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[ENH] SimpleTreeLearner: Release GIL & thread safety #2398

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merged 1 commit into from
Jun 16, 2017
Merged

[ENH] SimpleTreeLearner: Release GIL & thread safety #2398

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46 changes: 38 additions & 8 deletions Orange/classification/_simple_tree.c
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Original file line number Diff line number Diff line change
Expand Up @@ -47,16 +47,45 @@ enum { DiscreteNode, ContinuousNode, PredictorNode };
enum { Classification, Regression };
enum { IntVar, FloatVar };

int compar_attr;
/*
* Common interface for qsort_r
* (there are 3 (possibly more) different qsort_r call styles in the wild).
*
*/

#if (defined __APPLE__ || defined __DARWIN__ || defined __BSD__)
#define QSORT_R_STYLE_BSD
#define QSORT_R_FUNC(base, nel, size, thunk, compar) \
qsort_r(base, nel, size, thunk, compar)
#elif (defined __GLIBC__ || defined __GNU__ || defined __linux__)
#define QSORT_R_STYLE_GNU
#define QSORT_R_FUNC(base, nel, size, thunk, compar) \
qsort_r(base, nel, size, compar, thunk)
#elif (defined _MSC_VER)
#define QSORT_R_STYLE_MSVC
#define QSORT_R_FUNC(base, nel, size, thunk, compar) \
qsort_s(base, nel, size, compar, thunk)
#endif

/* This function uses the global variable compar_attr.

#if (defined QSORT_R_STYLE_BSD || defined QSORT_R_STYLE_MSVC)
#define SORT_CMP_FUNC(name) \
int name(void *context, const void *ptr1, const void *ptr2)
#elif (defined QSORT_R_STYLE_GNU)
#define SORT_CMP_FUNC(name) \
int name(const void *ptr1, const void *ptr2, void *context)
#else
#error "Unkown qsort_r comparator call convention"
#endif


/*
* Examples with unknowns are larger so that, when sorted, they appear at the bottom.
*/
int
compar_examples(const void *ptr1, const void *ptr2)
SORT_CMP_FUNC(compar_examples)
{
double x1, x2;

int compar_attr = *(int *)context;
x1 = ((struct Example *)ptr1)->x[compar_attr];
x2 = ((struct Example *)ptr2)->x[compar_attr];
if (isnan(x1))
Expand Down Expand Up @@ -102,7 +131,7 @@ gain_ratio_c(struct Example *examples, int size, int attr, float cls_entropy, st
struct Example *ex, *ex_end, *ex_next;
int i, cls, cls_vals, min_instances, size_known;
float score, *dist_lt, *dist_ge, *attr_dist, best_score, size_weight;

int compar_attr;
cls_vals = args->cls_vals;

/* min_instances should be at least 1, otherwise there is no point in splitting */
Expand All @@ -115,7 +144,7 @@ gain_ratio_c(struct Example *examples, int size, int attr, float cls_entropy, st

/* sort */
compar_attr = attr;
qsort(examples, size, sizeof(struct Example), compar_examples);
QSORT_R_FUNC(examples, size, sizeof(struct Example), (void*) &compar_attr, compar_examples);

/* compute gain ratio for every split */
size_known = size;
Expand Down Expand Up @@ -236,6 +265,7 @@ mse_c(struct Example *examples, int size, int attr, float cls_mse, struct Args *
struct Example *ex, *ex_end, *ex_next;
int i, min_instances, size_known;
float size_attr_known, size_weight, cls_val, best_score, size_attr_cls_known, score;
int compar_attr;

struct Variance {
double n, sum, sum2;
Expand All @@ -246,7 +276,7 @@ mse_c(struct Example *examples, int size, int attr, float cls_mse, struct Args *

/* sort */
compar_attr = attr;
qsort(examples, size, sizeof(struct Example), compar_examples);
QSORT_R_FUNC(examples, size, sizeof(struct Example), (void *)&compar_attr, compar_examples);

/* compute mse for every split */
size_known = size;
Expand Down
2 changes: 1 addition & 1 deletion Orange/classification/simple_tree.py
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Expand Up @@ -6,7 +6,7 @@
__all__ = ['SimpleTreeLearner']

from . import _simple_tree
_tree = ct.pydll.LoadLibrary(_simple_tree.__file__)
_tree = ct.cdll.LoadLibrary(_simple_tree.__file__)

DiscreteNode = 0
ContinuousNode = 1
Expand Down