Merge branch 'master' into optional_num_classes

.github/assistant.py

@@ -132,11 +132,24 @@ def changed_domains(
         if not files:
             logging.debug("Only integrations was changed so not reason for deep testing...")
             return _return_empty
+
         # filter only docs files
         files_docs = [fn for fn in files if fn.startswith("docs")]
         if len(files) == len(files_docs):
             logging.debug("Only docs was changed so not reason for deep testing...")
             return _return_empty
+
+        files_markdown = [fn for fn in files if fn.endswith(".md")]
+        if len(files) == len(files_markdown):
+            logging.debug("Only markdown files was changed so not reason for deep testing...")
+            return _return_empty
+
+        # filter only testing files which are not specific tests so for example configurations or helper tools
+        files_testing = [fn for fn in files if fn.startswith("tests") and not fn.endswith(".md") and "test_" not in fn]
+        if files_testing:
+            logging.debug("Some testing files was changed -> rather test everything...")
+            return _return_all
+
         # files in requirements folder
         files_req = [fn for fn in files if fn.startswith("requirements")]
         req_domains = [fn.split("/")[1] for fn in files_req]
@@ -147,19 +160,21 @@ def changed_domains(
             return _return_all
 
         # filter only package files and skip inits
-        _is_in_test = lambda fn: fn.startswith("tests")
-        _filter_pkg = lambda fn: _is_in_test(fn) or (fn.startswith("src/torchmetrics") and "__init__.py" not in fn)
+        _is_in_test = lambda fname: fname.startswith("tests")
+        _filter_pkg = lambda fname: _is_in_test(fname) or (
+            fname.startswith("src/torchmetrics") and "__init__.py" not in fname
+        )
         files_pkg = [fn for fn in files if _filter_pkg(fn)]
         if not files_pkg:
             return _return_all
 
         # parse domains
-        def _crop_path(fname: str, paths: list[str]) -> str:
+        def _crop_path(fname: str, paths: tuple[str] = ("src/torchmetrics/", "tests/unittests/", "functional/")) -> str:
             for p in paths:
                 fname = fname.replace(p, "")
             return fname
 
-        files_pkg = [_crop_path(fn, ["src/torchmetrics/", "tests/unittests/", "functional/"]) for fn in files_pkg]
+        files_pkg = [_crop_path(fn) for fn in files_pkg]
         # filter domain names
         tm_modules = [fn.split("/")[0] for fn in files_pkg if "/" in fn]
         # filter general (used everywhere) sub-packages

.github/workflows/ci-integrate.yml

@@ -36,7 +36,7 @@ jobs:
           - { python-version: "3.10", requires: "latest", os: "ubuntu-22.04" }
           # - { python-version: "3.10", requires: "latest", os: "macOS-14" } # M1 machine # todo: crashing for MPS out of memory
     env:
-      PYTORCH_URL: "https://download.pytorch.org/whl/cpu/torch_stable.html"
+      PYTORCH_URL: "https://download.pytorch.org/whl/cpu/"
       FREEZE_REQUIREMENTS: ${{ ! (github.ref == 'refs/heads/master' || startsWith(github.ref, 'refs/heads/release/')) }}
       PYPI_CACHE: "_ci-cache_PyPI"
 
@@ -64,7 +64,7 @@ jobs:
           # this was updated in `source cashing` by optional oldest
           cat requirements/_integrate.txt
           # to have install pyTorch
-          pip install -e . "setuptools==69.5.1" --find-links=${PYTORCH_URL}
+          pip install -e . "setuptools==69.5.1" --extra-index-url=${PYTORCH_URL}
 
           # adjust version to PT ecosystem based on installed TM
           python -m wget https://raw.githubusercontent.com/Lightning-AI/utilities/main/scripts/adjust-torch-versions.py
@@ -73,7 +73,7 @@ jobs:
 
           # install package and dependencies
           pip install -e . -r requirements/_tests.txt -r requirements/_integrate.txt \
-            --find-links=${PYTORCH_URL} --find-links=${PYPI_CACHE} \
+            --extra-index-url="${PYTORCH_URL}" --find-links="${PYPI_CACHE}" \
             --upgrade-strategy eager
           pip list
 

