TransformedDistribution¶
- class paddle.distribution. TransformedDistribution ( base, transforms ) [source]
-
Applies a sequence of Transforms to a base distribution.
- Parameters
-
base (Distribution) – The base distribution.
transforms (Sequence[Transform]) – A sequence of
Transform
.
Examples
import paddle from paddle.distribution import transformed_distribution d = transformed_distribution.TransformedDistribution( paddle.distribution.Normal(0., 1.), [paddle.distribution.AffineTransform(paddle.to_tensor(1.), paddle.to_tensor(2.))] ) print(d.sample([10])) # Tensor(shape=[10], dtype=float32, place=Place(gpu:0), stop_gradient=True, # [-0.10697651, 3.33609009, -0.86234951, 5.07457638, 0.75925219, # -4.17087793, 2.22579336, -0.93845034, 0.66054249, 1.50957513]) print(d.log_prob(paddle.to_tensor(0.5))) # Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True, # -1.64333570)
-
sample
(
shape=()
)
sample¶
-
Sample from
TransformedDistribution
.- Parameters
-
shape (Sequence[int], optional) – The sample shape. Defaults to ().
- Returns
-
The sample result.
- Return type
-
[Tensor]
-
rsample
(
shape=()
)
rsample¶
-
Reparameterized sample from
TransformedDistribution
.- Parameters
-
shape (Sequence[int], optional) – The sample shape. Defaults to ().
- Returns
-
The sample result.
- Return type
-
[Tensor]
-
log_prob
(
value
)
log_prob¶
-
The log probability evaluated at value.
- Parameters
-
value (Tensor) – The value to be evaluated.
- Returns
-
The log probability.
- Return type
-
Tensor
- property batch_shape
-
Returns batch shape of distribution
- Returns
-
batch shape
- Return type
-
Sequence[int]
-
entropy
(
)
entropy¶
-
The entropy of the distribution.
- property event_shape
-
Returns event shape of distribution
- Returns
-
event shape
- Return type
-
Sequence[int]
-
kl_divergence
(
other
)
[source]
kl_divergence¶
-
The KL-divergence between self distributions and other.
- property mean
-
Mean of distribution
-
prob
(
value
)
prob¶
-
Probability density/mass function evaluated at value.
- Parameters
-
value (Tensor) – value which will be evaluated
-
probs
(
value
)
probs¶
-
Probability density/mass function.
Note
This method will be deprecated in the future, please use prob instead.
- property variance
-
Variance of distribution