def test_op(self): n = tensor.lscalar() f = theano.function([self.p, n], multinomial(n, self.p)) _n = 5 tested = f(self._p, _n) assert tested.shape == self._p.shape assert numpy.allclose(numpy.floor(tested.todense()), tested.todense()) assert tested[2, 1] == _n n = tensor.lvector() f = theano.function([self.p, n], multinomial(n, self.p)) _n = numpy.asarray([1, 2, 3, 4], dtype='int64') tested = f(self._p, _n) assert tested.shape == self._p.shape assert numpy.allclose(numpy.floor(tested.todense()), tested.todense()) assert tested[2, 1] == _n[2]
def test_op(self): n = tensor.lscalar() f = theano.function([self.p, n], multinomial(n, self.p)) _n = 5 tested = f(self._p, _n) assert tested.shape == self._p.shape assert np.allclose(np.floor(tested.todense()), tested.todense()) assert tested[2, 1] == _n n = tensor.lvector() f = theano.function([self.p, n], multinomial(n, self.p)) _n = np.asarray([1, 2, 3, 4], dtype='int64') tested = f(self._p, _n) assert tested.shape == self._p.shape assert np.allclose(np.floor(tested.todense()), tested.todense()) assert tested[2, 1] == _n[2]
def test_infer_shape(self): self._compile_and_check([self.p], [multinomial(5, self.p)], [self._p], self.op_class, warn=False)