Merge branch 'master' into feature/hinge_loss

.github/workflows/ci_test-conda.yml

@@ -0,0 +1,76 @@
+name: PyTorch & Conda
+
+# see: https://help.github.com/en/actions/reference/events-that-trigger-workflows
+on:  # Trigger the workflow on push or pull request, but only for the master branch
+  push:
+    branches: [master, "release/*"]
+  pull_request:
+    branches: [master, "release/*"]
+
+jobs:
+  conda:
+    runs-on: ubuntu-20.04
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: [3.7]
+        pytorch-version: [1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9]
+
+    # Timeout: https://stackoverflow.com/a/59076067/4521646
+    timeout-minutes: 35
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Cache conda
+      uses: actions/cache@v2
+      with:
+        path: ~/conda_pkgs_dir
+        key: conda-py${{ matrix.python-version }}-pt${{ matrix.pytorch-version }}-${{ hashFiles('environment.yml') }}
+        restore-keys: conda-py${{ matrix.python-version }}-pt${{ matrix.pytorch-version }}-
+
+    # Add another cache for Pip as not all packages lives in Conda env
+    - name: Cache pip
+      uses: actions/cache@v2
+      with:
+        path: ~/.cache/pip
+        key: pip-py${{ matrix.python-version }}-pt${{ matrix.pytorch-version }}-${{ hashFiles('requirements/base.txt') }}
+        restore-keys: pip-py${{ matrix.python-version }}-pt${{ matrix.pytorch-version }}-
+
+    # https://docs.conda.io/projects/conda/en/4.6.0/_downloads/52a95608c49671267e40c689e0bc00ca/conda-cheatsheet.pdf
+    # https://gist.github.com/mwouts/9842452d020c08faf9e84a3bba38a66f
+    - name: Setup Miniconda
+      uses: conda-incubator/setup-miniconda@v2
+      with:
+        miniconda-version: "4.7.12"
+        python-version: ${{ matrix.python-version }}
+        channels: conda-forge,pytorch,pytorch-test,pytorch-nightly
+        channel-priority: true
+        auto-activate-base: true
+        # environment-file: ./environment.yml
+        use-only-tar-bz2: true # IMPORTANT: This needs to be set for caching to work properly!
+
+    - name: Update Environment
+      run: |
+        conda info
+        conda install pytorch=${{ matrix.pytorch-version }} cpuonly
+        conda list
+        pip --version
+        pip install --requirement requirements.txt --upgrade-strategy only-if-needed --quiet
+        pip install --requirement requirements/test.txt --upgrade-strategy only-if-needed --quiet
+        pip list
+        python -c "import torch; assert torch.__version__[:3] == '${{ matrix.pytorch-version }}', torch.__version__"
+      shell: bash -l {0}
+
+    - name: Testing
+      run: |
+        # NOTE: run coverage on tests does not propagare faler status for Win, https://github.com/nedbat/coveragepy/issues/1003
+        python -m pytest torchmetrics tests -v --durations=35 --junitxml=junit/test-conda-py${{ matrix.python-version }}-pt${{ matrix.pytorch-version }}.xml
+      shell: bash -l {0}
+
+    - name: Upload pytest test results
+      uses: actions/upload-artifact@master
+      with:
+        name: test-conda-py${{ matrix.python-version }}-pt${{ matrix.pytorch-version }}.xml
+        path: junit/test-conda-py${{ matrix.python-version }}-pt${{ matrix.pytorch-version }}.xml
+      # Use always() to always run this step to publish test results when there are test failures
+      if: failure()

MANIFEST.in

@@ -38,3 +38,4 @@ prune notebook*
 prune temp*
 prune test*
 prune benchmark*
+prune integration*

azure-pipelines.yml

@@ -84,5 +84,5 @@ jobs:
       condition: succeededOrFailed()
 
