h0rton.models.bayesian_resnet

Module Contents

Functions

resnet34(progress=True, **kwargs) ResNet-34 model from
resnet50(progress=True, **kwargs) ResNet-50 model from
resnet101(progress=True, **kwargs) ResNet-101 model from
resnet44(progress=True, **kwargs) ResNet-34 model from
resnet56(progress=True, **kwargs) ResNet-34 model from
h0rton.models.bayesian_resnet.resnet34(progress=True, **kwargs)[source]

ResNet-34 model from “Deep Residual Learning for Image Recognition”

Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet progress (bool): If True, displays a progress bar of the download to stderr
h0rton.models.bayesian_resnet.resnet50(progress=True, **kwargs)[source]

ResNet-50 model from “Deep Residual Learning for Image Recognition”

Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet progress (bool): If True, displays a progress bar of the download to stderr
h0rton.models.bayesian_resnet.resnet101(progress=True, **kwargs)[source]

ResNet-101 model from “Deep Residual Learning for Image Recognition”

Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet progress (bool): If True, displays a progress bar of the download to stderr
h0rton.models.bayesian_resnet.resnet44(progress=True, **kwargs)[source]

ResNet-34 model from “Deep Residual Learning for Image Recognition”

Args:
progress (bool): If True, displays a progress bar of the download to stderr
h0rton.models.bayesian_resnet.resnet56(progress=True, **kwargs)[source]

ResNet-34 model from “Deep Residual Learning for Image Recognition”

Args:
progress (bool): If True, displays a progress bar of the download to stderr