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a few tweaks to speed up data generation #4164

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merged 3 commits into from
Feb 21, 2019
+13 −8
Merged

a few tweaks to speed up data generation #4164

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603f098
a few tweaks to speed up data generation
rongou Feb 19, 2019
79fa114
del variable to save memory
rongou Feb 20, 2019
d45df56
switch to random numpy arrays
rongou Feb 20, 2019
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21 changes: 13 additions & 8 deletions tests/benchmark/benchmark_tree.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,8 +5,6 @@
import time

import numpy as np
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
import xgboost as xgb

RNG = np.random.RandomState(1994)
Expand All @@ -28,20 +26,27 @@ def run_benchmark(args):
print("Generating dataset: {} rows * {} columns".format(args.rows, args.columns))
print("{}/{} test/train split".format(args.test_size, 1.0 - args.test_size))
tmp = time.time()
X, y = make_classification(args.rows, n_features=args.columns, n_redundant=0,
n_informative=args.columns, n_repeated=0, random_state=7)
if args.sparsity < 1.0:
X = RNG.rand(args.rows, args.columns)
y = RNG.randint(0, 2, args.rows)
if 0.0 < args.sparsity < 1.0:
X = np.array([[np.nan if RNG.uniform(0, 1) < args.sparsity else x for x in x_row]
for x_row in X])

X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=args.test_size,
random_state=7)
train_rows = int(args.rows * (1.0 - args.test_size))
test_rows = int(args.rows * args.test_size)
X_train = X[:train_rows, :]
X_test = X[-test_rows:, :]
y_train = y[:train_rows]
y_test = y[-test_rows:]
print("Generate Time: %s seconds" % (str(time.time() - tmp)))
del X, y

tmp = time.time()
print("DMatrix Start")
dtrain = xgb.DMatrix(X_train, y_train)
dtrain = xgb.DMatrix(X_train, y_train, nthread=-1)
dtest = xgb.DMatrix(X_test, y_test, nthread=-1)
print("DMatrix Time: %s seconds" % (str(time.time() - tmp)))
del X_train, y_train, X_test, y_test

dtest.save_binary('dtest.dm')
dtrain.save_binary('dtrain.dm')
Expand Down