def log_prob(self, value):
"""probability mass function evaluated at value
Args:
value (Tensor): value to be evaluated.
Returns:
Tensor: probability of value.
"""
if paddle.is_integer(value):
value = paddle.cast(value, self.probs.dtype)
logits, value = paddle.broadcast_tensors(
[paddle.log(self.probs), value])
logits[(value == 0) & (paddle.isinf(logits))] = 0
return (paddle.lgamma(value.sum(-1) + 1) -
paddle.lgamma(value + 1).sum(-1) + (value * logits).sum(-1))
def test_for_exception(self):
with self.assertRaises(TypeError):
paddle.is_integer(np.array([1, 2]))
def test_for_floating_point(self):
x = paddle.randn([2, 3])
self.assertFalse(paddle.is_integer(x))
def test_for_complex(self):
x = paddle.randn([2, 3]) + 1j * paddle.randn([2, 3])
self.assertFalse(paddle.is_integer(x))
def test_for_integer(self):
x = paddle.arange(10)
self.assertTrue(paddle.is_integer(x))