.github/workflows/ci-tests.yml

@@ -64,7 +64,7 @@ jobs:
       FREEZE_REQUIREMENTS: ${{ ! (github.ref == 'refs/heads/master' || startsWith(github.ref, 'refs/heads/release/')) }}
       TOKENIZERS_PARALLELISM: false
       TEST_DIRS: ${{ needs.check-diff.outputs.test-dirs }}
-      PIP_EXTRA_INDEX_URL: "--find-links=https://download.pytorch.org/whl/cpu/torch_stable.html"
+      PIP_EXTRA_INDEX_URL: "--extra-index-url=https://download.pytorch.org/whl/cpu/"
       UNITTEST_TIMEOUT: "" # by default, it is not set
 
     # Timeout: https://stackoverflow.com/a/59076067/4521646

.github/workflows/docs-build.yml

@@ -18,7 +18,7 @@ defaults:
 
 env:
   FREEZE_REQUIREMENTS: "1"
-  TORCH_URL: "https://download.pytorch.org/whl/cpu/torch_stable.html"
+  TORCH_URL: "https://download.pytorch.org/whl/cpu/"
   PYPI_CACHE: "_ci-cache_PyPI"
   PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION: "python"
   TOKENIZERS_PARALLELISM: false
@@ -39,7 +39,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v5
         with:
-          python-version: "3.9"
+          python-version: "3.x"
 
       - name: source cashing
         uses: ./.github/actions/pull-caches
@@ -52,7 +52,7 @@ jobs:
           make get-sphinx-template
           # install with -e so the path to source link comes from this project not from the installed package
           pip install -e . -U -r requirements/_docs.txt \
-            --find-links="${PYPI_CACHE}" --find-links="${TORCH_URL}"
+            --find-links="${PYPI_CACHE}" --extra-index-url="${TORCH_URL}"
       - run: pip list
       - name: Full build for deployment
         if: github.event_name != 'pull_request'

.pre-commit-config.yaml

@@ -23,7 +23,7 @@ ci:
 
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.6.0
+    rev: v5.0.0
     hooks:
       - id: end-of-file-fixer
       - id: trailing-whitespace
@@ -46,11 +46,10 @@ repos:
         exclude: pyproject.toml
 
   - repo: https://github.com/crate-ci/typos
-    rev: v1.22.9
+    rev: dictgen-v0.3.1
     hooks:
       - id: typos
-        # empty to do not write fixes
-        args: []
+        args: [] # empty to do not write fixes
         exclude: pyproject.toml
 
   - repo: https://github.com/PyCQA/docformatter
@@ -61,12 +60,12 @@ repos:
         args: ["--in-place"]
 
   - repo: https://github.com/sphinx-contrib/sphinx-lint
-    rev: v0.9.1
+    rev: v1.0.0
     hooks:
       - id: sphinx-lint
 
   - repo: https://github.com/executablebooks/mdformat
-    rev: 0.7.17
+    rev: 0.7.21
     hooks:
       - id: mdformat
         args: ["--number"]
@@ -113,7 +112,7 @@ repos:
       - id: text-unicode-replacement-char
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.5.0
+    rev: v0.8.6
     hooks:
       # try to fix what is possible
       - id: ruff
@@ -124,11 +123,11 @@ repos:
       - id: ruff
 
   - repo: https://github.com/tox-dev/pyproject-fmt
-    rev: 2.1.3
+    rev: v2.5.0
     hooks:
       - id: pyproject-fmt
         additional_dependencies: [tox]
   - repo: https://github.com/abravalheri/validate-pyproject
-    rev: v0.18
+    rev: v0.23
     hooks:
       - id: validate-pyproject

CHANGELOG.md

@@ -842,7 +842,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   * `PearsonCorrcoef`
   * `SpearmanCorrcoef`
 - Removed deprecated functions, and warnings in detection and pairwise ([#804](https://github.com/Lightning-AI/metrics/pull/804))
-  * `MAP` and `functional.pairwise.manhatten`
+  * `MAP` and `functional.pairwise.manhattan`
 - Removed deprecated functions, and warnings in Audio ([#805](https://github.com/Lightning-AI/metrics/pull/805))
   * `PESQ` and `functional.audio.pesq`
   * `PIT` and `functional.audio.pit`
@@ -1032,7 +1032,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   - `pairwise_cosine_similarity`
   - `pairwise_euclidean_distance`
   - `pairwise_linear_similarity`
-  - `pairwise_manhatten_distance`
+  - `pairwise_manhattan_distance`
 
