Moving `sequence_to_str` to `torchvision._utils` (#5604)

* Moving `sequence_to_str` to `torchvision._utils`

* Fix linter

* Rename test_prototype_utils test to test_internal_utils

test/builtin_dataset_mocks.py

@@ -19,8 +19,8 @@ import torch
 from datasets_utils import make_zip, make_tar, create_image_folder, create_image_file
 from torch.nn.functional import one_hot
 from torch.testing import make_tensor as _make_tensor
+from torchvision._utils import sequence_to_str
 from torchvision.prototype.datasets._api import find
-from torchvision.prototype.utils._internal import sequence_to_str
 
 make_tensor = functools.partial(_make_tensor, device="cpu")
 make_scalar = functools.partial(make_tensor, ())

test/test_prototype_utils.py → test/test_internal_utils.py

 import pytest
-from torchvision.prototype.utils._internal import sequence_to_str
+from torchvision._utils import sequence_to_str
 
 
 @pytest.mark.parametrize(

test/test_prototype_builtin_datasets.py

@@ -10,8 +10,8 @@ from torch.testing._comparison import assert_equal, TensorLikePair, ObjectPair
 from torch.utils.data.datapipes.iter.grouping import ShardingFilterIterDataPipe as ShardingFilter
 from torch.utils.data.graph import traverse
 from torchdata.datapipes.iter import IterDataPipe, Shuffler
+from torchvision._utils import sequence_to_str
 from torchvision.prototype import transforms, datasets
-from torchvision.prototype.utils._internal import sequence_to_str
 
 
 assert_samples_equal = functools.partial(

torchvision/_utils.py

 import enum
-from typing import TypeVar, Type
+from typing import Sequence, TypeVar, Type
 
 T = TypeVar("T", bound=enum.Enum)
 
@@ -18,3 +18,15 @@ class StrEnumMeta(enum.EnumMeta):
 
 class StrEnum(enum.Enum, metaclass=StrEnumMeta):
     pass
+
+
+def sequence_to_str(seq: Sequence, separate_last: str = "") -> str:
+    if not seq:
+        return ""
+    if len(seq) == 1:
+        return f"'{seq[0]}'"
+
+    head = "'" + "', '".join([str(item) for item in seq[:-1]]) + "'"
+    tail = f"{'' if separate_last and len(seq) == 2 else ','} {separate_last}'{seq[-1]}'"
+
+    return head + tail

torchvision/prototype/datasets/utils/_dataset.py

@@ -7,7 +7,8 @@ import pathlib
 from typing import Any, Dict, List, Optional, Sequence, Union, Tuple, Collection
 
 from torch.utils.data import IterDataPipe
-from torchvision.prototype.utils._internal import FrozenBunch, make_repr, add_suggestion, sequence_to_str
+from torchvision._utils import sequence_to_str
+from torchvision.prototype.utils._internal import FrozenBunch, make_repr, add_suggestion
 
 from .._home import use_sharded_dataset
 from ._internal import BUILTIN_DIR, _make_sharded_datapipe

torchvision/prototype/utils/_internal.py

@@ -28,9 +28,10 @@ from typing import (
 
 import numpy as np
 import torch
+from torchvision._utils import sequence_to_str
+
 
 __all__ = [
-    "sequence_to_str",
     "add_suggestion",
     "FrozenMapping",
     "make_repr",
@@ -43,18 +44,6 @@ __all__ = [
 ]
 
 
-def sequence_to_str(seq: Sequence, separate_last: str = "") -> str:
-    if not seq:
-        return ""
-    if len(seq) == 1:
-        return f"'{seq[0]}'"
-
-    head = "'" + "', '".join([str(item) for item in seq[:-1]]) + "'"
-    tail = f"{'' if separate_last and len(seq) == 2 else ','} {separate_last}'{seq[-1]}'"
-
-    return head + tail
-
-
 def add_suggestion(
     msg: str,
     *,