Merge branch 'main' into main

detectron2/data/build.py

@@ -300,6 +300,7 @@ def build_batch_data_loader(
     num_workers=0,
     collate_fn=None,
     drop_last: bool = True,
+    single_gpu_batch_size=None,
     **kwargs,
 ):
     """
@@ -313,19 +314,31 @@ def build_batch_data_loader(
             Must be provided iff. ``dataset`` is a map-style dataset.
         total_batch_size, aspect_ratio_grouping, num_workers, collate_fn: see
             :func:`build_detection_train_loader`.
+        single_gpu_batch_size: You can specify either `single_gpu_batch_size` or `total_batch_size`.
+            `single_gpu_batch_size` specifies the batch size that will be used for each gpu/process.
+            `total_batch_size` allows you to specify the total aggregate batch size across gpus.
+            It is an error to supply a value for both.
         drop_last (bool): if ``True``, the dataloader will drop incomplete batches.
 
     Returns:
         iterable[list]. Length of each list is the batch size of the current
             GPU. Each element in the list comes from the dataset.
     """
-    world_size = get_world_size()
-    assert (
-        total_batch_size > 0 and total_batch_size % world_size == 0
-    ), "Total batch size ({}) must be divisible by the number of gpus ({}).".format(
-        total_batch_size, world_size
-    )
-    batch_size = total_batch_size // world_size
+    if single_gpu_batch_size:
+        if total_batch_size:
+            raise ValueError(
+                """total_batch_size and single_gpu_batch_size are mutually incompatible.
+                Please specify only one. """
+            )
+        batch_size = single_gpu_batch_size
+    else:
+        world_size = get_world_size()
+        assert (
+            total_batch_size > 0 and total_batch_size % world_size == 0
+        ), "Total batch size ({}) must be divisible by the number of gpus ({}).".format(
+            total_batch_size, world_size
+        )
+        batch_size = total_batch_size // world_size
     logger = logging.getLogger(__name__)
     logger.info("Making batched data loader with batch_size=%d", batch_size)
 

projects/DensePose/densepose/vis/densepose_data_points.py

@@ -28,7 +28,6 @@ def visualize(
     ) -> Image:
         if bbox_densepose_datas is None:
             return image_bgr
-        # pyre-fixme[23]: Unable to unpack single value, 2 were expected.
         for bbox_xywh, densepose_data in zip(*bbox_densepose_datas):
             matrix = densepose_data.segm.numpy()
             mask = np.zeros(matrix.shape, dtype=np.uint8)
@@ -50,7 +49,6 @@ def visualize(
     ) -> Image:
         if bbox_densepose_datas is None:
             return image_bgr
-        # pyre-fixme[23]: Unable to unpack single value, 2 were expected.
         for bbox_xywh, densepose_data in zip(*bbox_densepose_datas):
             x0, y0, w, h = bbox_xywh.numpy()
             x = densepose_data.x.numpy() * w / 255.0 + x0