Fix lint and test

pyproject.toml

@@ -84,7 +84,7 @@ pytorch-lightning = {version = ">=1.6.0, <3.0.0", optional = true}
 ipywidgets = {version = ">=7.7,<8.2", optional = true}
 plotly = {version="^5.22.0", optional = true}
 nbformat = {version = ">=4.2.0", optional = true}
-cupy-cuda12x = {version = "^13.3.0", extras = ["cupy"], optional = true}
+cupy-cuda12x = {version = "^13.3.0", python = "<3.13", extras = ["cupy"], optional = true}
 
 
 [tool.poetry.extras]

rectools/models/pure_svd.py

@@ -91,9 +91,13 @@ def __init__(
         self.tol = tol
         self.maxiter = maxiter
         self.random_state = random_state
-        if use_gpu and (not HAS_CUDA or cupy_svds is None):  # pragma: no cover
-            warnings.warn("Forced to use CPU. CUDA is not available.")
-            use_gpu = False
+        if use_gpu:  # pragma: no cover
+            if not HAS_CUDA:
+                warnings.warn("Forced to use CPU. CUDA is not available.")
+                use_gpu = False
+            if cp is None:
+                warnings.warn("Forced to use CPU. CuPy is not available.")
+                use_gpu = False
 
         self.use_gpu = use_gpu
 

tests/models/test_pure_svd.py

@@ -17,6 +17,8 @@
 import numpy as np
 import pandas as pd
 import pytest
+from implicit.gpu import HAS_CUDA
+from pytest_mock import MockerFixture
 
 from rectools import Columns
 from rectools.dataset import Dataset
@@ -33,7 +35,7 @@
 )
 
 try:
-    import cupy as cp
+    import cupy as cp  # pylint: disable=import-error, unused-import
 except ImportError:  # pragma: no cover
     cp = None
 
@@ -45,7 +47,7 @@ def dataset(self) -> Dataset:
         return DATASET
 
     @pytest.mark.parametrize(
-        "filter_viewed,expected,use_gpu",
+        "filter_viewed,expected",
         (
             (
                 True,
@@ -56,7 +58,6 @@ def dataset(self) -> Dataset:
                         Columns.Rank: [1, 2, 1, 2],
                     }
                 ),
-                False,
             ),
             (
                 False,
@@ -67,8 +68,33 @@ def dataset(self) -> Dataset:
                         Columns.Rank: [1, 2, 1, 2],
                     }
                 ),
-                False,
             ),
+        ),
+    )
+    def test_basic(
+        self,
+        dataset: Dataset,
+        filter_viewed: bool,
+        expected: pd.DataFrame,
+    ) -> None:
+        model = PureSVDModel(factors=2, use_gpu=False).fit(dataset)
+        actual = model.recommend(
+            users=np.array([10, 20]),
+            dataset=dataset,
+            k=2,
+            filter_viewed=filter_viewed,
+        )
+        pd.testing.assert_frame_equal(actual.drop(columns=Columns.Score), expected)
+        pd.testing.assert_frame_equal(
+            actual.sort_values([Columns.User, Columns.Score], ascending=[True, False]).reset_index(drop=True),
+            actual,
+        )
+
+    # SciPy's svds and cupy's svds results can be different and use_gpu fallback causes errors
+    @pytest.mark.skipif(HAS_CUDA is False, reason="CUDA is not available")
+    @pytest.mark.parametrize(
+        "filter_viewed,expected",
+        (
             (
                 True,
                 pd.DataFrame(
@@ -78,7 +104,6 @@ def dataset(self) -> Dataset:
                         Columns.Rank: [1, 2, 1, 2],
                     }
                 ),
-                True,
             ),
             (
                 False,
@@ -89,18 +114,16 @@ def dataset(self) -> Dataset:
                         Columns.Rank: [1, 2, 1, 2],
                     }
                 ),
-                True,
             ),
         ),
     )
-    def test_basic(
+    def test_basic_gpu(
         self,
         dataset: Dataset,
         filter_viewed: bool,
         expected: pd.DataFrame,
-        use_gpu: bool,
     ) -> None:
-        model = PureSVDModel(factors=2, use_gpu=use_gpu).fit(dataset)
+        model = PureSVDModel(factors=2, use_gpu=True).fit(dataset)
         actual = model.recommend(
             users=np.array([10, 20]),
             dataset=dataset,
@@ -297,12 +320,16 @@ def test_dumps_loads(self, dataset: Dataset) -> None:
 
 class TestPureSVDModelConfiguration:
 
-    def test_from_config(self) -> None:
+    @pytest.mark.parametrize("use_gpu", (False, True))
+    def test_from_config(self, mocker: MockerFixture, use_gpu: bool) -> None:
+        mocker.patch("rectools.models.pure_svd.HAS_CUDA", return_value=True)
+        mocker.patch("rectools.models.pure_svd.cp", return_value=True)
         config = {
             "factors": 100,
             "tol": 0,
             "maxiter": 100,
             "random_state": 32,
+            "use_gpu": use_gpu,
             "verbose": 0,
         }
         model = PureSVDModel.from_config(config)
@@ -315,10 +342,14 @@ def test_from_config(self) -> None:
     @pytest.mark.parametrize("random_state", (None, 42))
     @pytest.mark.parametrize("simple_types", (False, True))
     @pytest.mark.parametrize("use_gpu", (False, True))
-    def test_get_config(self, random_state: tp.Optional[int], simple_types: bool, use_gpu: bool) -> None:
+    def test_get_config(
+        self, mocker: MockerFixture, random_state: tp.Optional[int], simple_types: bool, use_gpu: bool
+    ) -> None:
+        mocker.patch("rectools.models.pure_svd.HAS_CUDA", return_value=True)
+        mocker.patch("rectools.models.pure_svd.cp", return_value=True)
         model = PureSVDModel(
             factors=100,
-            tol=1,
+            tol=1.0,
             maxiter=100,
             random_state=random_state,
             use_gpu=use_gpu,
@@ -328,7 +359,7 @@ def test_get_config(self, random_state: tp.Optional[int], simple_types: bool, us
         expected = {
             "cls": "PureSVDModel" if simple_types else PureSVDModel,
             "factors": 100,
-            "tol": 1,
+            "tol": 1.0,
             "maxiter": 100,
             "random_state": random_state,
             "use_gpu": use_gpu,