fix compatibility to PL (#192)

* fix compatibility

* local

* flake8

* drop 3.6 min

* .

.github/workflows/ci_test-full.yml

@@ -20,6 +20,8 @@ jobs:
         python-version: [3.6, 3.8, 3.9]
         requires: ['minimal', 'latest']
         exclude:
+          - python-version: 3.6
+            requires: 'latest'
           - python-version: 3.9
             requires: 'minimal'
 

LICENSE

@@ -186,7 +186,7 @@
       same "printed page" as the copyright notice for easier
       identification within third-party archives.
 
-   Copyright 2018-2021 William Falcon
+   Copyright 2020-2021 PytorchLightning team
 
    Licensed under the Apache License, Version 2.0 (the "License");
    you may not use this file except in compliance with the License.

integrations/__init__.py

@@ -1,3 +1,5 @@
-from torchmetrics.utilities.imports import _module_available
+import operator
 
-_PL_AVAILABLE = _module_available('pytorch_lightning')
+from torchmetrics.utilities.imports import _compare_version
+
+_LIGHTNING_GREATER_EQUAL_1_3 = _compare_version("pytorch_lightning", operator.ge, "1.3.0")

integrations/test_metric_lightning.py

@@ -20,8 +20,8 @@ from torch import tensor
 from torch.utils.data import DataLoader
 
 from integrations.lightning_models import BoringModel, RandomDataset
+from tests.helpers import _LIGHTNING_GREATER_EQUAL_1_3
 from torchmetrics import Accuracy, AveragePrecision, Metric
-from torchmetrics.utilities.imports import _LIGHTNING_GREATER_EQUAL_1_3
 
 
 class SumMetric(Metric):

tests/bases/test_metric.py

@@ -20,9 +20,9 @@ import pytest
 import torch
 from torch import nn, tensor
 
-from tests.helpers import seed_all
+from tests.helpers import _LIGHTNING_GREATER_EQUAL_1_3, seed_all
 from tests.helpers.testers import DummyListMetric, DummyMetric, DummyMetricSum
-from torchmetrics.utilities.imports import _LIGHTNING_AVAILABLE, _LIGHTNING_GREATER_EQUAL_1_3, _TORCH_LOWER_1_6
+from torchmetrics.utilities.imports import _LIGHTNING_AVAILABLE, _TORCH_LOWER_1_6
 
 seed_all(42)
 

tests/helpers/__init__.py

@@ -1,14 +1,17 @@
+import operator
 import random
 
 import numpy
 import torch
 
-from torchmetrics.utilities.imports import _TORCH_LOWER_1_4, _TORCH_LOWER_1_5, _TORCH_LOWER_1_6
+from torchmetrics.utilities.imports import _TORCH_LOWER_1_4, _TORCH_LOWER_1_5, _TORCH_LOWER_1_6, _compare_version
 
 _MARK_TORCH_MIN_1_4 = dict(condition=_TORCH_LOWER_1_4, reason="required PT >= 1.4")
 _MARK_TORCH_MIN_1_5 = dict(condition=_TORCH_LOWER_1_5, reason="required PT >= 1.5")
 _MARK_TORCH_MIN_1_6 = dict(condition=_TORCH_LOWER_1_6, reason="required PT >= 1.6")
 
+_LIGHTNING_GREATER_EQUAL_1_3 = _compare_version("pytorch_lightning", operator.ge, "1.3.0")
+
 
 def seed_all(seed):
     random.seed(seed)

torchmetrics/metric.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 import functools
 import inspect
+import operator
 from abc import ABC, abstractmethod
 from collections.abc import Sequence
 from copy import deepcopy
@@ -24,7 +25,7 @@ from torch import Tensor, nn
 from torchmetrics.utilities import apply_to_collection
 from torchmetrics.utilities.data import _flatten, dim_zero_cat, dim_zero_mean, dim_zero_sum
 from torchmetrics.utilities.distributed import gather_all_tensors
-from torchmetrics.utilities.imports import _LIGHTNING_AVAILABLE, _LIGHTNING_GREATER_EQUAL_1_3
+from torchmetrics.utilities.imports import _LIGHTNING_AVAILABLE, _compare_version
 
 
 class Metric(nn.Module, ABC):
@@ -70,6 +71,7 @@ class Metric(nn.Module, ABC):
         dist_sync_fn: Callable = None,
     ):
         super().__init__()
+        self._LIGHTNING_GREATER_EQUAL_1_3 = _compare_version("pytorch_lightning", operator.ge, "1.3.0")
 
         self.dist_sync_on_step = dist_sync_on_step
         self.compute_on_step = compute_on_step
@@ -257,9 +259,8 @@ class Metric(nn.Module, ABC):
         """
         This method automatically resets the metric state variables to their default value.
         """
-        # lower lightning versions requires this implicitly to log metric objects correctly
-        # in self.log
-        if not _LIGHTNING_AVAILABLE or _LIGHTNING_GREATER_EQUAL_1_3:
+        # lower lightning versions requires this implicitly to log metric objects correctly in self.log
+        if not _LIGHTNING_AVAILABLE or self._LIGHTNING_GREATER_EQUAL_1_3:
             self._computed = None
 
         for attr, default in self._defaults.items():

torchmetrics/utilities/imports.py

@@ -47,7 +47,10 @@ def _compare_version(package: str, op, version) -> Optional[bool]:
     >>> import operator
     >>> _compare_version("torch", operator.ge, "0.1")
     True
+    >>> _compare_version("any_module", operator.ge, "0.0")  # is None
     """
+    if not _module_available(package):
+        return None
     try:
         pkg = import_module(package)
         pkg_version = pkg.__version__
@@ -71,4 +74,3 @@ _TORCH_LOWER_1_6 = _compare_version("torch", operator.lt, "1.6.0")
 _TORCH_GREATER_EQUAL_1_6 = _compare_version("torch", operator.ge, "1.6.0")
 _TORCH_GREATER_EQUAL_1_7 = _compare_version("torch", operator.ge, "1.7.0")
 _LIGHTNING_AVAILABLE = _module_available("pytorch_lightning")
-_LIGHTNING_GREATER_EQUAL_1_3 = _compare_version("pytorch_lightning", operator.ge, "1.3.0")