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/sam3_image.py

@@ -8,19 +8,14 @@ from typing import Dict, List, Optional, Tuple
 
 import numpy as np
 import torch
-
 from sam3.model.model_misc import SAM3Output
-
 from sam3.model.sam1_task_predictor import SAM3InteractiveImagePredictor
 from sam3.model.vl_combiner import SAM3VLBackbone
 from sam3.perflib.nms import nms_masks
-
 from sam3.train.data.collator import BatchedDatapoint
 
 from .act_ckpt_utils import activation_ckpt_wrapper
-
 from .box_ops import box_cxcywh_to_xyxy
-
 from .geometry_encoders import Prompt
 from .model_misc import inverse_sigmoid
 
@@ -661,9 +656,9 @@ class Sam3Image(torch.nn.Module):
             inference_state["original_heights"],
             inference_state["original_widths"],
         )
-        assert (
-            batch_size == len(orig_heights) == len(orig_widths)
-        ), f"Batch size mismatch in predict_inst_batch. Got {batch_size}, {len(orig_heights)}, {len(orig_widths)}"
+        assert batch_size == len(orig_heights) == len(orig_widths), (
+            f"Batch size mismatch in predict_inst_batch. Got {batch_size}, {len(orig_heights)}, {len(orig_widths)}"
+        )
         feats = [
             feat.permute(1, 2, 0).view(batch_size, -1, *feat_size)
             for feat, feat_size in zip(