def ner_predict_proba():
from nerwindow import WindowMLP
np.random.seed(10)
wv = np.random.randn(20, 10)
clf = WindowMLP(wv, windowsize=3, dims=[None, 15, 3], rseed=10)
p = clf.predict_proba([1, 2, 3])
assert (len(p.flatten()) == 3)
p = clf.predict_proba([[1, 2, 3], [2, 3, 4]])
assert (np.ndim(p) == 2)
assert (p.shape == (2, 3))
def ner_predict_proba():
from nerwindow import WindowMLP
np.random.seed(10)
wv = np.random.randn(20,10)
clf = WindowMLP(wv, windowsize=3,
dims = [None, 15, 3], rseed=10)
p = clf.predict_proba([1,2,3])
assert(len(p.flatten()) == 3)
p = clf.predict_proba([[1,2,3], [2,3,4]])
assert(np.ndim(p) == 2)
assert(p.shape == (2,3))
