RetinaNetFocalLoss: RetinaNetFocalLoss

View source: R/fastaibuilt.R

RetinaNetFocalLossR Documentation

RetinaNetFocalLoss

Description

Base class for all neural network modules.

Usage

RetinaNetFocalLoss(...)

Arguments

...

parameters to pass

Details

Your models should also subclass this class. Modules can also contain other Modules, allowing to nest them in a tree structure. You can assign the submodules as regular attributes:: import torch.nn as nn import torch.nn.functional as F class Model(nn.Module): def __init__(self): super(Model, self).__init__() self.conv1 = nn.Conv2d(1, 20, 5) self.conv2 = nn.Conv2d(20, 20, 5) def forward(self, x): x = F.relu(self.conv1(x)) return F.relu(self.conv2(x)) Submodules assigned in this way will be registered, and will have their parameters converted too when you call :meth:'to', etc.

Value

None


fastai documentation built on March 21, 2022, 9:07 a.m.