bump: support torch>=2.0

.azure/gpu-integrations.yml

@@ -17,9 +17,9 @@ jobs:
   - job: integrate_GPU
     strategy:
       matrix:
-        "torch | 1.x":
-          docker-image: "pytorchlightning/torchmetrics:ubuntu22.04-cuda11.8.0-py3.9-torch1.13"
-          torch-ver: "1.13"
+        "torch | 2.0":
+          docker-image: "pytorch/pytorch:2.0.1-cuda11.7-cudnn8-runtime"
+          torch-ver: "2.0"
           requires: "oldest"
         "torch | 2.x":
           docker-image: "pytorch/pytorch:2.4.0-cuda12.1-cudnn9-runtime"

.azure/gpu-unittests.yml

@@ -24,13 +24,10 @@ jobs:
   - job: unitest_GPU
     strategy:
       matrix:
-        "PyTorch | 1.10 oldest":
+        "PyTorch | 2.0 oldest":
           # Torch does not have build wheels with old Torch versions for newer CUDA
-          docker-image: "ubuntu20.04-cuda11.3.1-py3.9-torch1.10"
-          torch-ver: "1.10"
-        "PyTorch | 1.X LTS":
-          docker-image: "ubuntu22.04-cuda11.8.0-py3.9-torch1.13"
-          torch-ver: "1.13"
+          docker-image: "ubuntu22.04-cuda11.8.0-py3.10-torch2.0"
+          torch-ver: "2.0"
         "PyTorch | 2.X stable":
           docker-image: "ubuntu22.04-cuda12.1.1-py3.11-torch2.4"
           torch-ver: "2.4"
@@ -123,7 +120,7 @@ jobs:
 
       - bash: |
           python .github/assistant.py set-oldest-versions
-        condition: eq(variables['torch-ver'], '1.10')
+        condition: eq(variables['torch-ver'], '2.0')
         displayName: "Setting oldest versions"
 
       - bash: |
@@ -191,7 +188,7 @@ jobs:
         workingDirectory: "tests/"
         # skip for PR if there is nothing to test, note that outside PR there is default 'unittests'
         condition: and(succeeded(), ne(variables['TEST_DIRS'], ''))
-        timeoutInMinutes: "90"
+        timeoutInMinutes: "95"
         displayName: "UnitTesting common"
 
       - bash: |
@@ -203,7 +200,7 @@ jobs:
         workingDirectory: "tests/"
         # skip for PR if there is nothing to test, note that outside PR there is default 'unittests'
         condition: and(succeeded(), ne(variables['TEST_DIRS'], ''))
-        timeoutInMinutes: "90"
+        timeoutInMinutes: "95"
         displayName: "UnitTesting DDP"
 
       - bash: |

.github/workflows/ci-tests.yml

@@ -34,29 +34,22 @@ jobs:
         os: ["ubuntu-20.04"]
         python-version: ["3.9"]
         pytorch-version:
-          - "1.10.2"
-          - "1.11.0"
-          - "1.12.1"
-          - "1.13.1"
           - "2.0.1"
           - "2.1.2"
           - "2.2.2"
           - "2.3.1"
           - "2.4.0"
         include:
           # cover additional python and PT combinations
-          - { os: "ubuntu-22.04", python-version: "3.8", pytorch-version: "1.13.1" }
           - { os: "ubuntu-22.04", python-version: "3.10", pytorch-version: "2.0.1" }
           - { os: "ubuntu-22.04", python-version: "3.10", pytorch-version: "2.2.2" }
           - { os: "ubuntu-22.04", python-version: "3.11", pytorch-version: "2.3.1" }
           # standard mac machine, not the M1
-          - { os: "macOS-13", python-version: "3.8", pytorch-version: "1.13.1" }
           - { os: "macOS-13", python-version: "3.10", pytorch-version: "2.0.1" }
           # using the ARM based M1 machine
           - { os: "macOS-14", python-version: "3.10", pytorch-version: "2.0.1" }
           - { os: "macOS-14", python-version: "3.11", pytorch-version: "2.4.0" }
           # some windows
-          - { os: "windows-2022", python-version: "3.8", pytorch-version: "1.13.1" }
           - { os: "windows-2022", python-version: "3.10", pytorch-version: "2.0.1" }
           - { os: "windows-2022", python-version: "3.11", pytorch-version: "2.4.0" }
           # Future released version

