# CumulativeDistributionTransform

Source: https://www.tensorplay.cn/docs/generated/tensorplay.distributions.CumulativeDistributionTransform.html

```python
class tensorplay.distributions.CumulativeDistributionTransform(distribution: Distribution, cache_size: int = 0)
```

Transform via the cumulative distribution function of a probability distribution.

Parameters:

distribution ([Distribution](/docs/generated/tensorplay.distributions.Distribution.html#tensorplay.distributions.Distribution)) – Distribution whose cumulative distribution function to use for
the transformation.

Example:

```
# Construct a Gaussian copula from a multivariate normal.
base_dist = MultivariateNormal(
    loc=tensorplay.zeros(2),
    scale_tril=LKJCholesky(2).sample(),
)
transform = CumulativeDistributionTransform(Normal(0, 1))
copula = TransformedDistribution(base_dist, [transform])
```

```python
forward_shape(shape)
```

Infers the shape of the forward computation, given the input shape.
Defaults to preserving shape.

```python
property inv: Transform
```

Returns the inverse [Transform](/docs/generated/tensorplay.distributions.Transform.html#tensorplay.distributions.Transform) of this transform.
This should satisfy t.inv.inv is t.

```python
inverse_shape(shape)
```

Infers the shapes of the inverse computation, given the output shape.
Defaults to preserving shape.