sort imports.

Makefile

@@ -26,7 +26,8 @@ test: $(test.python) $(src.python) ## Run tests
 
 
 .PHONY: format
-format: ## Run ruff format
+format: ## Run ruff format (Includes sorting of imports)
+	uv run ruff check --select I --config=config/ruff.toml --fix
 	uv run ruff format --config=config/ruff.toml $(src.python) $(test.python)
 
 .PHONY: check-format

agml/__init__.py

@@ -19,8 +19,8 @@
 # If AgML is being imported for the first time, then we need to setup
 # the module, namely prepping the config file.
 def _setup():
-    import os as _os
     import json as _json
+    import os as _os
 
     if not _os.path.exists(_os.path.expanduser("~/.agml")):
         _os.makedirs(_os.path.expanduser("~/.agml"))
@@ -39,4 +39,4 @@ def _setup():
 
 
 # There are no top-level imported functions or classes, only the modules.
-from . import data, backend, synthetic, viz, io
+from . import backend, data, io, synthetic, viz

agml/_internal/preprocess.py

@@ -20,32 +20,31 @@
 to install the necessary preprocessing packages.
 """
 
-import os
-import sys
-import json
-import glob
-import shutil
 import argparse
 import csv
+import glob
+import json
+import os
+import shutil
+import sys
 
 import cv2
 import numpy as np
 import pandas as pd
-
 from PIL import Image
 
-from agml.utils.logging import tqdm
-from agml.utils.io import create_dir, nested_dir_list, get_dir_list, get_file_list
-from agml.utils.data import load_public_sources
 from agml._internal.process_utils import (
-    read_txt_file,
-    get_image_info,
-    get_label2id,
     convert_bbox_to_coco,
-    get_coco_annotation_from_obj,
     convert_xmls_to_cocojson,
+    get_coco_annotation_from_obj,
+    get_image_info,
+    get_label2id,
     move_segmentation_dataset,
+    read_txt_file,
 )
+from agml.utils.data import load_public_sources
+from agml.utils.io import create_dir, get_dir_list, get_file_list, nested_dir_list
+from agml.utils.logging import tqdm
 
 
 class PublicDataPreprocessor(object):

agml/_internal/s3internal.py

@@ -16,11 +16,11 @@
 Internal class for interacting with the AgML public dataset S3 bucket.
 """
 
+import json
 import os
 import sys
-import json
-import zipfile
 import warnings
+import zipfile
 
 import boto3
 import botocore.exceptions

agml/_internal/utils.py

@@ -21,7 +21,6 @@
 
 from agml.utils.io import recursive_dirname
 
-
 _PERSONAL_ACCESS_TOKEN = None
 
 

agml/backend/__init__.py

@@ -24,16 +24,16 @@
 AgML, specifically data loaded or generated from the data module.
 """
 
+from . import experimental
 from .config import (
+    clear_all_datasets,
     data_save_path,
-    set_data_save_path,
-    synthetic_data_save_path,
-    set_synthetic_save_path,
+    downloaded_datasets,
     model_save_path,
+    set_data_save_path,
     set_model_save_path,
-    clear_all_datasets,
-    downloaded_datasets,
+    set_synthetic_save_path,
+    synthetic_data_save_path,
 )
-from .tftorch import get_backend, set_backend
 from .random import set_seed
-from . import experimental
+from .tftorch import get_backend, set_backend

agml/backend/config.py

@@ -12,14 +12,13 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import os
 import json
-import shutil
 import logging
+import os
+import shutil
 
 from agml.utils.logging import log
 
-
 # The super base save directory for AgML. This is the overriding base
 # save directory and default original save directory. This is saved here
 # because the default path to save datasets to can be overridden by

agml/backend/experimental.py

@@ -15,7 +15,6 @@
 
 from agml.framework import AgMLSerializable
 
-
 __all__ = ["allow_nested_data_splitting"]
 
 

agml/backend/random.py

@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from agml.backend.tftorch import torch, tf, get_backend
+from agml.backend.tftorch import get_backend, tf, torch
 
 
 def set_seed(seed=None):

agml/backend/tftorch.py

@@ -18,20 +18,19 @@
 importing of either library (which takes a significant amount of time).
 """
 
-import types
+import functools
+import importlib
 import inspect
 import logging
-import importlib
-import functools
+import types
+
+# Suppress any irrelevant warnings which will pop up from either backend.
+import warnings
 
 import numpy as np
 
-from agml.utils.logging import log
 from agml.utils.image import consistent_shapes
-
-
-# Suppress any irrelevant warnings which will pop up from either backend.
-import warnings
+from agml.utils.logging import log
 
 warnings.filterwarnings("ignore", category=UserWarning, message=".*Named tensors.*Triggered internally.*")
 

agml/data/__init__.py

@@ -12,12 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from .loader import AgMLDataLoader
+from . import experimental, exporters, extensions
 from .image_loader import ImageLoader
+from .loader import AgMLDataLoader
 from .point_cloud import PointCloud
-from .public import public_data_sources, source
-from .public import download_public_dataset
+from .public import download_public_dataset, public_data_sources, source
 from .tools import coco_to_bboxes, convert_bbox_format
-from . import experimental
-from . import exporters
-from . import extensions

agml/data/builder.py

@@ -12,15 +12,15 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import json
 import os
 import re
 import sys
-import json
 
