under the GNU General Public License as published by the Free
Software Foundation, either Version 3 of the License, or (at your option)
any later version, if this derivative work is distributed to a third party.
The copyright for the program is owned by Shandong University.
For commercial projects that require the ability to distribute
the code of this program as part of a program that cannot be
distributed under the GNU General Public License, please contact
[email protected]
to purchase a commercial license.
"""
from thexp import Params
params = Params()
params.device = 'cuda:1'
params.epoch = 5
params.batch_size = 128
params.topk = (1, 4)
params.from_args()
params.root = '/home/share/yanghaozhe/pytorchdataset'
params.dataloader = dict(shuffle=True, batch_size=32, drop_last=True)
params.optim = dict(lr=0.01, weight_decay=0.09, momentum=0.9)
params.choice('dataset', 'mnist', 'fmnist')
params.dataset = 'mnist'
params.bind('dataset', 'mnist', 'arch', 'simple')
params.bind('dataset', 'fmnist', 'arch', 'simple')
params.bind('dataset', 'cifar10', 'arch', 'cnn13')
params.ema = True
class MyParams(Params):
def __init__(self):
super().__init__()
self.batch_size = 50
self.topk = (1, 2, 3, 4)
self.optim = dict(lr=0.009, moment=0.9)
params = MyParams()
print(params)
from thexp import Params
params = Params()
params.choice("dataset", "mnist", "cifar10", "cifar100", "svhn")
params.arange("thresh", 5, 0, 20)
print(params)
# for g in params.grid_search("thresh",range(0,20)):
# for g in g.grid_search("dataset",['cifar10','cifar100','svhn']):
# print(g.dataset,g.thresh)
params.bind('dataset', 'mnist', 'arch', 'simplenet')
params.bind('dataset', 'cifar10', 'arch', 'cnn13')
params.bind('arch', 'simplenet', 'arch_param', dict(feature=128))
params.bind('arch', 'cnn13', 'arch_param', dict(feature=256))
params.dataset = 'cifar10'
print(params.arch)
print(params.arch_param)
params.dataset = 'mnist'