apply Black 25.11.0 style in fbcode/deeplearning/projects (21/92)

Summary:
Formats the covered files with pyfmt.

paintitblack

Reviewed By: itamaro

Differential Revision: D90476315

fbshipit-source-id: ee94c471788b8e7d067813d8b3e0311214d17f3f

sam3/model/encoder.py

@@ -322,9 +322,9 @@ class TransformerEncoder(nn.Module):
         return reference_points
 
     def _prepare_multilevel_features(self, srcs, masks, pos_embeds):
-        assert (
-            len(srcs) == self.num_feature_levels
-        ), "mismatch between expected and received # of feature levels"
+        assert len(srcs) == self.num_feature_levels, (
+            "mismatch between expected and received # of feature levels"
+        )
 
         src_flatten = []
         mask_flatten = []
@@ -406,9 +406,9 @@ class TransformerEncoder(nn.Module):
             - spatial_shapes: Spatial dimensions of each feature level
             - valid_ratios: Valid ratios for each feature level
         """
-        assert (
-            len(src) == self.num_feature_levels
-        ), "must be equal to num_feature_levels"
+        assert len(src) == self.num_feature_levels, (
+            "must be equal to num_feature_levels"
+        )
         if src_key_padding_masks is not None:
             assert len(src_key_padding_masks) == self.num_feature_levels
         if pos is not None:
@@ -538,9 +538,9 @@ class TransformerEncoderFusion(TransformerEncoder):
                     else None
                 )
         else:
-            assert all(
-                x.dim == 4 for x in src
-            ), "expected list of (bs, c, h, w) tensors"
+            assert all(x.dim == 4 for x in src), (
+                "expected list of (bs, c, h, w) tensors"
+            )
 
         if self.add_pooled_text_to_img_feat:
             # Fusion: Add mean pooled text to image features