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torchvision (version 0.3.0)

model_vgg: 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