Merge branch 'main' into feature/interactions_to_raw

rectools/dataset/identifiers.py

@@ -15,6 +15,7 @@
 """Mapping between external and internal ids."""
 
 import typing as tp
+import warnings
 
 import attr
 import numpy as np
@@ -80,7 +81,11 @@ def from_dict(cls, mapping: tp.Dict[ExternalId, InternalId]) -> "IdMap":
         order = np.argsort(internal_ids)
         internal_ids_sorted = internal_ids[order]
 
-        internals_incorrect = internal_ids_sorted != np.arange(internal_ids_sorted.size)
+        with warnings.catch_warnings():
+            # When comparing numeric vs. non-numeric array returns scalar, will change in the future
+            warnings.simplefilter("ignore", FutureWarning)
+            internals_incorrect = internal_ids_sorted != np.arange(internal_ids_sorted.size)
+
         if internals_incorrect is True or internals_incorrect.any():
             raise ValueError("Internal ids must be integers from 0 to n_objects-1")
 

rectools/models/dssm.py

@@ -19,13 +19,18 @@
 from __future__ import annotations
 
 import typing as tp
+import warnings
 from copy import deepcopy
 
 import numpy as np
 import torch
 import torch.nn.functional as F
-from pytorch_lightning import Callback, LightningModule, Trainer
-from pytorch_lightning.loggers import Logger
+
+with warnings.catch_warnings():
+    warnings.simplefilter("ignore", DeprecationWarning)
+    from pytorch_lightning import Callback, LightningModule, Trainer
+    from pytorch_lightning.loggers import Logger
+
 from torch import nn
 from torch.utils.data import DataLoader
 from torch.utils.data import Dataset as TorchDataset

setup.cfg

@@ -6,6 +6,8 @@ doctest_optionflags = DONT_ACCEPT_TRUE_FOR_1 NORMALIZE_WHITESPACE
 filterwarnings =
     ignore:LightFM was compiled without OpenMP support
     ignore:distutils Version classes are deprecated
+    ignore:Converting sparse features to dense array may cause MemoryError
+    ignore:OpenBLAS is configured to use
 
 [coverage:run]
 # the name of the data file to use for storing or reporting coverage.

tests/model_selection/test_cross_validate.py

@@ -1,6 +1,7 @@
 # pylint: disable=attribute-defined-outside-init
 
 import typing as tp
+import warnings
 
 import numpy as np
 import pandas as pd
@@ -251,12 +252,15 @@ def test_happy_path_with_features(self) -> None:
     def test_fail_with_cold_users(self) -> None:
         splitter = LastNSplitter(n=1, n_splits=2, filter_cold_users=False)
 
-        with pytest.raises(KeyError):
-            cross_validate(
-                dataset=self.dataset,
-                splitter=splitter,
-                metrics=self.metrics,
-                models=self.models,
-                k=2,
-                filter_viewed=False,
-            )
+        with warnings.catch_warnings(record=True) as w:
+            with pytest.raises(KeyError):
+                cross_validate(
+                    dataset=self.dataset,
+                    splitter=splitter,
+                    metrics=self.metrics,
+                    models=self.models,
+                    k=2,
+                    filter_viewed=False,
+                )
+            assert len(w) == 1
+            assert "Currently models do not support recommendations for cold users" in str(w[-1].message)