enh: Add device selection mechanism (#60)

* enh: Add device selection mechanism

* Fix bug in util

* remove prefix in patch

model2vec/distill/distillation.py

@@ -12,6 +12,7 @@
     create_output_embeddings_from_model_name_and_tokens,
 )
 from model2vec.distill.tokenizer import add_tokens, preprocess_vocabulary, remove_tokens
+from model2vec.distill.utils import select_optimal_device
 from model2vec.model import StaticModel
 
 logger = logging.getLogger(__name__)
@@ -24,7 +25,7 @@ def distill_from_model(
     model: PreTrainedModel,
     tokenizer: PreTrainedTokenizerFast,
     vocabulary: list[str] | None = None,
-    device: str = "cpu",
+    device: str | None = None,
     pca_dims: PCADimType = 256,
     apply_zipf: bool = True,
     use_subword: bool = True,
@@ -52,7 +53,7 @@ def distill_from_model(
     :return: A StaticModel
 
     """
-    """"""
+    device = select_optimal_device(device)
     if not use_subword and vocabulary is None:
         raise ValueError(
             "You must pass a vocabulary if you don't use subword tokens. Either pass a vocabulary, or set use_subword to True."
@@ -137,7 +138,7 @@ def distill_from_model(
 def distill(
     model_name: str,
     vocabulary: list[str] | None = None,
-    device: str = "cpu",
+    device: str | None = None,
     pca_dims: PCADimType = 256,
     apply_zipf: bool = True,
     use_subword: bool = True,

model2vec/distill/utils.py

@@ -0,0 +1,26 @@
+from logging import getLogger
+
+import torch
+
+logger = getLogger(__name__)
+
+
+def select_optimal_device(device: str | None) -> str:
+    """
+    Guess what your optimal device should be based on backend availability.
+
+    If you pass a device, we just pass it through.
+
+    :param device: The device to use. If this is not None you get back what you passed.
+    :return: The selected device.
+    """
+    if device is None:
+        if torch.cuda.is_available():
+            device = "cuda"
+        elif torch.backends.mps.is_available():
+            device = "mps"
+        else:
+            device = "cpu"
+        logger.info(f"Automatically selected device: {device}")
+
+    return device

tests/test_utils.py

@@ -1,6 +1,10 @@
 from pathlib import Path
 from tempfile import NamedTemporaryFile
+from unittest.mock import patch
 
+import pytest
+
+from model2vec.distill.utils import select_optimal_device
 from model2vec.utils import _get_metadata_from_readme
 
 
@@ -23,3 +27,26 @@ def test__get_metadata_from_readme_mocked_file_keys() -> None:
         f.write(b"")
         f.flush()
         assert set(_get_metadata_from_readme(Path(f.name))) == set()
+
+
+@pytest.mark.parametrize(
+    "device, expected, cuda, mps",
+    [
+        ("cpu", "cpu", True, True),
+        ("cpu", "cpu", True, False),
+        ("cpu", "cpu", False, True),
+        ("cpu", "cpu", False, False),
+        ("clown", "clown", False, False),
+        (None, "cuda", True, True),
+        (None, "cuda", True, False),
+        (None, "mps", False, True),
+        (None, "cpu", False, False),
+    ],
+)
+def test_select_optimal_device(device: str | None, expected: str, cuda: bool, mps: bool) -> None:
+    """Test whether the optimal device is selected."""
+    with (
+        patch("torch.cuda.is_available", return_value=cuda),
+        patch("torch.backends.mps.is_available", return_value=mps),
+    ):
+        assert select_optimal_device(device) == expected