def __init__(self, model, optimizer, device, config):
print('PI-v2')
self.model = model
self.optimizer = optimizer
self.ce_loss = torch.nn.CrossEntropyLoss(ignore_index=NO_LABEL)
self.cons_loss = mse_with_softmax #F.mse_loss
self.save_dir = '{}-{}_{}-{}_{}'.format(
config.arch, config.model, config.dataset, config.num_labels,
datetime.datetime.now().strftime("%Y-%m-%d-%H-%M"))
self.save_dir = os.path.join(config.save_dir, self.save_dir)
self.usp_weight = config.usp_weight
self.rampup = exp_rampup(config.weight_rampup)
self.save_freq = config.save_freq
self.print_freq = config.print_freq
self.device = device
self.epoch = 0
def __init__(self, model, optimizer, device, config):
print('Pseudo-Label-v1 2013 with iteration pseudo labels')
self.model = model
self.optimizer = optimizer
self.ce_loss = torch.nn.CrossEntropyLoss(ignore_index=NO_LABEL)
self.save_dir = '{}_{}-{}_{}'.format(
config.arch, config.dataset, config.num_labels,
datetime.datetime.now().strftime("%Y-%m-%d-%H-%M"))
self.save_dir = os.path.join(config.save_dir, self.save_dir)
self.usp_weight = config.usp_weight
#self.rampup = pseudo_rampup(config.t1, config.t2)
self.rampup = exp_rampup(config.weight_rampup)
self.save_freq = config.save_freq
self.print_freq = config.print_freq
self.device = device
self.epoch = 0
def __init__(self, model, optimizer, device, config):
print('Tempens-v1 with iteration pseudo labels')
self.model = model
self.optimizer = optimizer
self.ce_loss = torch.nn.CrossEntropyLoss(ignore_index=NO_LABEL)
self.mse_loss = mse_with_softmax # F.mse_loss
self.save_dir = '{}_{}-{}_{}'.format(
config.arch, config.dataset, config.num_labels,
datetime.datetime.now().strftime("%Y-%m-%d-%H-%M"))
self.save_dir = os.path.join(config.save_dir, self.save_dir)
self.usp_weight = config.usp_weight
self.save_freq = config.save_freq
self.print_freq = config.print_freq
self.device = device
self.epoch = 0
self.start_epoch = 0
self.ema_decay = config.ema_decay
self.rampup = exp_rampup(config.rampup_length)
def __init__(self, model, ema_model, optimizer, device, config):
print("MixMatch")
self.model = model
self.ema_model = ema_model
self.optimizer = optimizer
self.save_dir = '{}-{}_{}-{}_{}'.format(
config.arch, config.model, config.dataset, config.num_labels,
datetime.datetime.now().strftime("%Y-%m-%d-%H-%M"))
self.save_dir = os.path.join(config.save_dir, self.save_dir)
self.cons_weight = config.usp_weight
self.ema_decay = config.ema_decay
self.rampup = exp_rampup(config.weight_rampup)
self.save_freq = config.save_freq
self.print_freq = config.print_freq
self.device = device
self.global_step = 0
self.epoch = 0
self.alpha = config.mixup_alpha
self.temp = 0.5 # temperature for sharpening
def __init__(self, model, ema_model, optimizer, device, config):
print("FixMatch")
self.model = model
self.ema_model = ema_model
self.optimizer = optimizer
self.lce_loss = torch.nn.CrossEntropyLoss(ignore_index=NO_LABEL)
self.uce_loss = torch.nn.CrossEntropyLoss(reduction='none')
self.save_dir = '{}-{}_{}-{}_{}'.format(
config.arch, config.model, config.dataset, config.num_labels,
datetime.datetime.now().strftime("%Y-%m-%d-%H-%M"))
self.save_dir = os.path.join(config.save_dir, self.save_dir)
self.usp_weight = config.usp_weight
self.threshold = config.threshold
self.ema_decay = config.ema_decay
self.rampup = exp_rampup(config.weight_rampup)
self.save_freq = config.save_freq
self.print_freq = config.print_freq
self.device = device
self.global_step = 0
self.epoch = 0
def __init__(self, model, ema_model, optimizer, device, config):
print("ICT-v2")
self.model = model
self.ema_model = ema_model
self.optimizer = optimizer
self.ce_loss = torch.nn.CrossEntropyLoss(ignore_index=NO_LABEL)
self.mixup_loss = mixup_ce_loss_with_softmax #mixup_mse_loss_with_softmax
self.save_dir = '{}-{}_{}-{}_{}'.format(config.arch, config.model,
config.dataset, config.num_labels,
datetime.datetime.now().strftime("%Y-%m-%d-%H-%M"))
self.save_dir = os.path.join(config.save_dir, self.save_dir)
self.global_step = 0
self.epoch = 0
self.alpha = config.mixup_alpha
self.usp_weight = config.usp_weight
self.ema_decay = config.ema_decay
self.rampup = exp_rampup(config.weight_rampup)
self.device = device
self.save_freq = config.save_freq
self.print_freq = config.print_freq
def __init__(self, model, optimizer, device, config):
print('MixUp-Pseudo-Label-v2 with {} epoch pseudo labels'.format(
'soft' if config.soft else 'hard'))
self.model = model
self.optimizer = optimizer
self.ce_loss = torch.nn.CrossEntropyLoss(ignore_index=NO_LABEL)
self.save_dir = '{}-{}_{}-{}_{}'.format(
config.arch, config.model, config.dataset, config.num_labels,
datetime.datetime.now().strftime("%Y-%m-%d-%H-%M"))
self.save_dir = os.path.join(config.save_dir, self.save_dir)
self.alpha = config.mixup_alpha
self.usp_weight = config.usp_weight
#self.rampup = pseudo_rampup(config.t1, config.t2)
self.rampup = exp_rampup(config.weight_rampup)
self.save_freq = config.save_freq
self.print_freq = config.print_freq
self.device = device
self.epoch = 0
self.soft = config.soft
self.mixup_loss = mixup_ce_loss_with_softmax #mixup_mse_loss_with_softmax
if not self.soft: self.mixup_loss = mixup_ce_loss_hard