 ### Changed
 

_samples/bert_score-own_model.py

@@ -23,6 +23,7 @@
 import torch
 from torch import Tensor, nn
 from torch.nn import Module
+
 from torchmetrics.text.bert import BERTScore
 
 _NUM_LAYERS = 2

_samples/detection_map.py

@@ -14,6 +14,7 @@
 """An example of how the predictions and target should be defined for the MAP object detection metric."""
 
 from torch import BoolTensor, IntTensor, Tensor
+
 from torchmetrics.detection.mean_ap import MeanAveragePrecision
 
 # Preds should be a list of elements, where each element is a dict

docs/source/conf.py

@@ -18,9 +18,10 @@
 from typing import Optional
 
 import lai_sphinx_theme
-import torchmetrics
 from lightning_utilities.docs.formatting import _linkcode_resolve, _transform_changelog
 
+import torchmetrics
+
 _PATH_HERE = os.path.abspath(os.path.dirname(__file__))
 _PATH_ROOT = os.path.realpath(os.path.join(_PATH_HERE, "..", ".."))
 sys.path.insert(0, os.path.abspath(_PATH_ROOT))

docs/source/pages/implement.rst

@@ -30,7 +30,7 @@ We provide the remaining interface, such as ``reset()`` that will make sure to c
 states that have been added using ``add_state``. You should therefore not implement ``reset()`` yourself, only in rare
 cases where not all the state variables should be reset to their default value. Adding metric states with ``add_state``
 will make sure that states are correctly synchronized in distributed settings (DDP). To see how metric states are
-synchronized across distributed processes, refer to :meth:`~torchmetrics.Metric.add_state()` docs from the base
+synchronized across distributed processes, refer to :meth:`~torchmetrics.Metric.add_state` docs from the base
 :class:`~torchmetrics.Metric` class.
 
 Below is a basic implementation of a custom accuracy metric. In the ``__init__`` method we add the metric states

docs/source/pyplots/binary_accuracy.py

@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import torch
+
 import torchmetrics
 
 N = 10

docs/source/pyplots/binary_accuracy_multistep.py

@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import torch
+
 import torchmetrics
 
 N = 10

docs/source/pyplots/collection_binary.py

@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import torch
+
 import torchmetrics
 
 N = 10

docs/source/pyplots/collection_binary_together.py

@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import torch
+
 import torchmetrics
 
 N = 10

docs/source/pyplots/confusion_matrix.py

@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import torch
+
 import torchmetrics
 
 N = 10

docs/source/pyplots/multiclass_accuracy.py

@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import torch
+
 import torchmetrics
 
 N = 10

docs/source/pyplots/tracker_binary.py

@@ -1,5 +1,6 @@
 import matplotlib.pyplot as plt
 import torch
+
 import torchmetrics
 
 N = 10

examples/audio/pesq.py

@@ -19,6 +19,7 @@
 import numpy as np
 import torch
 import torchaudio
+
 from torchmetrics.audio import PerceptualEvaluationSpeechQuality
 
 # %%

examples/audio/signal_to_noise_ratio.py

@@ -13,6 +13,7 @@
 import matplotlib.pyplot as plt
 import numpy as np
 import torch
+
 from torchmetrics.audio import SignalNoiseRatio
 
 # %%

examples/image/clip_score.py

@@ -15,6 +15,7 @@
 import torch
 from matplotlib.table import Table
 from skimage.data import astronaut, cat, coffee
+
 from torchmetrics.multimodal import CLIPScore
 
 # %%

examples/image/spatial_correlation_coef.py

@@ -16,6 +16,7 @@
 import torch
 from skimage.data import shepp_logan_phantom
 from skimage.transform import iradon, radon, rescale
+
 from torchmetrics.image import SpatialCorrelationCoefficient
 
