# VGG16

**Repository Path**: peter_small_f/VGG16

## Basic Information

- **Project Name**: VGG16
- **Description**: A PyTorch implementation of VGG16.  This could be considered as a variant of the original VGG16 since BN layers are added after each conv. layer
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-06-02
- **Last Updated**: 2021-06-21

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# VGG16

an implementation of VGG16 in pytorch.
VGG16 architecture is well depicted in the following image:

![](https://www.cs.toronto.edu/~frossard/post/vgg16/vgg16.png)

image source : https://blog.heuritech.com/2016/02/29/a-brief-report-of-the-heuritech-deep-learning-meetup-5/


### modified (batch norm. added in each cnn layer)
```python
        # 1-1 conv layer
        tnn.Conv2d(3, 64, kernel_size=3, padding=1),
        tnn.BatchNorm2d(64),
        tnn.ReLU(),

        # 1-2 conv layer
        tnn.Conv2d(64, 64, kernel_size=3, padding=1),
        tnn.BatchNorm2d(64),
        tnn.ReLU(),

```