@@ -123,7 +123,7 @@ It means following the algorithm's default setting for compressed operations wit
#### Quantization specific keys
**If you use quantization algorithms, you need to specify more keys. If you use pruning algorithms, you can safely skip these keys**
Besides the keys explained above, if you use quantization algorithms you need to specify more keys in `config_list`, which are explained below.
* __quant_types__ : list of string.
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@@ -148,6 +148,31 @@ when the value is int type, all quantization types share same bits length. eg.
}
```
The following example shows a more complete `config_list`, it uses `op_names` (or `op_types`) to specify the target layers along with the quantization bits for those layers.
```
configure_list = [{
'quant_types': ['weight'],
'quant_bits': 8,
'op_names': ['conv1']
}, {
'quant_types': ['weight'],
'quant_bits': 4,
'quant_start_step': 0,
'op_names': ['conv2']
}, {
'quant_types': ['weight'],
'quant_bits': 3,
'op_names': ['fc1']
},
{
'quant_types': ['weight'],
'quant_bits': 2,
'op_names': ['fc2']
}
]
```
In this example, 'op_names' is the name of layer and four layers will be quantized to different quant_bits.
### APIs for Updating Fine Tuning Status
Some compression algorithms use epochs to control the progress of compression (e.g. [AGP](https://nni.readthedocs.io/en/latest/Compressor/Pruner.html#agp-pruner)), and some algorithms need to do something after every minibatch. Therefore, we provide another two APIs for users to invoke: `pruner.update_epoch(epoch)` and `pruner.step()`.
