Merge pull request #151 from testingautomated-usi/tf-upgrade-basebranch

⬆️ various dependency-version related fixes

.github/workflows/examples.yml

@@ -13,7 +13,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.6, 3.7, 3.8]
+        python-version: [3.8]
 
     steps:
       - uses: actions/checkout@v2

.github/workflows/unit_tests.yml

@@ -9,8 +9,8 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.6, 3.7, 3.8]
-        tf-version: [2.3.0, 2.4.0, 2.5.0]
+        python-version: [3.8]
+        tf-version: [2.7.0, 2.8.0, 2.9.0, 2.10.0, 2.11.0]
 
     steps:
       - uses: actions/checkout@v2
@@ -30,6 +30,11 @@ jobs:
           pip install tensorflow==${{ matrix.tf-version }}
           pip install -r test_requirements.txt
 
+      # Lazy fix for fact that some py/tf combinations don't like new versions of protobuf
+      - name: Downgrade protobuf
+        run: |  
+          pip install protobuf==3.20.0 
+
       - name: Run Tests
         run: |
           bash scripts/run_coverage.sh

requirements.txt

@@ -1,3 +1,3 @@
-tensorflow>=2.3.0
+tensorflow>=2.7.0
 # The following is only required for python 3.6
-# dataclasses==0.6
+# dataclasses==0.6

tests_unit/internals_tests/test_tf_version_resolver.py

@@ -19,18 +19,18 @@ def test_current_tf_version_is_older_than_is_false(self):
         self.call_current_tf_is_older_than("2.0.0", False)
 
         # Test release candidate
-        self.call_current_tf_is_older_than("1.2.3_rc2", False)
+        self.call_current_tf_is_older_than("1.2.3rc2", False)
 
         # Call on same version
         self.call_current_tf_is_older_than(tf.__version__, False)
 
     def test_current_tf_version_is_older_than_is_true(self):
         # Test regular case
         self.call_current_tf_is_older_than("3.2.1", True)
-        self.call_current_tf_is_older_than("2.9.0", True)
+        self.call_current_tf_is_older_than("2.36.0", True)
 
         # Test release candidate
-        self.call_current_tf_is_older_than("3.2.1_rc1", True)
+        self.call_current_tf_is_older_than("3.2.1rc1", True)
 
     def test_tf_version_is_older_than_fallback(self):
         invalid = "1.2.invalid"
@@ -66,7 +66,7 @@ def test_current_tf_version_is_newer_is_true(self):
         self.call_current_tf_is_newer_than("2.0.0", True)
 
         # Test release candidate
-        self.call_current_tf_is_newer_than("1.2.3_rc2", True)
+        self.call_current_tf_is_newer_than("1.2.3rc2", True)
 
     def test_current_tf_version_is_newer_is_false(self):
         # Call on same version

tests_unit/keras_assumptions_tests/test_experimental_calls_exist.py

@@ -1,8 +1,13 @@
 import inspect
+import unittest
 from unittest import TestCase
 
 import tensorflow as tf
 
+from uncertainty_wizard.internal_utils.tf_version_resolver import (
+    current_tf_version_is_older_than,
+)
+
 
 class TestExperimentalAPIAreAvailable(TestCase):
     """
@@ -21,6 +26,9 @@ def test_list_physical_devices(self):
         self.assertTrue("device_type" in parameters)
         self.assertEqual(1, len(parameters))
 
+    @unittest.skipIf(
+        not current_tf_version_is_older_than("2.10.0"), "Known to fail for tf >= 2.10.0"
+    )
     def test_virtual_device_configuration(self):
         self.assertTrue("VirtualDeviceConfiguration" in dir(tf.config.experimental))
         parameters = inspect.signature(

uncertainty_wizard/internal_utils/tf_version_resolver.py

@@ -15,14 +15,15 @@ def _compare_expected_to_current_tf_version(expected_version) -> Union[None, int
     """
     actual_version = tf.version.VERSION
 
-    # Note: We're currently only considering versions in the format 'x.y.z'
-    # (i.e., ignore RCs and multi digit versions - which is probably fine given tfs very fast major release cycles)
+    # replaces rc, dev and b with dots to make the version strings comparable
+    dotted_actual_version = actual_version.replace("rc", ".-1.")
+    dotted_expected_version = expected_version.replace("rc", ".-1.")
 
     # Inspection disabling reason: We really want to catch all exceptions.
     # noinspection PyBroadException
     try:
-        expected_v_splits = [int(v) for v in expected_version[:5].split(".")]
-        actual_v_splits = [int(v) for v in actual_version[:5].split(".")]
+        expected_v_splits = [int(v) for v in dotted_expected_version.split(".")]
+        actual_v_splits = [int(v) for v in dotted_actual_version.split(".")]
     except Exception:
         warnings.warn(
             f"One of the version strings '{expected_version}' (requested) "
@@ -35,6 +36,11 @@ def _compare_expected_to_current_tf_version(expected_version) -> Union[None, int
         )
         return None
 
+    if len(expected_v_splits) > len(actual_v_splits):
+        actual_v_splits += [1000] * (len(expected_v_splits) - len(actual_v_splits))
+    elif len(expected_v_splits) < len(actual_v_splits):
+        expected_v_splits += [1000] * (len(actual_v_splits) - len(expected_v_splits))
+
     for act, expected in zip(actual_v_splits, expected_v_splits):
         if expected > act:
             return 1

uncertainty_wizard/models/ensemble_utils/_lazy_contexts.py

@@ -7,6 +7,9 @@
 
 import tensorflow as tf
 
+from uncertainty_wizard.internal_utils.tf_version_resolver import (
+    current_tf_version_is_older_than,
+)
 from uncertainty_wizard.models.ensemble_utils._save_config import SaveConfig
 
 global number_of_tasks_in_this_process
@@ -35,7 +38,7 @@ def __init__(self, model_id: int, varargs: dict = None):
         it will have to generate a context.
         Later, to make it easier for custom child classes of EnsembleContextManager,
         a (now still empty) varargs is also passed which may be populated with more information
-        in future versions of uncertainty_wizard.
+        in future s of uncertainty_wizard.
         """
         self.ensemble_id = (model_id,)
         self.varargs = varargs
@@ -225,6 +228,15 @@ class DeviceAllocatorContextManager(EnsembleContextManager, abc.ABC):
     the abstract methods.
     """
 
+    def __init__(self):
+        super().__init__()
+        if not current_tf_version_is_older_than("2.10.0"):
+            raise RuntimeError(
+                "The DeviceAllocatorContextManager is not compatible with tensorflow 2.10.0 "
+                "or newer. Please fall back to a single GPU for now (see issue #75),"
+                "or downgrade to tensorflow 2.9.0."
+            )
+
     # docstr-coverage: inherited
     def __enter__(self) -> "DeviceAllocatorContextManager":
         super().__enter__()