.github/workflows/docker-build.yml

@@ -66,9 +66,6 @@ jobs:
         include:
           # These are the base images for PL release docker images,
           #  so include at least all the combinations in release-dockers.yml.
-          - { python: "3.9", pytorch: "1.10", cuda: "11.3.1", ubuntu: "20.04" }
-          #- { python: "3.9", pytorch: "1.11", cuda: "11.8.0", ubuntu: "22.04" }
-          - { python: "3.9", pytorch: "1.13", cuda: "11.8.0", ubuntu: "22.04" }
           - { python: "3.10", pytorch: "2.2", cuda: "12.1.1", ubuntu: "22.04" }
           - { python: "3.11", pytorch: "2.2", cuda: "12.1.1", ubuntu: "22.04" }
           - { python: "3.11", pytorch: "2.3", cuda: "12.1.1", ubuntu: "22.04" }

CHANGELOG.md

@@ -29,6 +29,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Tracker higher is better integration ([#2649](https://github.com/Lightning-AI/torchmetrics/pull/2649))
 
 
+- Changed minimum supported Pytorch version to 2.0 ([#2671](https://github.com/Lightning-AI/torchmetrics/pull/2671))
+
+
 - update `InfoLM` class to dynamically set `higher_is_better` ([#2674](https://github.com/Lightning-AI/torchmetrics/pull/2674))
 
 

requirements/_tests.txt

@@ -1,6 +1,7 @@
 # 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
 
+codecov ==2.1.13
 coverage ==7.6.*
 codecov ==2.1.13
 pytest ==8.3.*

requirements/audio.txt

@@ -4,8 +4,8 @@
 # this need to be the same as used inside speechmetrics
 pesq >=0.0.4, <0.0.5
 pystoi >=0.4.0, <0.5.0
-torchaudio >=0.10.0, <2.5.0
+torchaudio >=2.0.1, <2.5.0
 gammatone >=1.0.0, <1.1.0
-librosa >=0.9.0, <0.11.0
+librosa >=0.10.0, <0.11.0
 onnxruntime >=1.12.0, <1.20 # installing onnxruntime_gpu-gpu failed on macos
 requests >=2.19.0, <2.33.0

requirements/base.txt

@@ -3,6 +3,6 @@
 
 numpy >1.20.0, <2.0  # strict, for compatibility reasons
 packaging >17.1
-torch >=1.10.0, <2.5.0
+torch >=2.0.0, <2.5.0
 typing-extensions; python_version < '3.9'
 lightning-utilities >=0.8.0, <0.12.0

requirements/classification_test.txt

@@ -1,7 +1,7 @@
 # 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
 
-pandas >=1.4.0, <=2.2.2
+pandas >1.4.0, <=2.2.2
 netcal >1.0.0, <1.4.0 # calibration_error
 numpy <2.2.0
 fairlearn # group_fairness

requirements/detection.txt

@@ -1,5 +1,5 @@
 # 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
 
-torchvision >=0.8, <0.20.0
+torchvision >=0.15.1, <0.20.0
 pycocotools >2.0.0, <2.1.0

requirements/image.txt

@@ -2,5 +2,5 @@
 #  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
-torchvision >=0.8, <0.20.0
+torchvision >=0.15.1, <0.20.0
 torch-fidelity <=0.4.0  # bumping to allow install version from master, now used in testing

requirements/nominal_test.txt

@@ -1,7 +1,7 @@
 # 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
 
-pandas >1.0.0, <=2.2.2 # cannot pin version due to numpy version incompatibility
-dython <=0.7.7
+pandas >1.4.0, <=2.2.2 # cannot pin version due to numpy version incompatibility
+dython ==0.7.*
 scipy >1.0.0, <1.15.0 # cannot pin version due to some version conflicts with `oldest` CI configuration
 statsmodels >0.13.5, <0.15.0

requirements/visual.txt

@@ -1,5 +1,5 @@
 # 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
 
-matplotlib >=3.3.0, <3.10.0
+matplotlib >=3.5.0, <3.10.0
 SciencePlots >= 2.0.0, <2.2.0

src/torchmetrics/audio/__init__.py

@@ -28,10 +28,17 @@
     _ONNXRUNTIME_AVAILABLE,
     _PESQ_AVAILABLE,
     _PYSTOI_AVAILABLE,
+    _SCIPI_AVAILABLE,
     _TORCHAUDIO_AVAILABLE,
-    _TORCHAUDIO_GREATER_EQUAL_0_10,
 )
 
