Return one image and its corresponding attribute label.

Return a data point and its metadata information. Parameters: index - - a random integer for data indexing Returns:

Return a data point and its metadata information. Parameters: index (int) -- a random integer for data indexing Ret

Return one image and its corresponding attribute label.

FGSM, I-FGSM and PGD attacks epsilon: magnitude of attack k: iterations a: step size

Initialize configurations.

Initialize configurations.

Initialize configurations.

Initialize summary writer.

Initialize and preprocess the CelebA dataset.

FGSM, I-FGSM and PGD attacks epsilon: magnitude of attack k: iterations a: step size

FGSM, I-FGSM and PGD attacks epsilon: magnitude of attack k: iterations a: step size

FGSM, I-FGSM and PGD attacks epsilon: magnitude of attack k: iterations a: step size

Initialize and preprocess the CelebA dataset.

Initialize the class; save the options in the class Parameters: opt (Option class)-- stores all the experiment flags; needs to be

Initialize this class Step 1: create a dataset instance given the name [dataset_mode] Step 2: create a multi-threaded data loader.

Initialize this dataset class. Parameters: opt (Option class) -- stores all the experiment flags; needs to be a subclass of BaseO

Reset the class; indicates the class hasn't been initailized

Initialize the CycleGAN class. Parameters: opt (Option class)-- stores all the experiment flags; needs to be a subclass of BaseOpt

Construct a Resnet-based generator Parameters: input_nc (int) -- the number of channels in input images output_n

Initialize the Resnet block A resnet block is a conv block with skip connections We construct a conv block with build_conv_block func

Construct a Unet generator Parameters: input_nc (int) -- the number of channels in input images output_nc (int) -- th

Construct a Unet submodule with skip connections. Parameters: outer_nc (int) -- the number of filters in the outer conv layer

Construct a PatchGAN discriminator Parameters: input_nc (int) -- the number of channels in input images ndf (int)

Construct a 1x1 PatchGAN discriminator Parameters: input_nc (int) -- the number of channels in input images ndf (int

Initialize the BaseModel class. Parameters: opt (Option class)-- stores all the experiment flags; needs to be a subclass of BaseO

Initialize the CycleGAN class. Parameters: opt (Option class)-- stores all the experiment flags; needs to be a subclass of BaseOpt

Construct a Resnet-based generator Parameters: input_nc (int) -- the number of channels in input images output_n

Initialize the Resnet block A resnet block is a conv block with skip connections We construct a conv block with build_conv_block func

Construct a Unet generator Parameters: input_nc (int) -- the number of channels in input images output_nc (int) -- th

Construct a Unet submodule with skip connections. Parameters: outer_nc (int) -- the number of filters in the outer conv layer

Construct a PatchGAN discriminator Parameters: input_nc (int) -- the number of channels in input images ndf (int)

Construct a 1x1 PatchGAN discriminator Parameters: input_nc (int) -- the number of channels in input images ndf (int

Initialize the HTML classes Parameters: web_dir (str) -- a directory that stores the webpage. HTML file will be created at <web_d

Initialize the Visualizer class Parameters: opt -- stores all the experiment flags; needs to be a subclass of BaseOptions

Initialize the ImagePool class Parameters: pool_size (int) -- the size of image buffer, if pool_size=0, no buffer will be created

Initialize configurations.

Initialize summary writer.

Initialize and preprocess the CelebA dataset.

FGSM, I-FGSM and PGD attacks epsilon: magnitude of attack k: iterations a: step size

Return a batch of data

Return the number of images.