model_vgg: VGG implementation

In torchvision: Models, Datasets and Transformations for Images

VGG implementation

Description

VGG models implementations based on Very Deep Convolutional Networks For Large-Scale Image Recognition

Usage

model_vgg11(pretrained = FALSE, progress = TRUE, ...)

model_vgg11_bn(pretrained = FALSE, progress = TRUE, ...)

model_vgg13(pretrained = FALSE, progress = TRUE, ...)

model_vgg13_bn(pretrained = FALSE, progress = TRUE, ...)

model_vgg16(pretrained = FALSE, progress = TRUE, ...)

model_vgg16_bn(pretrained = FALSE, progress = TRUE, ...)

model_vgg19(pretrained = FALSE, progress = TRUE, ...)

model_vgg19_bn(pretrained = FALSE, progress = TRUE, ...)

Arguments

pretrained	(bool): If TRUE, returns a model pre-trained on ImageNet
progress	(bool): If TRUE, displays a progress bar of the download to stderr
...	other parameters passed to the VGG model implementation.

Functions

• model_vgg11(): VGG 11-layer model (configuration "A")

• model_vgg11_bn(): VGG 11-layer model (configuration "A") with batch normalization

• model_vgg13(): VGG 13-layer model (configuration "B")

• model_vgg13_bn(): VGG 13-layer model (configuration "B") with batch normalization

• model_vgg16(): VGG 13-layer model (configuration "D")

• model_vgg16_bn(): VGG 13-layer model (configuration "D") with batch normalization

• model_vgg19(): VGG 19-layer model (configuration "E")

• model_vgg19_bn(): VGG 19-layer model (configuration "E") with batch normalization

torchvision documentation built on June 22, 2024, 11:25 a.m.