+if _SCIPI_AVAILABLE:
+    import scipy.signal
+
+    # back compatibility patch due to SMRMpy using scipy.signal.hamming
+    if not hasattr(scipy.signal, "hamming"):
+        scipy.signal.hamming = scipy.signal.windows.hamming
+
 __all__ = [
     "PermutationInvariantTraining",
     "ScaleInvariantSignalDistortionRatio",
@@ -52,7 +59,7 @@
 
     __all__ += ["ShortTimeObjectiveIntelligibility"]
 
-if _GAMMATONE_AVAILABLE and _TORCHAUDIO_AVAILABLE and _TORCHAUDIO_GREATER_EQUAL_0_10:
+if _GAMMATONE_AVAILABLE and _TORCHAUDIO_AVAILABLE:
     from torchmetrics.audio.srmr import SpeechReverberationModulationEnergyRatio
 
     __all__ += ["SpeechReverberationModulationEnergyRatio"]

src/torchmetrics/audio/srmr.py

@@ -24,11 +24,10 @@
     _GAMMATONE_AVAILABLE,
     _MATPLOTLIB_AVAILABLE,
     _TORCHAUDIO_AVAILABLE,
-    _TORCHAUDIO_GREATER_EQUAL_0_10,
 )
 from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
 
-if not all([_GAMMATONE_AVAILABLE, _TORCHAUDIO_AVAILABLE, _TORCHAUDIO_GREATER_EQUAL_0_10]):
+if not all([_GAMMATONE_AVAILABLE, _TORCHAUDIO_AVAILABLE]):
     __doctest_skip__ = ["SpeechReverberationModulationEnergyRatio", "SpeechReverberationModulationEnergyRatio.plot"]
 elif not _MATPLOTLIB_AVAILABLE:
     __doctest_skip__ = ["SpeechReverberationModulationEnergyRatio.plot"]
@@ -105,7 +104,7 @@ def __init__(
         **kwargs: Any,
     ) -> None:
         super().__init__(**kwargs)
-        if not _TORCHAUDIO_AVAILABLE or not _TORCHAUDIO_GREATER_EQUAL_0_10 or not _GAMMATONE_AVAILABLE:
+        if not _TORCHAUDIO_AVAILABLE or not _GAMMATONE_AVAILABLE:
             raise ModuleNotFoundError(
                 "speech_reverberation_modulation_energy_ratio requires you to have `gammatone` and"
                 " `torchaudio>=0.10` installed. Either install as ``pip install torchmetrics[audio]`` or "

src/torchmetrics/detection/__init__.py

@@ -12,22 +12,16 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 from torchmetrics.detection.panoptic_qualities import ModifiedPanopticQuality, PanopticQuality
-from torchmetrics.utilities.imports import (
-    _TORCHVISION_GREATER_EQUAL_0_8,
-    _TORCHVISION_GREATER_EQUAL_0_13,
-)
+
+from torchmetrics.utilities.imports import _TORCHVISION_AVAILABLE
 
 __all__ = ["ModifiedPanopticQuality", "PanopticQuality"]
 
 if _TORCHVISION_GREATER_EQUAL_0_8:
     from torchmetrics.detection.giou import GeneralizedIntersectionOverUnion
     from torchmetrics.detection.iou import IntersectionOverUnion
     from torchmetrics.detection.mean_ap import MeanAveragePrecision
-
-    __all__ += ["MeanAveragePrecision", "GeneralizedIntersectionOverUnion", "IntersectionOverUnion"]
-
-if _TORCHVISION_GREATER_EQUAL_0_13:
     from torchmetrics.detection.ciou import CompleteIntersectionOverUnion
     from torchmetrics.detection.diou import DistanceIntersectionOverUnion
 
