# JoinHook

Source: https://www.tensorplay.cn/docs/generated/tensorplay.distributed.algorithms.JoinHook.html

```python
class tensorplay.distributed.algorithms.JoinHook
```

This defines a join hook, which provides two entry points in the join context manager.

Entry points : a main hook, which is called repeatedly while there exists a non-joined
process, and a post-hook, which is called once all processes have joined.

To implement a join hook for the generic join context manager, define a
class that inherits from [JoinHook](#tensorplay.distributed.algorithms.JoinHook) and override main_hook() and
post_hook() as appropriate.

```python
main_hook() → None
```

Call this hook while there exists a non-joined process to shadow collective communications in a training iteration.

Training iteration i.e., in one forward pass, backward pass, and optimizer step.

```python
post_hook(is_last_joiner: bool) → None
```

Call hook after all processes have joined.

It is passed an additional bool argument is_last_joiner, which indicates if the rank is one of the last to join.

Parameters:

is_last_joiner ([bool](https://docs.python.org/3/builtins/functions.html#bool)) – True if the rank is one of the last to
join; False otherwise.