Minimal API for receptive field calculation in PyTorch
- PyTorch >= 0.4
- Python 3
- MatPlotLib (optional)
>>> import torch.nn as nn
>>> from receptivefield import receptivefield
>>> net = nn.Sequential(
nn.Conv2d(in_channels=3, out_channels=32, stride=2, kernel_size=3),
nn.ReLU(),
nn.Conv2d(in_channels=32, out_channels=10, kernel_size=3),
)
>>> print(receptivefield(net, (1, 3, 32, 48)))
ReceptiveField(
offset=Vector(x=0, y=0),
stride=Vector(x=2, y=2),
rfsize=Size(w=7, h=7),
outputsize=Size(w=21, h=13),
inputsize=Size(w=48, h=32)
)
ReceptiveField.show can be used to visualize the receptive field on a checkerboard image.
Crosses denote the centers of receptive fields, and colored rectangles show their extent.
Not all rectangles are plotted to avoid crowding the image.
