Fix(requirements): use scikeras to bring back keras wrappers

* Add `scikeras~=0.13.0` dependency
* Use `scikeras.wrappers.KerasRegressor` instead of removed `tensorflow.keras.wrappers.scikit_learn import KerasRegressor`

gordo/machine/model/models.py

@@ -14,7 +14,7 @@
 import tensorflow.keras.models
 from tensorflow.keras.models import load_model, save_model
 from tensorflow.keras.preprocessing.sequence import pad_sequences, TimeseriesGenerator
-from tensorflow.keras.wrappers.scikit_learn import KerasRegressor as BaseWrapper
+from scikeras.wrappers import KerasRegressor as BaseWrapper
 from tensorflow.keras.callbacks import History
 import numpy as np
 import pandas as pd

requirements/full_requirements.txt

@@ -191,7 +191,9 @@ joblib==1.4.2
 jsonpickle==3.2.2
     # via azureml-core
 keras==3.3.3
-    # via tensorflow
+    # via
+    #   scikeras
+    #   tensorflow
 kiwisolver==1.4.5
     # via matplotlib
 knack==0.11.0
@@ -382,10 +384,13 @@ requests-oauthlib==2.0.0
     # via msrest
 rich==13.7.1
     # via keras
+scikeras==0.13.0
+    # via -r requirements.in
 scikit-learn==1.5.0
     # via
     #   gordo-core
     #   mlflow
+    #   scikeras
 scipy==1.13.1
     # via
     #   catboost

requirements/requirements.in

@@ -4,6 +4,7 @@ h5py~=3.1
 jinja2~=3.1
 python-dateutil~=2.8
 tensorflow~=2.16.0
+scikeras~=0.13.0
 Flask>=2.2.5,<3.0.0
 simplejson~=3.17
 catboost~=1.2.5

tests/gordo/machine/model/test_model.py

@@ -11,8 +11,7 @@
 from sklearn.exceptions import NotFittedError
 from sklearn.pipeline import Pipeline
 from sklearn.model_selection import cross_val_score, TimeSeriesSplit
-
-from tensorflow.keras.wrappers.scikit_learn import KerasRegressor as BaseWrapper
+from scikeras.wrappers import KerasRegressor as BaseWrapper
 from tensorflow.keras.callbacks import EarlyStopping
 
 from tests.utils import get_model