thomasjpfan

https://scikit-learn.org/dev/auto_examples/tree/plot_iris_dtc.html

https://scikit-learn.org/dev/auto_examples/ensemble/plot_adaboost_twoclass.html

https://scikit-learn.org/dev/auto_examples/calibration/plot_compare_calibration.html

https://scikit-learn.org/dev/auto_examples/linear_model/plot_logistic_multinomial.html

https://scikit-learn.org/dev/auto_examples/linear_model/plot_sgd_iris.html

thomasjpfan

thomasjpfan

diff --git a/sklearn/utils/_weight_vector.pxd.tp b/sklearn/utils/_weight_vector.pxd.tp
index 9d1779373c..f5e3e4af5a 100644
--- a/sklearn/utils/_weight_vector.pxd.tp
+++ b/sklearn/utils/_weight_vector.pxd.tp
@@ -27,11 +27,12 @@ cdef class WeightVector{{name_suffix}}(object):
     cdef readonly {{c_type}}[::1] aw
     cdef {{c_type}} *w_data_ptr
     cdef {{c_type}} *aw_data_ptr
-    cdef {{c_type}} wscale
-    cdef {{c_type}} average_a

thomasjpfan

diff --git a/sklearn/decomposition/_dict_learning.py b/sklearn/decomposition/_dict_learning.py
index b0c252fc31..e99465ada3 100644
--- a/sklearn/decomposition/_dict_learning.py
+++ b/sklearn/decomposition/_dict_learning.py
@@ -174,6 +174,8 @@ def _sparse_encode(
         )
 
         if init is not None:
+            if not init.flags["WRITEABLE"]:
+                init = np.array(init)

thomasjpfan

#0  __GI_raise (sig=sig@entry=6) at ../sysdeps/unix/sysv/linux/raise.c:50
#1  0x00007ffff7c66859 in __GI_abort () at abort.c:79
#2  0x00007ffff7cd126e in __libc_message (action=action@entry=do_abort, fmt=fmt@entry=0x7ffff7dfb298 "%s\n")
    at ../sysdeps/posix/libc_fatal.c:155
#3  0x00007ffff7cd92fc in malloc_printerr (str=str@entry=0x7ffff7dfd600 "free(): invalid next size (fast)")
    at malloc.c:5347
#4  0x00007ffff7cdabac in _int_free (av=0x7ffff7e30b80 <main_arena>, p=0x555559ff7e50, have_lock=0)
    at malloc.c:4249
#5  0x00007ffff5e1d2e1 in PyDataMem_UserFREE ()
   from /home/thomasfan/Desktop/cpython/.venv/lib/python3.11/site-packages/numpy/core/_multiarray_umath.cpython-311-x86_64-linux-gnu.so

thomasjpfan

        nanmin = self.get_computation_routine("nanmin")
        nanmax = self.get_computation_routine("nanmax")

        # self.get_computation_routine("nanmin_max")
        # cupy.array_api.min
        data_min = nanmin(X, axis=0)
        data_max = nanmax(X, axis=0)

        if first_pass:

thomasjpfan

"""Instructions
1. Build this PR and run:

```bash
python bench_missing.py bench ~/bench_results pr
```

2. On main run:

```bash

thomasjpfan

from functools import partial
import argparse
from time import perf_counter
from statistics import mean, stdev
from itertools import product
import csv

from sklearn.tree import DecisionTreeRegressor, DecisionTreeClassifier
from sklearn.datasets import make_classification, make_regression, make_low_rank_matrix
import numpy as np

thomasjpfan

thomasjpfan