FIX Update randomized SVD benchmark (scikit-learn#23373)

mathijs02 · May 19, 2022 · e966f96 · e966f96
1 parent 0f1c0e7
commit e966f96
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Showing 2 changed files with 6 additions and 4 deletions.
diff --git a/benchmarks/bench_plot_randomized_svd.py b/benchmarks/bench_plot_randomized_svd.py
@@ -153,7 +153,7 @@ def get_data(dataset_name):
     elif dataset_name == "rcv1":
         X = fetch_rcv1().data
     elif dataset_name == "CIFAR":
-        if handle_missing_dataset(CIFAR_FOLDER) == "skip":
+        if handle_missing_dataset(CIFAR_FOLDER) == 0:
             return
         X1 = [unpickle("%sdata_batch_%d" % (CIFAR_FOLDER, i + 1)) for i in range(5)]
         X = np.vstack(X1)

diff --git a/sklearn/utils/extmath.py b/sklearn/utils/extmath.py
@@ -216,9 +216,6 @@ def randomized_range_finder(
 
     # Generating normal random vectors with shape: (A.shape[1], size)
     Q = random_state.normal(size=(A.shape[1], size))
-    if A.dtype.kind == "f":
-        # Ensure f32 is preserved as f32
-        Q = Q.astype(A.dtype, copy=False)
 
     # Deal with "auto" mode
     if power_iteration_normalizer == "auto":
@@ -243,6 +240,11 @@ def randomized_range_finder(
     # Sample the range of A using by linear projection of Q
     # Extract an orthonormal basis
     Q, _ = linalg.qr(safe_sparse_dot(A, Q), mode="economic")
+
+    if hasattr(A, "dtype") and A.dtype.kind == "f":
+        # Ensure f32 is preserved as f32
+        Q = Q.astype(A.dtype, copy=False)
+
     return Q