-    __all__ += ["CompleteIntersectionOverUnion", "DistanceIntersectionOverUnion"]
+    __all__ += ["MeanAveragePrecision", "GeneralizedIntersectionOverUnion", "IntersectionOverUnion", "CompleteIntersectionOverUnion", "DistanceIntersectionOverUnion"]

src/torchmetrics/detection/_deprecated.py

@@ -1,17 +1,8 @@
 from typing import Any, Collection
 
 from torchmetrics.detection import ModifiedPanopticQuality, PanopticQuality
-from torchmetrics.utilities.imports import _TORCH_GREATER_EQUAL_1_12
 from torchmetrics.utilities.prints import _deprecated_root_import_class
 
-if not _TORCH_GREATER_EQUAL_1_12:
-    __doctest_skip__ = [
-        "_PanopticQuality",
-        "_PanopticQuality.*",
-        "_ModifiedPanopticQuality",
-        "_ModifiedPanopticQuality.*",
-    ]
-
 
 class _ModifiedPanopticQuality(ModifiedPanopticQuality):
     """Wrapper for deprecated import.

src/torchmetrics/detection/_mean_ap.py

@@ -22,13 +22,13 @@
 from torchmetrics.detection.helpers import _fix_empty_tensors, _input_validator
 from torchmetrics.metric import Metric
 from torchmetrics.utilities.data import _cumsum
-from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _PYCOCOTOOLS_AVAILABLE, _TORCHVISION_GREATER_EQUAL_0_8
+from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _PYCOCOTOOLS_AVAILABLE
 from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
 
 if not _MATPLOTLIB_AVAILABLE:
     __doctest_skip__ = ["MeanAveragePrecision.plot"]
 
-if not _TORCHVISION_GREATER_EQUAL_0_8 or not _PYCOCOTOOLS_AVAILABLE:
+if not _PYCOCOTOOLS_AVAILABLE:
     __doctest_skip__ = ["MeanAveragePrecision.plot", "MeanAveragePrecision"]
 
 log = logging.getLogger(__name__)
@@ -327,10 +327,10 @@ def __init__(
                 "`MAP` metric requires that `pycocotools` installed."
                 " Please install with `pip install pycocotools` or `pip install torchmetrics[detection]`"
             )
-        if not _TORCHVISION_GREATER_EQUAL_0_8:
+        if not _TORCHVISION_AVAILABLE:
             raise ModuleNotFoundError(
-                "`MeanAveragePrecision` metric requires that `torchvision` version 0.8.0 or newer is installed."
-                " Please install with `pip install torchvision>=0.8` or `pip install torchmetrics[detection]`."
+                "`MeanAveragePrecision` metric requires that `torchvision` is installed."
+                " Please install with `pip install torchmetrics[detection]`."
             )
 
         allowed_box_formats = ("xyxy", "xywh", "cxcywh")

src/torchmetrics/detection/ciou.py

@@ -17,10 +17,10 @@
 
 from torchmetrics.detection.iou import IntersectionOverUnion
 from torchmetrics.functional.detection.ciou import _ciou_compute, _ciou_update
-from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _TORCHVISION_GREATER_EQUAL_0_13
+from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _TORCHVISION_AVAILABLE
 from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
 
-if not _TORCHVISION_GREATER_EQUAL_0_13:
+if not _TORCHVISION_AVAILABLE:
     __doctest_skip__ = ["CompleteIntersectionOverUnion", "CompleteIntersectionOverUnion.plot"]
 elif not _MATPLOTLIB_AVAILABLE:
     __doctest_skip__ = ["CompleteIntersectionOverUnion.plot"]
@@ -110,10 +110,10 @@ def __init__(
         respect_labels: bool = True,
         **kwargs: Any,
     ) -> None:
-        if not _TORCHVISION_GREATER_EQUAL_0_13:
+        if not _TORCHVISION_AVAILABLE:
             raise ModuleNotFoundError(
-                f"Metric `{self._iou_type.upper()}` requires that `torchvision` version 0.13.0 or newer is installed."
-                " Please install with `pip install torchvision>=0.13` or `pip install torchmetrics[detection]`."
+                f"Metric `{self._iou_type.upper()}` requires that `torchvision` is installed."
+                " Please install with `pip install torchmetrics[detection]`."
             )
         super().__init__(box_format, iou_threshold, class_metrics, respect_labels, **kwargs)
 

src/torchmetrics/detection/diou.py

@@ -17,10 +17,10 @@
 
 from torchmetrics.detection.iou import IntersectionOverUnion
 from torchmetrics.functional.detection.diou import _diou_compute, _diou_update
-from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _TORCHVISION_GREATER_EQUAL_0_13
+from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _TORCHVISION_AVAILABLE
 from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
 
