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|
Author: Michael R. Crusoe <crusoe@debian.org>
Description: Support pre-1.8 sklearn
Forwarded: not-needed
Please remove this patch when sklearn 1.6 lands in Debian
--- umap-learn.orig/umap/distances.py
+++ umap-learn/umap/distances.py
@@ -1285,7 +1285,7 @@
return metric(_X, _Y, *kwd_vals)
return pairwise_distances(
- X, Y, metric=_partial_metric, ensure_all_finite=ensure_all_finite
+ X, Y, metric=_partial_metric, force_all_finite=ensure_all_finite
)
else:
special_metric_func = named_distances[metric]
--- umap-learn.orig/umap/parametric_umap.py
+++ umap-learn/umap/parametric_umap.py
@@ -365,7 +365,7 @@
landmark_positions = check_array(
landmark_positions,
dtype=np.float32,
- ensure_all_finite="allow-nan",
+ force_all_finite="allow-nan",
)
# get dataset of edges
--- umap-learn.orig/umap/umap_.py
+++ umap-learn/umap/umap_.py
@@ -2366,7 +2366,7 @@
"""
if self.metric in ("bit_hamming", "bit_jaccard"):
X = check_array(
- X, dtype=np.uint8, order="C", ensure_all_finite=ensure_all_finite
+ X, dtype=np.uint8, order="C", force_all_finite=ensure_all_finite
)
else:
X = check_array(
@@ -2374,7 +2374,7 @@
dtype=np.float32,
accept_sparse="csr",
order="C",
- ensure_all_finite=ensure_all_finite,
+ force_all_finite=ensure_all_finite,
)
self._raw_data = X
@@ -2390,7 +2390,7 @@
self.init,
dtype=np.float32,
accept_sparse=False,
- ensure_all_finite=ensure_all_finite,
+ force_all_finite=ensure_all_finite,
)
else:
init = self.init
@@ -2700,7 +2700,7 @@
if self.target_metric == "string":
y_ = y[index]
else:
- y_ = check_array(y, ensure_2d=False, ensure_all_finite=ensure_all_finite)[
+ y_ = check_array(y, ensure_2d=False, force_all_finite=ensure_all_finite)[
index
]
if self.target_metric == "categorical":
@@ -2975,7 +2975,7 @@
# If we just have the original input then short circuit things
if self.metric in ("bit_hamming", "bit_jaccard"):
X = check_array(
- X, dtype=np.uint8, order="C", ensure_all_finite=ensure_all_finite
+ X, dtype=np.uint8, order="C", force_all_finite=ensure_all_finite
)
else:
X = check_array(
@@ -2983,7 +2983,7 @@
dtype=np.float32,
accept_sparse="csr",
order="C",
- ensure_all_finite=ensure_all_finite,
+ force_all_finite=ensure_all_finite,
)
x_hash = joblib.hash(X)
if x_hash == self._input_hash:
@@ -3357,7 +3357,7 @@
def update(self, X, ensure_all_finite=True):
if self.metric in ("bit_hamming", "bit_jaccard"):
X = check_array(
- X, dtype=np.uint8, order="C", ensure_all_finite=ensure_all_finite
+ X, dtype=np.uint8, order="C", force_all_finite=ensure_all_finite
)
else:
X = check_array(
@@ -3365,7 +3365,7 @@
dtype=np.float32,
accept_sparse="csr",
order="C",
- ensure_all_finite=ensure_all_finite,
+ force_all_finite=ensure_all_finite,
)
random_state = check_random_state(self.transform_seed)
rng_state = random_state.randint(INT32_MIN, INT32_MAX, 3).astype(np.int64)
|
