Q & A

How to train my customized network using the framework of APS?

There are two options. The first one is straightforward: modify the source code of the APS following the steps:
- Give your implementation of network structure if needed in aps.asr, aps.sse or aps.xxx (may coming in the future) and decorate it using @ApsRegisters.xxx.register(...).
- Give your implementation of Task if needed in aps.task and also decorate it using @ApsRegisters.task.register(...).
- Give your implementation of dataloader if needed in aps.loader and also decorate with @ApsRegisters.loader.register(...).
- Prepare your training & validation & test data & configuration files and train the models using the scripts scripts/*.sh.
  
  If new python files are added, remember to update the ApsModules class in aps/libs.py to make sure your implementation can be imported correctly.
Another way only requires us to modify the training configurations. Assuming we have my_nnet.py, my_task.py under /path/to/my_code, the .yaml configuration like
```
nnet: /path/to/my_code/my_nnet.py:MyNnet
nnet_conf:
    # put parameters here
    ...
task: /path/to/my_code/my_task.py:MyTask
task_conf:
    # put parameters here
    ...
# other configurations
...
```
could be used. In this case, please remember to make sure there is no import errors in your python code.