Drop python 3.7 support

.github/workflows/ci-checks.yml

@@ -26,3 +26,4 @@ jobs:
  actions-ref: main
  artifact-name: dist-packages-${{ github.sha }}
  import-name: "torchmetrics"
+ testing-matrix: {"os": ["ubuntu-20.04", "macos-11", "windows-2022"], "python-version": ["3.8", "3.10"]}

.github/workflows/ci-integrate.yml

@@ -28,10 +28,9 @@ jobs:
  fail-fast: false
  matrix:
  os: [ubuntu-20.04, macOS-11, windows-2022]
- python-version: ['3.7', '3.10']
+ python-version: ['3.8', '3.10']
  requires: ['oldest', 'latest']
  exclude:
- - {python-version: '3.7', requires: 'latest'}
  - {python-version: '3.10', requires: 'oldest'}
  - {python-version: '3.10', os: 'windows'} # todo: https://discuss.pytorch.org/t/numpy-is-not-available-error/146192
  include:

.github/workflows/ci-tests-full.yml

@@ -44,11 +44,8 @@ jobs:
  - {os: 'windows-2022', python-version: '3.9', pytorch-version: '1.13.1'}
  - {os: 'windows-2022', python-version: '3.10', pytorch-version: '2.0.0'}
  # the oldest configurations
- - {os: 'ubuntu-20.04', python-version: '3.7', pytorch-version: '1.8.1', requires: 'oldest'}
  - {os: 'ubuntu-20.04', python-version: '3.8', pytorch-version: '1.8.1', requires: 'oldest'}
- - {os: 'macOS-11', python-version: '3.7', pytorch-version: '1.8.1', requires: 'oldest'}
  - {os: 'macOS-11', python-version: '3.8', pytorch-version: '1.8.1', requires: 'oldest'}
- - {os: 'windows-2019', python-version: '3.7', pytorch-version: '1.8.1', requires: 'oldest'}
  - {os: 'windows-2019', python-version: '3.8', pytorch-version: '1.8.1', requires: 'oldest'}
  env:
  PYTORCH_URL: "https://download.pytorch.org/whl/cpu/torch_stable.html"

CHANGELOG.md

@@ -102,7 +102,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ### Removed
 
--
+- Support for python 3.7 ([#1640](https://github.com/Lightning-AI/metrics/pull/1640))
 
 
 ### Fixed

setup.py

@@ -201,7 +201,7 @@ def _prepare_extras(skip_files: Tuple[str] = ("devel.txt", "doctest.txt", "integ
  include_package_data=True,
  zip_safe=False,
  keywords=["deep learning", "machine learning", "pytorch", "metrics", "AI"],
- python_requires=">=3.7",
+ python_requires=">=3.8",
  setup_requires=[],
  install_requires=BASE_REQUIREMENTS,
  extras_require=_prepare_extras(),
@@ -227,7 +227,6 @@ def _prepare_extras(skip_files: Tuple[str] = ("devel.txt", "doctest.txt", "integ
  # Specify the Python versions you support here. In particular, ensure
  # that you indicate whether you support Python 2, Python 3 or both.
  "Programming Language :: Python :: 3",
- "Programming Language :: Python :: 3.7",
  "Programming Language :: Python :: 3.8",
  "Programming Language :: Python :: 3.9",
  "Programming Language :: Python :: 3.10",

tests/unittests/nominal/test_cramers.py

@@ -90,9 +90,6 @@ def _dython_cramers_v_matrix(matrix, bias_correction, nan_strategy, nan_replace_
 
 
 @pytest.mark.skipif(compare_version("pandas", operator.lt, "1.3.2"), reason="`dython` package requires `pandas>=1.3.2`")
-@pytest.mark.skipif( # TODO: testing on CUDA fails with pandas 1.3.5, and newer is not available for python 3.7
- torch.cuda.is_available(), reason="Tests fail on CUDA with the most up-to-date available pandas"
-)
 @pytest.mark.parametrize(
  "preds, target",
  [
@@ -167,9 +164,6 @@ def test_cramers_v_differentiability(self, preds, target, bias_correction, nan_s
 
