# OneHotCategoricalStraightThrough

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

```python
class tensorplay.distributions.OneHotCategoricalStraightThrough(probs: Tensor | None = None, logits: Tensor | None = None, validate_args: bool | None = None)
```

Creates a reparameterizable [OneHotCategorical](/docs/generated/tensorplay.distributions.OneHotCategorical.html#tensorplay.distributions.OneHotCategorical) distribution based on the straight-
through gradient estimator from [1].

[1] Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
(Bengio et al., 2013)

```python
property batch_shape: Size
```

Returns the shape over which parameters are batched.

```python
cdf(value: Tensor) → Tensor
```

Returns the cumulative density/mass function evaluated at
value.

Parameters:

value ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor))

```python
property event_shape: Size
```

Returns the shape of a single sample (without batching).

```python
icdf(value: Tensor) → Tensor
```

Returns the inverse cumulative density/mass function evaluated at
value.

Parameters:

value ([Tensor](/docs/generated/tensorplay.Tensor.html#tensorplay.Tensor))

```python
perplexity() → Tensor
```

Returns perplexity of distribution, batched over batch_shape.

Returns:

Tensor of shape batch_shape.

```python
sample_n(n: int) → Tensor
```

Generates n samples or n batches of samples if the distribution
parameters are batched.

```python
static set_default_validate_args(value: bool) → None
```

Sets whether validation is enabled or disabled.

The default behavior mimics Python’s assert statement: validation
is on by default, but is disabled if Python is run in optimized mode
(via python -O). Validation may be expensive, so you may want to
disable it once a model is working.

Parameters:

value ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – Whether to enable validation.

```python
property stddev: Tensor
```

Returns the standard deviation of the distribution.