Simple Code Implementation of "Xception" architecture using PyTorch.
For simplicity, i write codes in ipynb. So, you can easliy test my code.
Last update : 2018/12/19
- hoya012
Python 3.5
numpy
matplotlib
torch=1.0.0
torchvision
You only run Xception_pytorch.ipynb.
For test, i used CIFAR-10 Dataset and resize image scale from 32x32 to 299x299.
If you want to use own dataset, you can simply resize images.
In Xception, there are many depthwise separable convolution operation. This is my simple implemenatation.
class depthwise_separable_conv(nn.Module):
def __init__(self, nin, nout, kernel_size, padding, bias=False):
super(depthwise_separable_conv, self).__init__()
self.depthwise = nn.Conv2d(nin, nin, kernel_size=kernel_size, padding=padding, groups=nin, bias=bias)
self.pointwise = nn.Conv2d(nin, nout, kernel_size=1, bias=bias)
def forward(self, x):
out = self.depthwise(x)
out = self.pointwise(out)
return out
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