#include <toolkits/style_transfer/st_resnet16_model_trainer.hpp>

Public Member Functions
	ResNet16Checkpoint (Config config, const std::string &resnet_mlmodel_path)

	ResNet16Checkpoint (Config config, neural_net::float_array_map weights)

std::unique_ptr< ModelTrainer >	CreateModelTrainer () const override

neural_net::model_spec	ExportToCoreML () const override

Detailed Description

Subclass of Checkpoint that generates ResNet16ModelTrainer instances.

Definition at line 19 of file st_resnet16_model_trainer.hpp.

Constructor & Destructor Documentation

◆ ResNet16Checkpoint() [1/2]

turi::style_transfer::ResNet16Checkpoint::ResNet16Checkpoint	(	Config	config,
		const std::string &	resnet_mlmodel_path
	)

Loads a pretrained model to use as a starting point.

◆ ResNet16Checkpoint() [2/2]

turi::style_transfer::ResNet16Checkpoint::ResNet16Checkpoint	(	Config	config,
		neural_net::float_array_map	weights
	)

Loads weights saved from a ResNet16ModelTrainer.

Member Function Documentation

◆ CreateModelTrainer()

std::unique_ptr<ModelTrainer> turi::style_transfer::ResNet16Checkpoint::CreateModelTrainer ( ) const

overridevirtual

Loads the checkpoint into an active ModelTrainer instance.

Implements turi::style_transfer::Checkpoint.

◆ ExportToCoreML()

neural_net::model_spec turi::style_transfer::ResNet16Checkpoint::ExportToCoreML ( ) const

overridevirtual

Returns the CoreML spec corresponding to the current model.

The first layer of the model should have a single input: the image to stylize. The last layer of the model should have a single output: the stylized image.