fixed reproducibility issue of DMR & GDMR

src/TopicModel/DMRModel.hpp

@@ -86,7 +86,7 @@ namespace tomoto
 			const size_t chStride = pool.getNumWorkers() * 8;
 			for (size_t ch = 0; ch < chStride; ++ch)
 			{
-				res.emplace_back(pool.enqueue([&](size_t threadId)
+				res.emplace_back(pool.enqueue([&, ch](size_t threadId)
 				{
 					auto& tmpK = localData[threadId].tmpK;
 					if (!tmpK.size()) tmpK.resize(this->K);

test/unit_test.py

@@ -135,6 +135,28 @@ def train0_without_optim(cls, inputFile, mdFields, f, kargs, ps):
     mdl.train(2000, parallel=ps)
     mdl.summary(file=sys.stderr)
 
+def reproducibility(cls, inputFile, mdFields, f, kargs, ps):
+    print('Test reproducibility')
+    tw = 0
+    results = []
+    for _ in range(3):
+        print('Initialize model %s with TW=%s ...' % (str(cls), ['one', 'idf', 'pmi'][tw]))
+        mdl = cls(tw=tw, min_df=2, rm_top=2, seed=42, **kargs)
+        print('Adding docs...')
+        for n, line in enumerate(open(inputFile, encoding='utf-8')):
+            ch = line.strip().split()
+            if len(ch) < mdFields + 1: continue
+            if mdFields: mdl.add_doc(ch[mdFields:], f(ch[:mdFields]))
+            else: mdl.add_doc(ch)
+        mdl.train(1000, workers=1)
+        if isinstance(mdl, tp.DTModel):
+            results.append([mdl.get_topic_words(k, timepoint=0) for k in range(mdl.k)])
+        else:
+            results.append([mdl.get_topic_words(k) for k in range(mdl.k)])
+
+    assert results[0] == results[1]
+    assert results[0] == results[2]
+
 def save_and_load(cls, inputFile, mdFields, f, kargs, ps):
     print('Test save & load')
     tw = 0
@@ -603,6 +625,10 @@ def test_purge_dead_topics():
             copy_train, uninit_doc,
         ]:
             locals()['test_{}_{}_{}'.format(model_case[0].__name__, func.__name__, ps.name)] = (lambda f, mc, ps: lambda: f(*(mc + (ps,))))(func, model_case[:-1], ps)
+
+    func = reproducibility
+    ps = tp.ParallelScheme.NONE
+    locals()['test_{}_{}_{}'.format(model_case[0].__name__, func.__name__, ps.name)] = (lambda f, mc, ps: lambda: f(*(mc + (ps,))))(func, model_case[:-1], ps)
 
 for model_case in model_asym_cases:
     pss = model_case[5]