Bundle recent deps updates (#233)

* Bump pandas from 1.5.2 to 2.2.3

Bumps [pandas](https://github.com/pandas-dev/pandas) from 1.5.2 to 2.2.3.
- [Release notes](https://github.com/pandas-dev/pandas/releases)
- [Commits](pandas-dev/pandas@v1.5.2...v2.2.3)

---
updated-dependencies:
- dependency-name: pandas
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <[email protected]>

* Bump actions/setup-python from 4 to 5

Bumps [actions/setup-python](https://github.com/actions/setup-python) from 4 to 5.
- [Release notes](https://github.com/actions/setup-python/releases)
- [Commits](actions/setup-python@v4...v5)

---
updated-dependencies:
- dependency-name: actions/setup-python
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <[email protected]>

* Use `pip` cache for linting step

* Bump actions/checkout from 3 to 4

Bumps [actions/checkout](https://github.com/actions/checkout) from 3 to 4.
- [Release notes](https://github.com/actions/checkout/releases)
- [Changelog](https://github.com/actions/checkout/blob/main/CHANGELOG.md)
- [Commits](actions/checkout@v3...v4)

---
updated-dependencies:
- dependency-name: actions/checkout
  dependency-type: direct:production
  update-type: version-update:semver-major
...

Signed-off-by: dependabot[bot] <[email protected]>

* Bump tensorflow from 2.11.0 to 2.16.1

Bumps [tensorflow](https://github.com/tensorflow/tensorflow) from 2.11.0 to 2.16.1.
- [Release notes](https://github.com/tensorflow/tensorflow/releases)
- [Changelog](https://github.com/tensorflow/tensorflow/blob/v2.16.1/RELEASE.md)
- [Commits](tensorflow/tensorflow@v2.11.0...v2.16.1)

---
updated-dependencies:
- dependency-name: tensorflow
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <[email protected]>

* Bump scikit-learn from 1.3.2 to 1.5.2

Bumps [scikit-learn](https://github.com/scikit-learn/scikit-learn) from 1.3.2 to 1.5.2.
- [Release notes](https://github.com/scikit-learn/scikit-learn/releases)
- [Commits](scikit-learn/scikit-learn@1.3.2...1.5.2)

---
updated-dependencies:
- dependency-name: scikit-learn
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <[email protected]>

* Bump pymatgen from 2024.3.1 to 2024.5.31

Bumps [pymatgen](https://github.com/materialsproject/pymatgen) from 2024.3.1 to 2024.5.31.
- [Release notes](https://github.com/materialsproject/pymatgen/releases)
- [Changelog](https://github.com/materialsproject/pymatgen/blob/master/docs/CHANGES.md)
- [Commits](materialsproject/pymatgen@v2024.3.1...v2024.5.31)

---
updated-dependencies:
- dependency-name: pymatgen
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <[email protected]>

* Remove deprecated Bayesian model tests from CI run

* Add CI debug print of installed versions

* Downgrade tensorflow to avoid needing keras downgrade

* Try to deprecate 'learning_rate' again

* Take all models from ensemble when refitting in `fit_preset`

No idea how this wasn't triggered in the tests previously...

---------

Signed-off-by: dependabot[bot] <[email protected]>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>

.github/workflows/ci.yml

@@ -17,18 +17,21 @@ jobs:
 
     steps:
 
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
 
     - name: Set up Python 3.10
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: '3.10'
+        cache: pip
+        cache-dependency-path: |
+          **/requirements*.txt
 
     - name: Install pre-commit
       run: |
         python -m pip install --upgrade pip
         pip install -U setuptools wheel
-        pip install .[dev,bayesian]
+        pip install .[dev]
 
     - name: Run pre-commit
       run: |
@@ -45,10 +48,10 @@ jobs:
 
     steps:
 