 
 @pytest.mark.skipif(compare_version("pandas", operator.lt, "1.3.2"), reason="`dython` package requires `pandas>=1.3.2`")
-@pytest.mark.skipif( # TODO: testing on CUDA fails with pandas 1.3.5, and newer is not available for python 3.7
- torch.cuda.is_available(), reason="Tests fail on CUDA with the most up-to-date available pandas"
-)
 @pytest.mark.parametrize("bias_correction", [False, True])
 @pytest.mark.parametrize(("nan_strategy", "nan_replace_value"), [("replace", 1.0), ("drop", None)])
 def test_cramers_v_matrix(cramers_matrix_input, bias_correction, nan_strategy, nan_replace_value):

tests/unittests/nominal/test_pearson.py

@@ -77,9 +77,6 @@ def _pd_pearsons_t_matrix(matrix):
 
 
 @pytest.mark.skipif(compare_version("pandas", operator.lt, "1.3.2"), reason="`dython` package requires `pandas>=1.3.2`")
-@pytest.mark.skipif( # TODO: testing on CUDA fails with pandas 1.3.5, and newer is not available for python 3.7
- torch.cuda.is_available(), reason="Tests fail on CUDA with the most up-to-date available pandas"
-)
 @pytest.mark.parametrize(
  "preds, target",
  [
@@ -124,9 +121,6 @@ def test_pearsons_t_differentiability(self, preds, target):
 
 
 @pytest.mark.skipif(compare_version("pandas", operator.lt, "1.3.2"), reason="`dython` package requires `pandas>=1.3.2`")
-@pytest.mark.skipif( # TODO: testing on CUDA fails with pandas 1.3.5, and newer is not available for python 3.7
- torch.cuda.is_available(), reason="Tests fail on CUDA with the most up-to-date available pandas"
-)
 def test_pearsons_contingency_coefficient_matrix(pearson_matrix_input):
  """Test matrix version of metric works as expected."""
  tm_score = pearsons_contingency_coefficient_matrix(pearson_matrix_input)

tests/unittests/nominal/test_theils_u.py

@@ -88,9 +88,6 @@ def _dython_theils_u_matrix(matrix, nan_strategy, nan_replace_value):
 
 
 @pytest.mark.skipif(compare_version("pandas", operator.lt, "1.3.2"), reason="`dython` package requires `pandas>=1.3.2`")
-@pytest.mark.skipif( # TODO: testing on CUDA fails with pandas 1.3.5, and newer is not available for python 3.7
- torch.cuda.is_available(), reason="Tests fail on CUDA with the most up-to-date available pandas"
-)
 @pytest.mark.parametrize(
  "preds, target",
  [
@@ -159,9 +156,6 @@ def test_theils_u_differentiability(self, preds, target, nan_strategy, nan_repla
 
 
 @pytest.mark.skipif(compare_version("pandas", operator.lt, "1.3.2"), reason="`dython` package requires `pandas>=1.3.2`")
-@pytest.mark.skipif( # TODO: testing on CUDA fails with pandas 1.3.5, and newer is not available for python 3.7
- torch.cuda.is_available(), reason="Tests fail on CUDA with the most up-to-date available pandas"
-)
 @pytest.mark.parametrize(("nan_strategy", "nan_replace_value"), [("replace", 1.0), ("drop", None)])
 def test_theils_u_matrix(theils_u_matrix_input, nan_strategy, nan_replace_value):
  """Test matrix version of metric works as expected."""

tests/unittests/nominal/test_tschuprows.py

@@ -74,9 +74,6 @@ def _pd_tschuprows_t_matrix(matrix):
 
 
 @pytest.mark.skipif(compare_version("pandas", operator.lt, "1.3.2"), reason="`dython` package requires `pandas>=1.3.2`")
-@pytest.mark.skipif( # TODO: testing on CUDA fails with pandas 1.3.5, and newer is not available for python 3.7
- torch.cuda.is_available(), reason="Tests fail on CUDA with the most up-to-date available pandas"
-)
 @pytest.mark.parametrize(
  "preds, target",
  [
@@ -122,9 +119,6 @@ def test_tschuprows_t_differentiability(self, preds, target):
 
 
 @pytest.mark.skipif(compare_version("pandas", operator.lt, "1.3.2"), reason="`dython` package requires `pandas>=1.3.2`")
-@pytest.mark.skipif( # TODO: testing on CUDA fails with pandas 1.3.5, and newer is not available for python 3.7
- torch.cuda.is_available(), reason="Tests fail on CUDA with the most up-to-date available pandas"
-)
 def test_tschuprows_t_matrix(tschuprows_matrix_input):
  """Test matrix version of metric works as expected."""
  tm_score = tschuprows_t_matrix(tschuprows_matrix_input, bias_correction=False)