本文整理匯總了Python中utils.AttributeDict.class_cost_x方法的典型用法代碼示例。如果您正苦於以下問題：Python AttributeDict.class_cost_x方法的具體用法？Python AttributeDict.class_cost_x怎麽用？Python AttributeDict.class_cost_x使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類utils.AttributeDict的用法示例。
在下文中一共展示了AttributeDict.class_cost_x方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: AttributeDict
# 需要導入模塊: from utils import AttributeDict [as 別名]
# 或者: from utils.AttributeDict import class_cost_x [as 別名]
from utils import AttributeDict
from tagger_exp import TaggerExperiment
p = AttributeDict()
p.encoder_proj = (2000, 1000, 500)
p.input_noise = 0.2
p.class_cost_x = 0
p.zhat_init_value = 0.26 # mean of the input data.
p.n_iterations = 3
p.n_groups = 4
p.lr = 0.0004
p.seed = 10
p.num_epochs = 100
p.batch_size = 100
p.valid_batch_size = 100
p.dataset = 'shapes50k20x20'
p.input_type = 'binary'
p.save_to = 'shapes50k20x20'
if __name__ == '__main__':
experiment = TaggerExperiment(p)
experiment.train()
示例2: AttributeDict
# 需要導入模塊: from utils import AttributeDict [as 別名]
# 或者: from utils.AttributeDict import class_cost_x [as 別名]
import sys
from utils import AttributeDict
from tagger_exp import TaggerExperiment
p = AttributeDict()
p.encoder_proj = (3000, 2000, 1000)
p.input_noise = 0.2
p.class_cost_x = 0.
p.zhat_init_value = 0.5
p.n_iterations = 3
p.n_groups = 4
p.lr = 0.001
p.labeled_samples = 1000
p.save_freq = 50
p.seed = 1
p.num_epochs = 150
p.batch_size = 100
p.valid_batch_size = 100
p.objects_per_sample = 2
p.dataset = 'freq20-2mnist'
p.input_type = 'continuous'
if __name__ == '__main__':
if len(sys.argv) == 2 and sys.argv[1] == '--pretrain':
p.save_to = 'freq20-2mnist-pretraining'
experiment = TaggerExperiment(p)
experiment.train()
elif len(sys.argv) == 3 and sys.argv[1] == '--continue':