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/utils/checkpoint_utils.py

@@ -36,9 +36,9 @@ def unix_pattern_to_parameter_names(
     parameter_names = []
     for param_name in constraints:
         matching_parameters = set(fnmatch.filter(all_parameter_names, param_name))
-        assert (
-            len(matching_parameters) > 0
-        ), f"param_names {param_name} don't match any param in the given names."
+        assert len(matching_parameters) > 0, (
+            f"param_names {param_name} don't match any param in the given names."
+        )
         parameter_names.append(matching_parameters)
     return set.union(*parameter_names)
 

sam3/train/utils/logger.py

@@ -10,10 +10,8 @@ import uuid
 from typing import Any, Dict, Optional, Union
 
 from hydra.utils import instantiate
-
 from iopath.common.file_io import g_pathmgr
 from numpy import ndarray
-
 from sam3.train.utils.train_utils import get_machine_local_and_dist_rank, makedir
 from torch import Tensor
 from torch.utils.tensorboard import SummaryWriter

sam3/train/utils/train_utils.py

@@ -11,7 +11,6 @@ from datetime import timedelta
 from typing import Optional
 
 import hydra
-
 import numpy as np
 import omegaconf
 import torch
@@ -83,9 +82,9 @@ def get_machine_local_and_dist_rank():
     """
     local_rank = int(os.environ.get("LOCAL_RANK", None))
     distributed_rank = int(os.environ.get("RANK", None))
-    assert (
-        local_rank is not None and distributed_rank is not None
-    ), "Please the set the RANK and LOCAL_RANK environment variables."
+    assert local_rank is not None and distributed_rank is not None, (
+        "Please the set the RANK and LOCAL_RANK environment variables."
+    )
     return local_rank, distributed_rank