brails.processors.FoundationClassifier.models.resnet_applied module

class brails.processors.FoundationClassifier.models.resnet_applied.ResNet(block, layers, low_dim=128)

Bases: Module

forward(x)

Define the computation performed at every call.

Should be overridden by all subclasses.

Note

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

brails.processors.FoundationClassifier.models.resnet_applied.resnet101(pretrained=False, **kwargs)

Constructs a ResNet-101 model.

Args:

pretrained (bool): If True, returns a model pre-trained on ImageNet

brails.processors.FoundationClassifier.models.resnet_applied.resnet152(pretrained=False, **kwargs)

Constructs a ResNet-152 model.

Args:

pretrained (bool): If True, returns a model pre-trained on ImageNet

brails.processors.FoundationClassifier.models.resnet_applied.resnet18(pretrained=False, **kwargs)

Constructs a ResNet-18 model.

Args:

pretrained (bool): If True, returns a model pre-trained on ImageNet

brails.processors.FoundationClassifier.models.resnet_applied.resnet34(pretrained=False, **kwargs)

Constructs a ResNet-34 model.

Args:

pretrained (bool): If True, returns a model pre-trained on ImageNet

brails.processors.FoundationClassifier.models.resnet_applied.resnet50(pretrained=False, **kwargs)

Constructs a ResNet-50 model.

Args:

pretrained (bool): If True, returns a model pre-trained on ImageNet