def __init__(self, device=None, learning_rate=1e-3, act=F.relu, n_cls=10):
# Settings
self.device = device
self.act = act
self.learning_rate = learning_rate
self.n_cls = n_cls
# Losses
self.md_loss = MeanDistanceLoss()
self.er_loss = EntropyRegularizationLoss()
self.d_loss = DistanceLoss()
# Model
from recon.cifar10.cnn_model_001 import Encoder, MLP, Decoder
self.encoder = Encoder(device, act)
self.mlp = MLP(device, act)
self.encoder.to_gpu(device) if self.device else None
self.mlp.to_gpu(device) if self.device else None
# Optimizer
self.optimizer_enc = optimizers.Adam(learning_rate)
self.optimizer_enc.setup(self.encoder)
self.optimizer_enc.use_cleargrads()
self.optimizer_mlp = optimizers.Adam(learning_rate)
self.optimizer_mlp.setup(self.mlp)
self.optimizer_mlp.use_cleargrads()
def __init__(self, device=None, learning_rate=1e-3, act=F.relu, n_cls=10):
# Settings
self.device = device
self.act = act
self.learning_rate = learning_rate
self.n_cls = n_cls
# Losses
self.recon_loss = ReconstructionLoss()
self.er_loss = EntropyRegularizationLoss()
# Model
from recon.cifar10.cnn_model_007 import Encoder, Decoder
self.encoder = Encoder(device, act)
self.decoder = Decoder(device, act)
self.encoder.to_gpu(device) if self.device else None
self.decoder.to_gpu(device) if self.device else None
# Optimizer
self.optimizer_enc = optimizers.Adam(learning_rate)
self.optimizer_enc.setup(self.encoder)
self.optimizer_enc.use_cleargrads()
self.optimizer_dec = optimizers.Adam(learning_rate)
self.optimizer_dec.setup(self.decoder)
self.optimizer_dec.use_cleargrads()
def __init__(self, device=None, learning_rate=1e-3, act=F.relu, n_cls=10):
# Settings
self.device = device
self.act = act
self.learning_rate = learning_rate
self.n_cls = n_cls
# Losses
self.recon_loss = ReconstructionLoss()
self.gan_loss = GANLoss()
self.er_loss = EntropyRegularizationLoss()
# Model
from recon.svhn.cnn_model_000 \
import Encoder, MLP, Decoder, Discriminator
self.encoder = Encoder(device, act)
self.mlp = MLP(device, act)
self.decoder = Decoder(device, act)
self.discriminator = Discriminator(device, act, n_cls)
self.encoder.to_gpu(device) if self.device else None
self.mlp.to_gpu(device) if self.device else None
self.decoder.to_gpu(device) if self.device else None
self.discriminator.to_gpu(device) if self.device else None
# Optimizer
self.optimizer_enc = optimizers.Adam(learning_rate)
self.optimizer_enc.setup(self.encoder)
self.optimizer_enc.use_cleargrads()
self.optimizer_mlp = optimizers.Adam(learning_rate)
self.optimizer_mlp.setup(self.mlp)
self.optimizer_mlp.use_cleargrads()
self.optimizer_dec = optimizers.Adam(learning_rate)
self.optimizer_dec.setup(self.decoder)
self.optimizer_dec.use_cleargrads()
self.optimizer_dis = optimizers.Adam(learning_rate)
self.optimizer_dis.setup(self.discriminator)
self.optimizer_dis.use_cleargrads()