SqueezeNet (Deep Java Library 0.25.0 - model-zoo API)

java.lang.Object
- ai.djl.basicmodelzoo.cv.classification.SqueezeNet

```
public final class SqueezeNet
extends java.lang.Object
```
SqueezeNet contains a generic implementation of Squeezenet adapted from [torchvision implmentation](https://github.com/pytorch/vision/blob/master/torchvision/models/squeezenet.py)
Squeezenet is an efficient NN used for Image classification. It provides both performance boost and a tiny size. It's a good choice to adopt squeezenet for application runs on Mobile or Edge devices. Implementing the original squeezenet from Forrest N. Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, William J. Dally, Kurt Keutzer. "SQUEEZENET: ALEXNET-LEVEL ACCURACY WITH 50X FEWER PARAMETERS AND 0.5MB MODEL SIZE"

- Method Summary
  
  All Methods Static Methods Concrete Methods
  Modifier and Type Method Description
  
  static ai.djl.nn.Block squeezenet(int outSize)
  Construct squeezenet v1.1.
  - Methods inherited from class java.lang.Object
    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Method Detail
  - squeezenet
```
public static ai.djl.nn.Block squeezenet(int outSize)
```
    Construct squeezenet v1.1.
    
    Parameters:
    
    outSize - the number of output classes
    
    Returns:
    
    squeezenet Block