Merge pull request #480 from mdekstrand/tweak/numpy-update

Allow NumPy 2.0
lenskit · Aug 25, 2024 · d2a5cee · d2a5cee
2 parents 2f5b8d1 + 6f63af5
commit d2a5cee
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Showing 4 changed files with 21 additions and 21 deletions.
diff --git a/lenskit-funksvd/lenskit/funksvd.py b/lenskit-funksvd/lenskit/funksvd.py
@@ -26,12 +26,12 @@
 
 @jitclass(
     [
-        ("user_features", n.double[:, :]),
-        ("item_features", n.double[:, :]),
+        ("user_features", n.float64[:, :]),
+        ("item_features", n.float64[:, :]),
         ("feature_count", n.int32),
         ("user_count", n.int32),
         ("item_count", n.int32),
-        ("initial_value", n.double),
+        ("initial_value", n.float64),
     ]
 )  # type: ignore
 class Model:
@@ -48,8 +48,8 @@ def __init__(self, umat, imat):
 
 
 def _fresh_model(nfeatures, nusers, nitems, init=0.1):
-    umat = np.full([nusers, nfeatures], init, dtype=np.float_)
-    imat = np.full([nitems, nfeatures], init, dtype=np.float_)
+    umat = np.full([nusers, nfeatures], init, dtype=np.float64)
+    imat = np.full([nitems, nfeatures], init, dtype=np.float64)
     model = Model(umat, imat)
     model.initial_value = init
     assert model.feature_count == nfeatures
@@ -61,10 +61,10 @@ def _fresh_model(nfeatures, nusers, nitems, init=0.1):
 @jitclass(
     [
         ("iter_count", n.int32),
-        ("lrate", n.double),
-        ("reg_term", n.double),
-        ("rmin", n.double),
-        ("rmax", n.double),
+        ("lrate", n.float64),
+        ("reg_term", n.float64),
+        ("rmin", n.float64),
+        ("rmax", n.float64),
     ]
 )  # type: ignore
 class _Params:
@@ -86,7 +86,7 @@ def make_params(niters, lrate, reg, range):
     return _Params(niters, lrate, reg, rmin, rmax)
 
 
-@jitclass([("est", n.double[:]), ("feature", n.int32), ("trail", n.double)])  # type: ignore
+@jitclass([("est", n.float64[:]), ("feature", n.int32), ("trail", n.float64)])  # type: ignore
 class _FeatContext:
     def __init__(self, est, feature, trail):
         self.est = est
@@ -98,8 +98,8 @@ def __init__(self, est, feature, trail):
     [
         ("users", n.int32[:]),
         ("items", n.int32[:]),
-        ("ratings", n.double[:]),
-        ("bias", n.double[:]),
+        ("ratings", n.float64[:]),
+        ("bias", n.float64[:]),
         ("n_samples", n.uint64),
     ]
 )  # type: ignore
@@ -277,11 +277,11 @@ def fit(self, data: Dataset, **kwargs):
 
         users = np.array(rate_df["user_num"])
         items = np.array(rate_df["item_num"])
-        ratings = np.array(rate_df["rating"], dtype=np.float_)
+        ratings = np.array(rate_df["rating"], dtype=np.float64)
 
         _logger.debug("[%s] computing initial estimates", timer)
         if self.bias:
-            initial = np.full(len(users), self.bias.mean_, dtype=np.float_)
+            initial = np.full(len(users), self.bias.mean_, dtype=np.float64)
             if self.bias.item_offsets_ is not None:
                 initial += self.bias.item_offsets_.values[items]
             if self.bias.user_offsets_ is not None:

diff --git a/lenskit-implicit/tests/test_implicit.py b/lenskit-implicit/tests/test_implicit.py
@@ -59,7 +59,7 @@ def test_implicit_als_batch_accuracy(ml_100k, n_jobs):
 
     def eval(train, test):
         _log.info("running training")
-        train["rating"] = train.rating.astype(np.float_)
+        train["rating"] = train.rating.astype(np.float32)
         algo = util.clone(algo_t)
         algo.fit(from_interactions_df(train))
         users = test.user.unique()

diff --git a/lenskit/pyproject.toml b/lenskit/pyproject.toml
@@ -21,14 +21,14 @@ license = { file = "LICENSE.md" }
 dynamic = ["version"]
 dependencies = [
   "pandas >=1.5, <3",
-  "numpy >= 1.23,<2",
+  "numpy >= 1.23",
   "scipy >= 1.9.0",
-  "torch ~=2.1",            # conda: pytorch>=2.1,<3
+  "torch ~=2.1",                                           # conda: pytorch>=2.1,<3
   "threadpoolctl >=3.0",
   "pydantic >=2.8,<3",
-  "seedbank >=0.2.0a2",     # conda: @pip
-  "progress-api >=0.1.0a9", # conda: @pip
-  "manylog >=0.1.0a5",      # conda: @pip
+  "seedbank >=0.2.0a2",                                    # conda: @pip
+  "progress-api >=0.1.0a9",                                # conda: @pip
+  "manylog@git+https://github.com/mdekstrand/manylog.git", # conda: @pip
 ]
 
 [project.optional-dependencies]

diff --git a/lenskit/tests/algorithms/test_als_implicit.py b/lenskit/tests/algorithms/test_als_implicit.py
@@ -304,7 +304,7 @@ def test_als_implicit_batch_accuracy(ml_100k):
     ratings = load_movielens_df(lktu.ml_100k_zip)
 
     def eval(train, test):
-        train = train.astype({"rating": np.float_})
+        train = train.astype({"rating": np.float32})
         _log.info("training implicit MF")
         ials_algo = als.ImplicitMF(25, epochs=20)
         ials_algo = Recommender.adapt(ials_algo)