ENH speedup coordinate descent by avoiding calls to axpy in innermost loop #31956
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BenchmarkingBenchmarking code from #17021. Time Ratios Code file mtl_bench.py """
Benchmark of MultiTaskLasso
"""
import gc
from itertools import product
from time import time
import numpy as np
import pandas as pd
from sklearn.datasets import make_regression
from sklearn.linear_model import MultiTaskLasso
def compute_bench(alpha, n_samples, n_features, n_tasks):
results = []
n_bench = len(n_samples) * len(n_features) * len(n_tasks)
for it, (ns, nf, nt) in enumerate(product(n_samples, n_features, n_tasks)):
print('==================')
print('Iteration %s of %s' % (it, n_bench))
print('==================')
n_informative = nf // 10
X, Y, coef_ = make_regression(n_samples=ns, n_features=nf,
n_informative=n_informative,
n_targets=nt,
noise=0.1, coef=True)
X /= np.sqrt(np.sum(X ** 2, axis=0)) # Normalize data
gc.collect()
clf = MultiTaskLasso(alpha=alpha, fit_intercept=False)
tstart = time()
clf.fit(X, Y)
results.append(
dict(n_samples=ns, n_features=nf, n_tasks=nt, time=time() - tstart)
)
return pd.DataFrame(results)
def compare_results():
results_new = pd.read_csv('mlt_new.csv').set_index(['n_samples', 'n_features', 'n_tasks'])
results_old = pd.read_csv('mlt_old.csv').set_index(['n_samples', 'n_features', 'n_tasks'])
results_ratio = (results_old / results_new)
results_ratio.columns = ['time (old) / time (new)']
print(results_new)
print(results_old)
print(results_ratio)
if __name__ == '__main__':
import matplotlib.pyplot as plt
alpha = 0.01 # regularization parameter
list_n_features = [300, 1000, 4000]
list_n_samples = [100, 500]
list_n_tasks = [2, 10, 20, 50]
results = compute_bench(alpha, list_n_samples,
list_n_features, list_n_tasks)
# results.to_csv('mlt_old.csv', index=False)
results.to_csv('mlt_new.csv', index=False)
compare_results() |
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Reference Issues/PRs
Similar to #31880.
Continues and fixes #15931.
What does this implement/fix? Explain your changes.
This PR avoids calls to
_axpyin the innermost loop of all coordinate descent solvers (Lasso and Enet), exceptenet_coordinate_descent_gramwhich was done in #31880.Any other comments?
Ironically, this improvement also reduces code size 😄
For reviewers: better merge #31957 first.