "example_model.pth"
 layers = 3
 
-[predict]
+[infer]
 batch_size = 32

tests/fibad/test_data/test_user_config.toml

@@ -5,5 +5,5 @@ dev_mode = false
 model_weights_filepath = "final_best.pth"
 layers = 3
 
-[predict]
+[infer]
 batch_size = 8