def setUp(self):
seed_rng()
self.base = tensor.lmatrix()
self.amt = tensor.lmatrix()
self.i0 = tensor.lvector()
self.i1 = tensor.lvector()
self.zget = sparse_gram_get(self.base, self.i0, self.i1)
self.zset = sparse_gram_set(self.base, self.amt, self.i0, self.i1)
self.zinc = sparse_gram_inc(self.base, self.amt, self.i0, self.i1)
self.zmul = sparse_gram_mul(self.base, self.amt, self.i0, self.i1)
self.vbase0 = numpy.zeros((5, 6), dtype='int')
self.vbase1 = (1 + numpy.zeros((5, 6), dtype='int'))
self.vbase2 = (2 + numpy.zeros((5, 6), dtype='int'))
self.vbase9 = (9 + numpy.zeros((5, 6), dtype='int'))
self.vbaser = numpy.arange(30).reshape(5, 6).astype('int')
self.vamt = (1 + numpy.arange(6)).reshape(2, 3).astype('int')
self.vi0 = numpy.asarray([0, 3])
self.vi1 = numpy.asarray([1, 2, 4])
def op(x):
return sparse_gram_get(x, self.vi0, self.vi1)