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
 
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v4
+      uses: actions/setup-python@v5
       with:
         python-version: ${{ matrix.python-version }}
         cache: 'pip'
@@ -59,9 +62,13 @@ jobs:
       run: |
         python -m pip install --upgrade pip
         pip install -r requirements.txt
-        pip install .[test,dev,bayesian]
+        pip install .[test,dev]
+
+    - name: List installed versions
+      run: |
+        pip list
 
     - name: Run tests with pytest
       run: |
         # run tests with pytest, reporting coverage and timings
-        pytest -m "not slow" -rs -vvv  --durations=0 --cov=./modnet/
+        pytest -m "not slow" -m "not deprecated" -rs -vvv  --durations=0 --cov=./modnet/

modnet/models/ensemble.py

@@ -438,7 +438,7 @@ def fit_preset(
             for i in range(n_splits):
                 best_5_idx = np.argsort(val_losses[:, i])[:5]
                 for idx in best_5_idx:
-                    final_models += models[idx][i].model
+                    final_models.extend(models[idx][i].models)
             self.__init__(modnet_models=final_models)
 
         os.environ["TF_CPP_MIN_LOG_LEVEL"] = "0"  # reset

modnet/models/vanilla.py

@@ -1343,6 +1343,9 @@ def fit(
         }
 
         fit_params.update(fit_params_kw)
+        if "learning_rate" in fit_params:
+            fit_params.pop("learning_rate")
+            warnings.warn("learning_rate is deprecated, use lr instead.")
 
         if loss is None:
             loss = "mse"

modnet/tests/test_model.py

@@ -142,6 +142,7 @@ def test_model_integration(subset_moddata, tf_session):
     assert not np.isnan(model.evaluate(data))
 
 
+@pytest.mark.deprecated
 def test_train_small_bayesian_single_target(subset_moddata, tf_session):
     """Tests the single target training."""
     from modnet.models import BayesianMODNetModel
@@ -165,6 +166,7 @@ def test_train_small_bayesian_single_target(subset_moddata, tf_session):
     assert not np.isnan(model.evaluate(data))
 
 
+@pytest.mark.deprecated
 def test_train_small_bayesian_single_target_classif(subset_moddata, tf_session):
     """Tests the single target training."""
     from modnet.models import BayesianMODNetModel
@@ -196,6 +198,7 @@ def is_metal(egap):
     assert not np.isnan(model.evaluate(data))
 
 
+@pytest.mark.deprecated
 def test_train_small_bayesian_multi_target(subset_moddata, tf_session):
     """Tests the multi-target training."""
     from modnet.models import BayesianMODNetModel

pytest.ini

@@ -1,3 +1,4 @@
 [pytest]
 markers =
     slow: marks tests as slow (deselect with '-m "not slow"')
+    deprecated: mark tests as deprecated (deselect with -m "not deprecated")

requirements.txt

@@ -1,7 +1,6 @@
-tensorflow==2.11.0
-pandas==1.5.2
-scikit-learn==1.3.2
+tensorflow==2.15.1
+pandas==2.2.3
+scikit-learn==1.5.0
 matminer==0.9.2
 numpy>=1.25
-pymatgen==2024.3.1
-scikit-learn==1.3.2
+pymatgen==2024.5.31

setup.py

@@ -32,17 +32,17 @@
     include_package_data=True,
     packages=setuptools.find_packages(),
     install_requires=[
-        "pandas~=1.5",
-        "tensorflow~=2.10,<2.12",
-        "pymatgen>=2023",
-        "matminer~=0.9",
-        "numpy>=1.24",
-        "scikit-learn~=1.3",
+        "pandas <= 1.5, < 3",
+        "tensorflow ~= 2.10, < 2.16",
+        "pymatgen >= 2023",
+        "matminer ~= 0.9",
+        "numpy >= 1.24",
+        "scikit-learn ~= 1.3",
     ],
     tests_require=tests_require,
     test_suite="modnet.tests",
     extras_require={
-        "bayesian": ["tensorflow-probability==0.18"],
+        "bayesian": ["tensorflow-probability==0.18", "tensorflow == 2.11.*"],
         "test": tests_require,
         "dev": dev_require,
     },