SIENTIAPDE-1255: Integrate sientia-mlops-library into model-manager, adding model serving, reporting, and updated model definitions.

model_manager/sientia/utils.py

@@ -0,0 +1,36 @@
+from typing import Any
+
+from numpy.typing import ArrayLike
+from sklearn.model_selection import train_test_split
+
+
+def split_train_test(
+    *data: Any,
+    test_size: float | None = None,
+    train_size: float | None = None,
+    random_state: int | None = None,
+    shuffle: bool = True,
+    stratify: ArrayLike | None = None,
+) -> tuple[Any, Any, Any, Any]:
+    """
+    Split arrays or matrices into random train and test subsets.
+
+    Args:
+        *data: data to be splitted.
+        test_size: size of test subset.
+        train_size: size of train subset.
+        random_state: Seed applied to the data before applying the split.
+        shuffle: Whether or not to shuffle the data before splitting.
+        stratify: If not None, data is split in a stratified fashion, using this as the class labels.
+    Returns:
+        X_train, X_test, y_train, y_test
+    """
+    X_train, X_test, y_train, y_test = train_test_split(
+        *data,
+        test_size=test_size,
+        train_size=train_size,
+        random_state=random_state,
+        shuffle=shuffle,
+        stratify=stratify,
+    )
+    return X_train, X_test, y_train, y_test