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* wip * add torchvision learners * desc * ... * ... * ... * ... * fix example * ... * ...
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,180 @@ | ||
| #' @title AlexNet Image Classifier | ||
| #' | ||
| #' @name mlr_learners.torchvision | ||
| #' | ||
| #' @description | ||
| #' Classic image classification networks from `torchvision`. | ||
| #' | ||
| #' @section Parameters: | ||
| #' Parameters from [`LearnerTorchImage`] and | ||
| #' | ||
| #' * `pretrained` :: `logical(1)`\cr | ||
| #' Whether to use the pretrained model. | ||
| #' The final linear layer will be replaced with a new `nn_linear` with the | ||
| #' number of classes inferred from the [`Task`][mlr3::Task]. | ||
| #' | ||
| #' @section Properties: | ||
| #' * Supported task types: `"classif"` | ||
| #' * Predict Types: `"response"` and `"prob"` | ||
| #' * Feature Types: `"lazy_tensor"` | ||
| #' * Required packages: `"mlr3torch"`, `"torch"`, `"torchvision"` | ||
| #' @template params_learner | ||
| #' @param name (`character(1)`)\cr | ||
| #' The name of the network. | ||
| #' @param module_generator (`function(pretrained, num_classes)`)\cr | ||
| #' Function that generates the network. | ||
| #' @param label (`character(1)`)\cr | ||
| #' The label of the network. | ||
| #'#' @references | ||
| #' `r format_bib("krizhevsky2017imagenet")` | ||
| #' `r format_bib("sandler2018mobilenetv2")` | ||
| #' `r format_bib("he2016deep")` | ||
| #' `r format_bib("simonyan2014very")` | ||
| #' @include LearnerTorchImage.R | ||
| #' @export | ||
| LearnerTorchVision = R6Class("LearnerTorchVision", | ||
| inherit = LearnerTorchImage, | ||
| public = list( | ||
| #' @description Creates a new instance of this [R6][R6::R6Class] class. | ||
| initialize = function(name, module_generator, label, optimizer = NULL, loss = NULL, callbacks = list()) { # nolint | ||
| task_type = "classif" | ||
| private$.module_generator = module_generator | ||
| param_set = ps( | ||
| pretrained = p_lgl(tags = c("required", "train")) | ||
| ) | ||
| param_set$values = list(pretrained = TRUE) | ||
| super$initialize( | ||
| task_type = task_type, | ||
| id = paste0(task_type, ".", name), | ||
| param_set = param_set, | ||
| man = paste0("mlr3torch::mlr_learners.torchvision"), | ||
| optimizer = optimizer, | ||
| loss = loss, | ||
| callbacks = callbacks, | ||
| label = label | ||
| ) | ||
| } | ||
| ), | ||
| private = list( | ||
| .module_generator = NULL, | ||
| .network = function(task, param_vals) { | ||
| nout = get_nout(task) | ||
| if (param_vals$pretrained) { | ||
| network = replace_head(private$.module_generator(pretrained = TRUE), nout) | ||
| return(network) | ||
| } | ||
| private$.module_generator(pretrained = FALSE, num_classes = nout) | ||
| }, | ||
| .additional_phash_input = function() { | ||
| list(private$.module_generator) | ||
| } | ||
| ) | ||
| ) | ||
|
|
||
| #' @export | ||
| replace_head.AlexNet = function(network, d_out) { | ||
| network$classifier$`6` = torch::nn_linear( | ||
| in_features = network$classifier$`6`$in_features, | ||
| out_features = d_out, | ||
| bias = TRUE | ||
| ) | ||
| network | ||
| } | ||
|
|
||
| # #' @export | ||
| # replace_head.Inception3 = function(network, d_out) { | ||
| # network$fc = nn_linear(2048, d_out) | ||
| # network | ||
| # } | ||
|
|
||
| #' @export | ||
| replace_head.mobilenet_v2 = function(network, d_out) { | ||
