Identified and re-named all multi-processed functions vs. multi-threa…

…ded ones (#771)

darwin/dataset/local_dataset.py

@@ -350,14 +350,14 @@ def annotation_type_supported(self, annotation) -> bool:
             )
 
     def measure_mean_std(
-        self, multi_threaded: bool = True
+        self, multi_processed: bool = True
     ) -> Tuple[np.ndarray, np.ndarray]:
         """
         Computes mean and std of trained images, given the train loader.
 
         Parameters
         ----------
-        multi_threaded : bool, default: True
+        multi_processed : bool, default: True
             Uses multiprocessing to download the dataset in parallel.
 
         Returns
@@ -367,7 +367,7 @@ def measure_mean_std(
         std : ndarray[double]
             Standard deviation (for each channel) of all pixels of the images in the input folder.
         """
-        if multi_threaded:
+        if multi_processed:
             # Set up a pool of workers
             with mp.Pool(mp.cpu_count()) as pool:
                 # Online mean

darwin/dataset/remote_dataset.py

@@ -183,7 +183,7 @@ def pull(
         *,
         release: Optional[Release] = None,
         blocking: bool = True,
-        multi_threaded: bool = True,
+        multi_processed: bool = True,
         only_annotations: bool = False,
         force_replace: bool = False,
         remove_extra: bool = False,
@@ -203,7 +203,7 @@ def pull(
             The release to pull.
         blocking : bool, default: True
             If False, the dataset is not downloaded and a generator function is returned instead.
-        multi_threaded : bool, default: True
+        multi_processed : bool, default: True
             Uses multiprocessing to download the dataset in parallel. If blocking is False this has no effect.
         only_annotations : bool, default: False
             Download only the annotations and no corresponding images.
@@ -364,7 +364,7 @@ def pull(
             successes, errors = exhaust_generator(
                 progress=progress(),
                 count=count,
-                multi_threaded=multi_threaded,
+                multi_processed=multi_processed,
                 worker_count=max_workers,
             )
             if errors:

darwin/dataset/utils.py

@@ -223,12 +223,12 @@ def _f(x: Any) -> Any:
 def exhaust_generator(
     progress: Generator,
     count: int,
-    multi_threaded: bool,
+    multi_processed: bool,
     worker_count: Optional[int] = None,
 ) -> Tuple[List[Dict[str, Any]], List[Exception]]:
     """
 
-    Exhausts the generator passed as parameter. Can be done multi threaded if desired.
+    Exhausts the generator passed as parameter. Can be done multi processed if desired.
     Creates and returns a coco record from the given annotation.
 
     Uses ``BoxMode.XYXY_ABS`` from ``detectron2.structures`` if available, defaults to ``box_mode = 0``
@@ -260,7 +260,7 @@ def exhaust_generator(
     """
     successes = []
     errors = []
-    if multi_threaded:
+    if multi_processed:
         progress_bar: ProgressBar = ProgressBar(total=count)
         responses = []