 # %%

examples/text/bertscore.py

@@ -6,9 +6,10 @@
 Let's consider a use case in natural language processing where BERTScore is used to evaluate the quality of a text generation model. In this case we are imaging that we are developing a automated news summarization system. The goal is to create concise summaries of news articles that accurately capture the key points of the original articles. To evaluate the performance of your summarization system, you need a metric that can compare the generated summaries to human-written summaries. This is where the BERTScore can be used.
 """
 
-from torchmetrics.text import BERTScore, ROUGEScore
 from transformers import AutoTokenizer, pipeline
 
+from torchmetrics.text import BERTScore, ROUGEScore
+
 pipe = pipeline("text-generation", model="openai-community/gpt2")
 tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2")
 

examples/text/perplexity.py

@@ -12,9 +12,10 @@
 # Here's a hypothetical Python example demonstrating the usage of Perplexity to evaluate a generative language model
 
 import torch
-from torchmetrics.text import Perplexity
 from transformers import AutoModelWithLMHead, AutoTokenizer
 
+from torchmetrics.text import Perplexity
+
 # %%
 # Load the GPT-2 model and tokenizer
 

examples/text/rouge.py

@@ -9,9 +9,10 @@
 # %%
 # Here's a hypothetical Python example demonstrating the usage of unigram ROUGE F-score to evaluate a generative language model:
 
-from torchmetrics.text import ROUGEScore
 from transformers import AutoTokenizer, pipeline
 
+from torchmetrics.text import ROUGEScore
+
 pipe = pipeline("text-generation", model="openai-community/gpt2")
 tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2")
 

requirements/image.txt

@@ -1,6 +1,6 @@
 # NOTE: the upper bound for the package version is only set for CI stability, and it is dropped while installing this package
 #  in case you want to preserve/enforce restrictions on the latest compatible version, add "strict" as an in-line comment
 
-scipy >1.0.0, <1.15.0
+scipy >1.0.0, <1.16.0
 torchvision >=0.15.1, <0.22.0
 torch-fidelity <=0.4.0  # bumping to allow install version from master, now used in testing

requirements/nominal_test.txt

@@ -3,6 +3,6 @@
 
 pandas >1.4.0, <=2.2.3 # cannot pin version due to numpy version incompatibility
 dython ==0.7.6 ; python_version <"3.9"
-dython ~=0.7.8 ; python_version > "3.8"  # we do not use `> =`
-scipy >1.0.0, <1.15.0 # cannot pin version due to some version conflicts with `oldest` CI configuration
+dython ==0.7.9 ; python_version > "3.8"  # we do not use `> =`
+scipy >1.0.0, <1.16.0 # cannot pin version due to some version conflicts with `oldest` CI configuration
 statsmodels >0.13.5, <0.15.0

requirements/segmentation_test.txt

@@ -1,6 +1,6 @@
 # NOTE: the upper bound for the package version is only set for CI stability, and it is dropped while installing this package
 #  in case you want to preserve/enforce restrictions on the latest compatible version, add "strict" as an in-line comment
 
-scipy >1.0.0, <1.15.0
+scipy >1.0.0, <1.16.0
 monai ==1.3.2 ; python_version < "3.9"
 monai ==1.4.0 ; python_version > "3.8"

requirements/text_test.txt

@@ -5,7 +5,7 @@ jiwer >=2.3.0, <3.1.0
 rouge-score >0.1.0, <=0.1.2
 bert_score ==0.3.13
 huggingface-hub <0.28
-sacrebleu >=2.3.0, <2.5.0
+sacrebleu >=2.3.0, <2.6.0
 
 mecab-ko >=1.0.0, <1.1.0 ; python_version < "3.12"  # strict # todo: unpin python_version
 mecab-ko-dic >=1.0.0, <1.1.0 ; python_version < "3.12"  # todo: unpin python_version

src/conftest.py

@@ -11,7 +11,7 @@
     MANUAL_SEED = doctest.register_optionflag("MANUAL_SEED")
 
     @pytest.fixture(autouse=True)
-    def reset_random_seed(seed: int = 42) -> None:  # noqa: PT004
+    def reset_random_seed(seed: int = 42) -> None:
         """Reset the random seed before running each doctest."""
         import random