Performs a single optimization step. Arguments: closure (callable, optional): A closure that reevaluates the model

Update the learning rate at the end of the given epoch.

Performs a single optimization step. Arguments: closure (callable, optional): A closure that reevaluates the model

Performs a single optimization step. Arguments: closure (callable, optional): A closure that reevaluates the model

Update the learning rate at the end of the given epoch.

Update the learning rate after each update.

Update the learning rate after each update.

change the first element of a tensor to scalar

VGG 11-layer model (configuration "A") Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

VGG 11-layer model (configuration "A") with batch normalization

VGG 13-layer model (configuration "B") Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

VGG 13-layer model (configuration "B") with batch normalization

VGG 16-layer model (configuration "D") Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

VGG 16-layer model (configuration "D") with batch normalization

VGG 19-layer model (configuration "E") Args: pretrained (bool): If True, returns a model pre-trained on ImageNet

VGG 19-layer model (configuration 'E') with batch normalization

Constructs a Wide Residual Networks.