     - bash: |
-        python -m pytest integrations --durations=25
+        python -m pytest integrations -v --durations=25
       displayName: 'Integrations'

integrations/__init__.py

@@ -0,0 +1,3 @@
+from torchmetrics.utilities.imports import _module_available
+
+_PL_AVAILABLE = _module_available('pytorch_lightning')

integrations/lightning_models.py

@@ -11,6 +11,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
+
 import torch
 from pytorch_lightning import LightningModule
 from torch.utils.data import Dataset

setup.cfg

@@ -21,7 +21,10 @@ exclude_lines =
 
 [flake8]
 max-line-length = 120
-exclude = .tox,*.egg,build,temp
+exclude =
+    *.egg
+    build
+    temp
 select = E,W,F
 doctests = True
 verbose = 2

tests/classification/test_stat_scores.py

@@ -21,7 +21,7 @@
 from torch import Tensor, tensor
 
 from tests.classification.inputs import _input_binary, _input_binary_prob, _input_multiclass
-from tests.classification.inputs import _input_multiclass_prob as _input_mccls_prob
+from tests.classification.inputs import _input_multiclass_prob as _input_mcls_prob
 from tests.classification.inputs import _input_multidim_multiclass as _input_mdmc
 from tests.classification.inputs import _input_multidim_multiclass_prob as _input_mdmc_prob
 from tests.classification.inputs import _input_multilabel as _input_mcls
@@ -104,8 +104,8 @@ def _sk_stat_scores_mdim_mcls(preds, target, reduce, mdmc_reduce, num_classes, i
         ["macro", None, None, _input_binary, None],
         ["micro", None, None, _input_mdmc_prob, None],
         ["micro", None, None, _input_binary_prob, 0],
-        ["micro", None, None, _input_mccls_prob, NUM_CLASSES],
-        ["micro", None, NUM_CLASSES, _input_mccls_prob, NUM_CLASSES],
+        ["micro", None, None, _input_mcls_prob, NUM_CLASSES],
+        ["micro", None, NUM_CLASSES, _input_mcls_prob, NUM_CLASSES],
     ],
 )
 def test_wrong_params(reduce, mdmc_reduce, num_classes, inputs, ignore_index):
@@ -141,8 +141,8 @@ def test_wrong_threshold():
         (_input_mlb_prob.preds, _input_mlb_prob.target, _sk_stat_scores, None, NUM_CLASSES, None, None),
         (_input_mlb_prob.preds, _input_mlb_prob.target, _sk_stat_scores, None, NUM_CLASSES, None, 2),
         (_input_mcls.preds, _input_mcls.target, _sk_stat_scores, None, NUM_CLASSES, False, None),
-        (_input_mccls_prob.preds, _input_mccls_prob.target, _sk_stat_scores, None, NUM_CLASSES, None, None),
-        (_input_mccls_prob.preds, _input_mccls_prob.target, _sk_stat_scores, None, NUM_CLASSES, None, 2),
+        (_input_mcls_prob.preds, _input_mcls_prob.target, _sk_stat_scores, None, NUM_CLASSES, None, None),
+        (_input_mcls_prob.preds, _input_mcls_prob.target, _sk_stat_scores, None, NUM_CLASSES, None, 2),
         (_input_multiclass.preds, _input_multiclass.target, _sk_stat_scores, None, NUM_CLASSES, None, None),
         (_input_mdmc.preds, _input_mdmc.target, _sk_stat_scores_mdim_mcls, "samplewise", NUM_CLASSES, None, None),
         (

torchmetrics/utilities/imports.py

@@ -1,6 +1,64 @@
+# Copyright The PyTorch Lightning team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
 from distutils.version import LooseVersion
+from importlib import import_module
+from importlib.util import find_spec
 
 import torch
+from pkg_resources import DistributionNotFound
+
+
+def _module_available(module_path: str) -> bool:
+    """
+    Check if a path is available in your environment
+
+    >>> _module_available('os')
+    True
+    >>> _module_available('bla.bla')
+    False
+    """
+    try:
+        return find_spec(module_path) is not None
+    except AttributeError:
+        # Python 3.6
+        return False
+    except ModuleNotFoundError:
+        # Python 3.7+
+        return False
+
+
+def _compare_version(package: str, op, version) -> bool:
+    """
+    Compare package version with some requirements
+
+    >>> import operator
+    >>> _compare_version("torch", operator.ge, "0.1")
+    True
+    """
+    try:
+        pkg = import_module(package)
+    except (ModuleNotFoundError, DistributionNotFound):
+        return False
+    try:
+        pkg_version = LooseVersion(pkg.__version__)
+    except AttributeError:
+        return False
+    if not (hasattr(pkg_version, "vstring") and hasattr(pkg_version, "version")):
+        # this is mock by sphinx, so it shall return True ro generate all summaries
+        return True
+    return op(pkg_version, LooseVersion(version))
+
 
 _TORCH_LOWER_1_4 = LooseVersion(torch.__version__) < LooseVersion("1.4.0")
 _TORCH_LOWER_1_5 = LooseVersion(torch.__version__) < LooseVersion("1.5.0")