-if not _TORCHVISION_GREATER_EQUAL_0_13:
+if not _TORCHVISION_AVAILABLE:
     __doctest_skip__ = ["DistanceIntersectionOverUnion", "DistanceIntersectionOverUnion.plot"]
 elif not _MATPLOTLIB_AVAILABLE:
     __doctest_skip__ = ["DistanceIntersectionOverUnion.plot"]
@@ -110,10 +110,10 @@ def __init__(
         respect_labels: bool = True,
         **kwargs: Any,
     ) -> None:
-        if not _TORCHVISION_GREATER_EQUAL_0_13:
+    if not _TORCHVISION_AVAILABLE:
             raise ModuleNotFoundError(
-                f"Metric `{self._iou_type.upper()}` requires that `torchvision` version 0.13.0 or newer is installed."
-                " Please install with `pip install torchvision>=0.13` or `pip install torchmetrics[detection]`."
+                f"Metric `{self._iou_type.upper()}` requires that `torchvision` is installed."
+                " Please install with `pip install torchmetrics[detection]`."
             )
         super().__init__(box_format, iou_threshold, class_metrics, respect_labels, **kwargs)
 

src/torchmetrics/detection/giou.py

@@ -17,10 +17,10 @@
 
 from torchmetrics.detection.iou import IntersectionOverUnion
 from torchmetrics.functional.detection.giou import _giou_compute, _giou_update
-from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _TORCHVISION_GREATER_EQUAL_0_8
+from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _TORCHVISION_AVAILABLE
 from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
 
-if not _TORCHVISION_GREATER_EQUAL_0_8:
+if not _TORCHVISION_AVAILABLE:
     __doctest_skip__ = ["GeneralizedIntersectionOverUnion", "GeneralizedIntersectionOverUnion.plot"]
 elif not _MATPLOTLIB_AVAILABLE:
     __doctest_skip__ = ["GeneralizedIntersectionOverUnion.plot"]

src/torchmetrics/detection/iou.py

@@ -20,10 +20,10 @@
 from torchmetrics.functional.detection.iou import _iou_compute, _iou_update
 from torchmetrics.metric import Metric
 from torchmetrics.utilities.data import dim_zero_cat
-from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _TORCHVISION_GREATER_EQUAL_0_8
+from torchmetrics.utilities.imports import _MATPLOTLIB_AVAILABLE, _TORCHVISION_AVAILABLE
 from torchmetrics.utilities.plot import _AX_TYPE, _PLOT_OUT_TYPE
 
-if not _TORCHVISION_GREATER_EQUAL_0_8:
+if not _TORCHVISION_AVAILABLE:
     __doctest_skip__ = ["IntersectionOverUnion", "IntersectionOverUnion.plot"]
 elif not _MATPLOTLIB_AVAILABLE:
     __doctest_skip__ = ["IntersectionOverUnion.plot"]
@@ -146,12 +146,12 @@ def __init__(
     ) -> None:
         super().__init__(**kwargs)
 
-        if not _TORCHVISION_GREATER_EQUAL_0_8:
+    ) -> None:
+    if not _TORCHVISION_AVAILABLE:
             raise ModuleNotFoundError(
-                f"Metric `{self._iou_type.upper()}` requires that `torchvision` version 0.8.0 or newer is installed."
-                " Please install with `pip install torchvision>=0.8` or `pip install torchmetrics[detection]`."
+                f"Metric `{self._iou_type.upper()}` requires that `torchvision` is installed."
+                " Please install with `pip install torchmetrics[detection]`."
             )
-
         allowed_box_formats = ("xyxy", "xywh", "cxcywh")
         if box_format not in allowed_box_formats:
             raise ValueError(f"Expected argument `box_format` to be one of {allowed_box_formats} but got {box_format}")