Minor.

resampler/__init__.py

@@ -3,10 +3,8 @@
 .. include:: ../README.md
 """
 
-from __future__ import annotations
-
 __docformat__ = 'google'
-__version__ = '0.8.8'
+__version__ = '0.8.9'
 __version_info__ = tuple(int(num) for num in __version__.split('.'))
 
 from collections.abc import Callable, Iterable, Sequence
@@ -394,6 +392,7 @@ def make_sparse_matrix(
 
 class _NumpyArraylib(_Arraylib[_NDArray]):
   """Numpy implementation of the array abstraction."""
+
   # pylint: disable=missing-function-docstring
 
   def __init__(self, array: _NDArray) -> None:
@@ -557,7 +556,7 @@ def best_dims_order_for_resize(self, dst_shape: tuple[int, ...]) -> list[int]:
     return dims
 
   def premult_with_sparse(
-      self, sparse: tf.sparse.SparseTensor, num_threads: int | Literal['auto']
+      self, sparse: 'tf.sparse.SparseTensor', num_threads: int | Literal['auto']
   ) -> _TensorflowTensor:
     import tensorflow as tf
 
@@ -590,6 +589,7 @@ def make_sparse_matrix(
 
 class _TorchArraylib(_Arraylib[_TorchTensor]):
   """Torch implementation of the array abstraction."""
+
   # pylint: disable=missing-function-docstring
 
   def __init__(self, array: _NDArray) -> None:
@@ -763,7 +763,7 @@ def best_dims_order_for_resize(self, dst_shape: tuple[int, ...]) -> list[int]:
     return dims
 
   def premult_with_sparse(
-      self, sparse: jax.experimental.sparse.BCOO, num_threads: int | Literal['auto']
+      self, sparse: 'jax.experimental.sparse.BCOO', num_threads: int | Literal['auto']
   ) -> _JaxArray:
     del num_threads
     return sparse @ self.array  # Calls jax.bcoo_multiply_dense().

resampler_notebook.ipynb

@@ -470,6 +470,7 @@
     "import matplotlib.pyplot as plt\n",
     "import mediapy as media  # https://github.com/google/mediapy\n",
     "import numpy as np\n",
+    "import numpy.typing\n",
     "import pdoc\n",
     "import scipy.signal\n",
     "import skimage\n",
@@ -490,8 +491,8 @@
     "# pylint: disable=protected-access, missing-function-docstring\n",
     "# mypy: allow-incomplete-defs, allow-untyped-defs\n",
     "\n",
-    "_ArrayLike = resampler._ArrayLike\n",
-    "_NDArray = resampler._NDArray\n",
+    "_ArrayLike = numpy.typing.ArrayLike\n",
+    "_NDArray = numpy.typing.NDArray[Any]\n",
     "_TensorflowTensor = resampler._TensorflowTensor\n",
     "_TorchTensor = resampler._TorchTensor\n",
     "_JaxArray = resampler._JaxArray\n",
@@ -853,8 +854,8 @@
    "source": [
     "def get_rms(a: _ArrayLike, b: _ArrayLike) -> float:\n",
     "  \"\"\"Return the root-mean-square difference between two arrays.\"\"\"\n",
-    "  a2: _NDArray = media.to_float01(a)\n",
-    "  b2: _NDArray = media.to_float01(b)\n",
+    "  a2 = media.to_float01(a)\n",
+    "  b2 = media.to_float01(b)\n",
     "  rms: float = np.sqrt(np.mean(np.square(a2 - b2))).item()\n",
     "  return rms\n",
     "\n",

resampler_notebook.py

@@ -312,8 +312,6 @@
 
 # %%
 """Python notebook demonstrating the `resampler` package."""
-from __future__ import annotations
-
 import collections
 from collections.abc import Callable, Iterable, Mapping, Sequence
 import concurrent.futures

test_resampler.py

@@ -4,8 +4,6 @@
 
 c:/windows/sysnative/wsl -e bash -lc 'flake8 --indent-size 2 --max-line-length=1000 --extend-ignore E302,E741,E131,E305,E402 test_resampler.py && python3 test_resampler.py'
 """
-from __future__ import annotations
-
 from collections.abc import Callable
 import functools
 import itertools