-from agml.framework import AgMLSerializable
 from agml.backend.config import data_save_path
+from agml.framework import AgMLSerializable
 from agml.utils.downloads import download_dataset
-from agml.utils.io import get_file_list, get_dir_list, is_image_file
+from agml.utils.io import get_dir_list, get_file_list, is_image_file
 
 
 class DataBuilder(AgMLSerializable):

agml/data/experimental.py

@@ -20,7 +20,6 @@
 
 import numpy as np
 
-
 __all__ = ["generate_keras_segmentation_dual_transform"]
 
 

agml/data/exporters/yolo.py

@@ -1,7 +1,8 @@
 import os
-import yaml
 import shutil
 
+import yaml
+
 import agml
 from agml.utils.general import flatten
 from agml.utils.logging import log

agml/data/extensions/cvat.py

@@ -12,9 +12,9 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import json
 import os
 import shutil
-import json
 
 
 def restructure_cvat_annotations(image_dir, cvat_dir, dataset_name, output_dir=None):

agml/data/image_loader.py

@@ -17,9 +17,9 @@
 import cv2
 import numpy as np
 
-from agml.framework import AgMLSerializable
 from agml.data.loader import AgMLDataLoader
 from agml.data.public import public_data_sources
+from agml.framework import AgMLSerializable
 from agml.utils.io import nested_file_list
 from agml.utils.random import inject_random_state
 

agml/data/loader.py

@@ -12,36 +12,36 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import os
-import json
 import copy
-import glob
 import fnmatch
-from typing import Union
+import glob
+import json
+import os
 from collections.abc import Sequence
-from decimal import getcontext, Decimal
+from decimal import Decimal, getcontext
+from typing import Union
 
 import numpy as np
 
-from agml.framework import AgMLSerializable
-from agml.data.manager import DataManager
-from agml.data.builder import DataBuilder
-from agml.data.metadata import DatasetMetadata, make_metadata
-from agml.data.exporters.yolo import export_yolo
-from agml.utils.logging import log
-from agml.utils.io import get_file_list, get_dir_list
-from agml.utils.data import load_public_sources
-from agml.utils.general import NoArgument, resolve_list_value
-from agml.utils.random import inject_random_state
-from agml.backend.config import data_save_path, synthetic_data_save_path, SUPER_BASE_DIR
+from agml.backend.config import SUPER_BASE_DIR, data_save_path, synthetic_data_save_path
 from agml.backend.experimental import AgMLExperimentalFeatureWrapper
 from agml.backend.tftorch import (
+    StrictBackendError,
+    _add_dataset_to_mro,  # noqa
     get_backend,
     set_backend,
     user_changed_backend,
-    StrictBackendError,
-    _add_dataset_to_mro,  # noqa
 )
+from agml.data.builder import DataBuilder
+from agml.data.exporters.yolo import export_yolo
+from agml.data.manager import DataManager
+from agml.data.metadata import DatasetMetadata, make_metadata
+from agml.framework import AgMLSerializable
+from agml.utils.data import load_public_sources
+from agml.utils.general import NoArgument, resolve_list_value
+from agml.utils.io import get_dir_list, get_file_list
+from agml.utils.logging import log
+from agml.utils.random import inject_random_state
 from agml.viz.general import show_sample
 
 
@@ -1761,9 +1761,10 @@ def export_torch(self, **loader_kwargs):
         -------
         A `torch.utils.data.DataLoader` enclosing a copy of this loader.
         """
-        from agml.backend.tftorch import torch
         from torch.utils.data import DataLoader
 
+        from agml.backend.tftorch import torch
+
         if get_backend() != "torch":
             if user_changed_backend():
                 raise StrictBackendError(change="torch", obj=self.export_torch)

agml/data/manager.py

@@ -14,19 +14,18 @@
 
 import numpy as np
 
-from agml.framework import AgMLSerializable
-from agml.data.object import DataObject
+from agml.backend.tftorch import convert_to_batch, is_array_like
 from agml.data.builder import DataBuilder
-from agml.data.metadata import DatasetMetadata
-from agml.data.managers.transforms import TransformManager
 from agml.data.managers.resize import ImageResizeManager
 from agml.data.managers.training import TrainingManager
-
+from agml.data.managers.transforms import TransformManager
+from agml.data.metadata import DatasetMetadata
+from agml.data.object import DataObject
+from agml.framework import AgMLSerializable
 from agml.utils.general import NoArgument
-from agml.backend.tftorch import convert_to_batch, is_array_like
-from agml.utils.random import seed_context
 from agml.utils.image import consistent_shapes
 from agml.utils.logging import log
+from agml.utils.random import seed_context
 
 
 class DataManager(AgMLSerializable):

agml/data/managers/resize.py

@@ -19,10 +19,10 @@
 import numpy as np
 
 from agml.framework import AgMLSerializable
-from agml.utils.logging import log
-from agml.utils.image import imread_context
 from agml.utils.general import resolve_tuple
+from agml.utils.image import imread_context
 from agml.utils.io import recursive_dirname
+from agml.utils.logging import log
 
 
 class ImageResizeManager(AgMLSerializable):

agml/data/managers/training.py

@@ -16,18 +16,18 @@
 
 import numpy as np
 
-from agml.framework import AgMLSerializable
-from agml.utils.image import needs_batch_dim
 from agml.backend.tftorch import (
-    tf,
-    torch,
-    set_backend,
-    get_backend,
-    user_changed_backend,
     StrictBackendError,
     _convert_image_to_torch,
+    get_backend,
     is_array_like,
+    set_backend,
+    tf,
+    torch,
+    user_changed_backend,
 )
+from agml.framework import AgMLSerializable
+from agml.utils.image import needs_batch_dim
 
 
 class TrainState(Enum):