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/train/data/coco_json_loaders.py

@@ -142,9 +142,9 @@ class COCO_FROM_JSON:
             self.prompts = {}
             for loc_dict in prompts:
                 self.prompts[int(loc_dict["id"])] = loc_dict["name"]
-            assert len(self.prompts) == len(
-                self._sorted_cat_ids
-            ), "Number of prompts must match number of categories"
+            assert len(self.prompts) == len(self._sorted_cat_ids), (
+                "Number of prompts must match number of categories"
+            )
 
     def getDatapointIds(self):
         """Return all datapoint indices for training."""

sam3/train/data/collator.py

@@ -6,7 +6,6 @@ from dataclasses import dataclass, field as field_ptr_behaviour, fields, is_data
 from typing import Any, get_args, get_origin, List, Union
 
 import torch
-
 from sam3.model.data_misc import (
     BatchedDatapoint,
     BatchedFindTarget,
@@ -217,9 +216,9 @@ def collate_fn_api(
                 text_batch.append(q.query_text)
             stages[stage_id].text_ids.append(text_batch.index(q.query_text))
 
-            assert (
-                q.inference_metadata is not None
-            ), "inference_metadata must be provided when FindQueryLoaded is created."
+            assert q.inference_metadata is not None, (
+                "inference_metadata must be provided when FindQueryLoaded is created."
+            )
             for f in fields(q.inference_metadata):
                 getattr(find_metadatas[stage_id], f.name).append(
                     getattr(q.inference_metadata, f.name)

sam3/train/data/sam3_image_dataset.py

@@ -19,10 +19,8 @@ import torch.utils.data
 import torchvision
 from decord import cpu, VideoReader
 from iopath.common.file_io import g_pathmgr
-
 from PIL import Image as PILImage
 from PIL.Image import DecompressionBombError
-
 from sam3.model.box_ops import box_xywh_to_xyxy
 from torchvision.datasets.vision import VisionDataset
 
@@ -234,9 +232,9 @@ class CustomCocoDetectionAPI(VisionDataset):
         if self.coco is not None:
             return
 
-        assert g_pathmgr.isfile(
-            self.annFile
-        ), f"please provide valid annotation file. Missing: {self.annFile}"
+        assert g_pathmgr.isfile(self.annFile), (
+            f"please provide valid annotation file. Missing: {self.annFile}"
+        )
         annFile = g_pathmgr.get_local_path(self.annFile)
 
         if self.coco is not None:
@@ -326,9 +324,9 @@ class CustomCocoDetectionAPI(VisionDataset):
         else:
             num_queries_per_stage = stage2num_queries.most_common(1)[0][1]
         for stage, num_queries in stage2num_queries.items():
-            assert (
-                num_queries == num_queries_per_stage
-            ), f"Number of queries in stage {stage} is {num_queries}, expected {num_queries_per_stage}"
+            assert num_queries == num_queries_per_stage, (
+                f"Number of queries in stage {stage} is {num_queries}, expected {num_queries_per_stage}"
+            )
 
         for query_id, query in enumerate(queries):
             h, w = id2imsize[query["image_id"]]

sam3/train/data/sam3_video_dataset.py

@@ -3,7 +3,6 @@
 # pyre-unsafe
 
 import copy
-
 import io
 import json
 import logging
@@ -16,7 +15,6 @@ from typing import Any, Dict, List, Optional, Set, Tuple, Union
 
 import torch
 import torchvision
-
 # from decord import cpu, VideoReader
 
 from iopath.common.file_io import PathManager
@@ -220,9 +218,9 @@ class VideoGroundingDataset(Sam3ImageDataset):
             for query in filtered_queries:
                 ptr_x_is_empty = query["ptr_x_query_id"] in [None, -1]
                 ptr_y_is_empty = query["ptr_y_query_id"] in [None, -1]
-                assert (
-                    ptr_x_is_empty and ptr_y_is_empty
-                ), "Remapping stage ids is not supported for queries with non-empty ptr_x or ptr_y pointers"
+                assert ptr_x_is_empty and ptr_y_is_empty, (
+                    "Remapping stage ids is not supported for queries with non-empty ptr_x or ptr_y pointers"
+                )
                 query["query_processing_order"] = stage_id_old2new[
                     query["query_processing_order"]
                 ]