diff --git a/albumentations/core/composition.py b/albumentations/core/composition.py
index 7a78e43f7..d9f53c4a2 100644
--- a/albumentations/core/composition.py
+++ b/albumentations/core/composition.py
@@ -48,6 +48,12 @@ def get_always_apply(transforms: typing.Union["BaseCompose", TransformsSeqType])
 
 class BaseCompose(metaclass=SerializableMeta):
     def __init__(self, transforms: TransformsSeqType, p: float):
+        if isinstance(transforms, (BaseCompose, BasicTransform)):
+            warnings.warn(
+                "transforms is single transform, but a sequence is expected! Transform will be wrapped into list."
+            )
+            transforms = [transforms]
+
         self.transforms = transforms
         self.p = p
 
@@ -276,7 +282,7 @@ class OneOf(BaseCompose):
 
     def __init__(self, transforms: TransformsSeqType, p: float = 0.5):
         super(OneOf, self).__init__(transforms, p)
-        transforms_ps = [t.p for t in transforms]
+        transforms_ps = [t.p for t in self.transforms]
         s = sum(transforms_ps)
         self.transforms_ps = [t / s for t in transforms_ps]
 
@@ -308,7 +314,7 @@ def __init__(self, transforms: TransformsSeqType, n: int, replace: bool = True,
         super(SomeOf, self).__init__(transforms, p)
         self.n = n
         self.replace = replace
-        transforms_ps = [t.p for t in transforms]
+        transforms_ps = [t.p for t in self.transforms]
         s = sum(transforms_ps)
         self.transforms_ps = [t / s for t in transforms_ps]
 
@@ -347,9 +353,9 @@ def __init__(
             if first is None or second is None:
                 raise ValueError("You must set both first and second or set transforms argument.")
             transforms = [first, second]
-        elif len(transforms) != 2:
-            warnings.warn("Length of transforms is not equal to 2.")
         super(OneOrOther, self).__init__(transforms, p)
+        if len(self.transforms) != 2:
+            warnings.warn("Length of transforms is not equal to 2.")
 
     def __call__(self, *args, force_apply: bool = False, **data) -> typing.Dict[str, typing.Any]:
         if self.replay_mode:
diff --git a/tests/test_core.py b/tests/test_core.py
index 18e677bb9..5d69d2989 100644
--- a/tests/test_core.py
+++ b/tests/test_core.py
@@ -1,26 +1,43 @@
 from __future__ import absolute_import
 
+import typing
 from unittest import mock
-from unittest.mock import Mock, MagicMock, call
+from unittest.mock import MagicMock, Mock, call
 
 import cv2
 import numpy as np
 import pytest
 
-from albumentations.core.transforms_interface import to_tuple, ImageOnlyTransform, DualTransform
+from albumentations import (
+    BasicTransform,
+    Blur,
+    Crop,
+    HorizontalFlip,
+    MedianBlur,
+    Normalize,
+    PadIfNeeded,
+    Resize,
+    Rotate,
+)
 from albumentations.augmentations.bbox_utils import check_bboxes
 from albumentations.core.composition import (
-    OneOrOther,
+    BaseCompose,
+    BboxParams,
     Compose,
+    KeypointParams,
     OneOf,
+    OneOrOther,
     SomeOf,
     PerChannel,
     ReplayCompose,
-    KeypointParams,
-    BboxParams,
     Sequential,
 )
-from albumentations import HorizontalFlip, Rotate, Blur, MedianBlur, PadIfNeeded, Crop
+from albumentations.core.transforms_interface import (
+    DualTransform,
+    ImageOnlyTransform,
+    to_tuple,
+)
+from .utils import get_filtered_transforms
 
 
 def test_one_or_other():
@@ -332,3 +349,24 @@ def test_bbox_params_is_not_set(image, bboxes):
     with pytest.raises(ValueError) as exc_info:
         t(image=image, bboxes=bboxes)
     assert str(exc_info.value) == "bbox_params must be specified for bbox transformations"
+
+
+@pytest.mark.parametrize(
+    "compose_transform", get_filtered_transforms((BaseCompose,), custom_arguments={SomeOf: {"n": 1}})
+)
+@pytest.mark.parametrize(
+    "inner_transform",
+    [(Normalize, {}), (Resize, {"height": 100, "width": 100})]
+    + get_filtered_transforms((BaseCompose,), custom_arguments={SomeOf: {"n": 1}}),  # type: ignore
+)
+def test_single_transform_compose(
+    compose_transform: typing.Tuple[typing.Type[BaseCompose], dict],
+    inner_transform: typing.Tuple[typing.Union[typing.Type[BaseCompose], typing.Type[BasicTransform]], dict],
+):
+    compose_cls, compose_kwargs = compose_transform
+    cls, kwargs = inner_transform
+    transform = cls(transforms=[], **kwargs) if issubclass(cls, BaseCompose) else cls(**kwargs)
+
+    with pytest.warns(UserWarning):
+        res_transform = compose_cls(transforms=transform, **compose_kwargs)  # type: ignore
+    assert isinstance(res_transform.transforms, list)
diff --git a/tests/utils.py b/tests/utils.py
index b5dea110c..13d1fb8ca 100644
--- a/tests/utils.py
+++ b/tests/utils.py
@@ -1,6 +1,6 @@
+import inspect
 import random
 import typing
-import inspect
 import numpy as np
 
 from io import StringIO
@@ -73,7 +73,9 @@ def get_filtered_transforms(
     result = []
 
     for name, cls in inspect.getmembers(albumentations):
-        if not inspect.isclass(cls) or not issubclass(cls, albumentations.BasicTransform):
+        if not inspect.isclass(cls) or not issubclass(
+            cls, (albumentations.BasicTransform, albumentations.BaseCompose)
+        ):
             continue
 
         if "DeprecationWarning" in inspect.getsource(cls) or "FutureWarning" in inspect.getsource(cls):