8000 [MRG+1] micro-optimize HashingVectorizer and FeatureHasher by kmike · Pull Request #7470 · scikit-learn/scikit-learn · GitHub
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[MRG+1] micro-optimize HashingVectorizer and FeatureHasher #7470

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Merged
merged 2 commits into from
Sep 30, 2016
Merged

[MRG+1] micro-optimize HashingVectorizer and FeatureHasher #7470

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4cb6fd4
micro-optimize HashingVectorizer and FeatureHasher
kmike Sep 22, 2016
9de996d
fix backwards compatibility for Cython < 0.20
kmike Sep 22, 2016
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8 changes: 3 additions & 5 deletions sklearn/feature_extraction/_hashing.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -8,8 +8,6 @@ from libc.stdlib cimport abs
cimport numpy as np
import numpy as np

from ..externals.six import string_types

from sklearn.utils.murmurhash cimport murmurhash3_bytes_s32

np.import_array()
Expand Down Expand Up @@ -45,7 +43,7 @@ def transform(raw_X, Py_ssize_t n_features, dtype):

for x in raw_X:
for f, v in x:
if isinstance(v, string_types):
if isinstance(v, (str, unicode)):
f = "%s%s%s" % (f, '=', v)
value = 1
else:
Expand All @@ -55,13 +53,13 @@ def transform(raw_X, Py_ssize_t n_features, dtype):
continue

if isinstance(f, unicode):
f = f.encode("utf-8")
f = (<unicode>f).encode("utf-8")
# Need explicit type check because Murmurhash does not propagate
# all exceptions. Add "except *" there?
elif not isinstance(f, bytes):
raise TypeError("feature names must be strings")

h = murmurhash3_bytes_s32(f, 0)
h = murmurhash3_bytes_s32(<bytes>f, 0)

array.resize_smart(indices, len(indices) + 1)
indices[len(indices) - 1] = abs(h) % n_features
Expand Down
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