def test_shape(di, dj, dk):
x = self._gen_sparse(2, 20, [di, dj])[0]
y = self.randn(dj, dk)
res = torch.hsmm(x, y)
expected = torch.mm(x.to_dense(), y)
self.assertEqual(res.to_dense(), expected)
def test_shape(di, dj, dk):
x = self._gen_sparse(2, 20, [di, dj])[0]
y = self.randn(dj, dk)
res = torch.hsmm(x, y)
expected = torch.mm(x.to_dense(), y)
self.assertEqual(res.to_dense(), expected)
def test_shape(di, dj, dk):
x = self._gen_sparse(2, 20, [di, dj])[0]
y = self.randn(dj, dk)
res = torch.hsmm(x, y)
# TODO: use self.safeToDense(), but this triggers
# https://github.com/pytorch/pytorch/issues/3170
expected = torch.mm(x.to_dense(), y)
self.assertEqual(res.to_dense(), expected)
def test_shape(di, dj, dk):
x = self._gen_sparse(2, 20, [di, dj])[0]
y = self.randn(dj, dk)
res = torch.hsmm(x, y)
# TODO: use self.safeToDense(), but this triggers
# https://github.com/pytorch/pytorch/issues/3170
expected = torch.mm(x.to_dense(), y)
self.assertEqual(res.to_dense(), expected)
