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