| network$classifier$`1` = nn_linear(1280, d_out) | ||
| network | ||
| } | ||
|
|
||
| #' @export | ||
| replace_head.resnet = function(network, d_out) { | ||
| in_features = network$fc$in_features | ||
| network$fc = nn_linear(in_features, d_out) | ||
| network | ||
| } | ||
|
|
||
| #' @export | ||
| replace_head.VGG = function(network, d_out) { | ||
| network$classifier$`6` = nn_linear(4096, d_out) | ||
| network | ||
| } | ||
|
|
||
| #' @include zzz.R | ||
| register_learner("classif.alexnet", function() { | ||
| LearnerTorchVision$new("alexnet", torchvision::model_alexnet, "AlexNet") | ||
| }) | ||
|
|
||
| # register_learner("classif.inception_v3", function() { | ||
| # LearnerTorchVision$new("inception_v3", torchvision::model_inception_v3, "Inception V3") | ||
| # }) | ||
|
|
||
| register_learner("classif.mobilenet_v2", function() { | ||
| LearnerTorchVision$new("mobilenet_v2", torchvision::model_mobilenet_v2, "Mobilenet V2") | ||
| }) | ||
|
|
||
| register_learner("classif.resnet18", function() { | ||
| LearnerTorchVision$new("resnet18", torchvision::model_resnet18, "ResNet-18") | ||
| }) | ||
|
|
||
| register_learner("classif.resnet34", function() { | ||
| LearnerTorchVision$new("resnet34", torchvision::model_resnet34, "ResNet-34") | ||
| }) | ||
|
|
||
| register_learner("classif.resnet50", function() { | ||
| LearnerTorchVision$new("resnet50", torchvision::model_resnet50, "ResNet-50") | ||
| }) | ||
|
|
||
| register_learner("classif.resnet101", function() { | ||
| LearnerTorchVision$new("resnet101", torchvision::model_resnet101, "ResNet-101") | ||
| }) | ||
|
|
||
| register_learner("classif.resnet152", function() { | ||
| LearnerTorchVision$new("resnet152", torchvision::model_resnet152, "ResNet-152") | ||
| }) | ||
|
|
||
| register_learner("classif.resnext101_32x8d", function() { | ||
| LearnerTorchVision$new("resnext101_32x8d", torchvision::model_resnext101_32x8d, "ResNeXt-101 32x8d") | ||
| }) | ||
|
|
||
| register_learner("classif.resnext50_32x4d", function() { | ||
| LearnerTorchVision$new("resnext50_32x4d", torchvision::model_resnext50_32x4d, "ResNeXt-50 32x4d") | ||
| }) | ||
|
|
||
| register_learner("classif.vgg11", function() { | ||
| LearnerTorchVision$new("vgg11", torchvision::model_vgg11, "VGG 11") | ||
| }) | ||
|
|
||
| register_learner("classif.vgg11_bn", function() { | ||
| LearnerTorchVision$new("vgg11_bn", torchvision::model_vgg11_bn, "VGG 11") | ||
| }) | ||
|
|
||
| register_learner("classif.vgg13", function() { | ||
| LearnerTorchVision$new("vgg13", torchvision::model_vgg13, "VGG 13") | ||
| }) | ||
|
|
||
| register_learner("classif.vgg13_bn", function() { | ||
| LearnerTorchVision$new("vgg13_bn", torchvision::model_vgg13_bn, "VGG 13") | ||
| }) | ||
|
|
||
| register_learner("classif.vgg16", function() { | ||
| LearnerTorchVision$new("vgg16", torchvision::model_vgg16, "VGG 16") | ||
| }) | ||
|
|
||
| register_learner("classif.vgg16_bn", function() { | ||
| LearnerTorchVision$new("vgg16_bn", torchvision::model_vgg16_bn, "VGG 16") | ||
| }) | ||
|
|
||
| register_learner("classif.vgg19", function() { | ||
| LearnerTorchVision$new("vgg19", torchvision::model_vgg19, "VGG 19") | ||
| }) | ||
|
|
||
| register_learner("classif.vgg19_bn", function() { | ||
| LearnerTorchVision$new("vgg19_bn", torchvision::model_vgg19_bn, "VGG 19") | ||
| }) |
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