ogrisel

# %%
import numpy as np
from numpy.random import sample
from numpy.testing import assert_allclose
from sklearn.preprocessing import scale
from sklearn.datasets import make_regression
from sklearn.model_selection import train_test_split
from scipy.optimize import fmin_l_bfgs_b, check_grad

ogrisel

import numpy as np
from sklearn.utils.extmath import _incremental_mean_and_var
from sklearn.utils.sparsefuncs import _incr_mean_var_axis0
from sklearn.utils.sparsefuncs import _csc_mean_var_axis0
from sklearn.utils.sparsefuncs import _csr_mean_var_axis0
from scipy.sparse import csr_matrix
from scipy.sparse import csc_matrix

for dtype in [np.float64, np.float32]:
    print(f"## dtype={dtype.__name__}")

ogrisel

# %%
import numpy as np
from numpy.testing import assert_allclose
from sklearn.linear_model import Ridge
from sklearn.datasets import make_regression
from sklearn.model_selection import train_test_split
from scipy.optimize import fmin_l_bfgs_b, check_grad

np.random.seed(0)

ogrisel

# %%
from time import perf_counter
from sklearn.datasets import make_blobs
from sklearn.cluster import KMeans
from sklearn.cluster import MiniBatchKMeans
from sklearn.cluster import kmeans_plusplus
from sklearn.model_selection import train_test_split
from scipy.spatial.distance import cdist
from subprocess import run
from pprint import pprint

ogrisel

NumPy version 0.3.0+24607.gd075ba2ce
NumPy relaxed strides checking option: True
NumPy CPU features: NEON NEON_FP16 NEON_VFPV4 ASIMD ASIMDHP? ASIMDDP?
........................................................................ [  0%]
......................................................x................. [  1%]
........................................................................ [  1%]
................................................x....................... [  2%]
........................................................................ [  2%]
........................................................................ [  3%]
........................................................................ [  3%]

ogrisel

import numpy as np
try:
    import tensorflow as tf
except ImportError:
    tf = None
from time import perf_counter


def timeit(func, *args, **kwargs):
    durations = []

ogrisel

NumPy version 1.20.0
NumPy relaxed strides checking option: True
NumPy CPU features: NEON NEON_FP16 NEON_VFPV4 ASIMD ASIMDHP? ASIMDDP?
........................................................................ [  0%]
......................................................x................. [  1%]
........................................................................ [  1%]
.................................x...................................... [  2%]
........................................................................ [  2%]
..........................sssssssss..................................... [  3%]
........................................................................ [  4%]

ogrisel

#include <stdio.h>
#include <stdlib.h>
#include <math.h>
#include <float.h>
#include "cblas.h"


int main() {
    int found_error;
    int k;

ogrisel

import os
os.environ["OMP_NUM_THREADS"] = "1"  # avoid oversubscription

import pandas as pd
from distributed.client import performance_report
from time import perf_counter
from joblib import Memory, parallel_backend
from distributed import Client, LocalCluster
from sklearn.datasets import make_regression
from sklearn.experimental import enable_hist_gradient_boosting  # noqa

ogrisel