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update codes

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D-X-Y
2019-02-01 04:03:35 +11:00
parent 3f9b54d99e
commit 65d9c1c57f
11 changed files with 103 additions and 55 deletions
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14
exps-cnn/train_base.py
View File

@@ -54,15 +54,15 @@ def main():
if not os.path.isdir(args.save_path):
os.makedirs(args.save_path)
log = open(os.path.join(args.save_path, 'log-seed-{:}.txt'.format(args.manualSeed)), 'w')
print_log('save path : {}'.format(args.save_path), log)
print_log('Save Path : {:}'.format(args.save_path), log)
state = {k: v for k, v in args._get_kwargs()}
print_log(state, log)
print_log("Random Seed: {}".format(args.manualSeed), log)
print_log("Python version : {}".format(sys.version.replace('\n', ' ')), log)
print_log("Torch version : {}".format(torch.__version__), log)
print_log("CUDA version : {}".format(torch.version.cuda), log)
print_log("cuDNN version : {}".format(cudnn.version()), log)
print_log("Num of GPUs : {}".format(torch.cuda.device_count()), log)
print_log("Random Seed : {:}".format(args.manualSeed), log)
print_log("Python version : {:}".format(sys.version.replace('\n', ' ')), log)
print_log("Torch version : {:}".format(torch.__version__), log)
print_log("CUDA version : {:}".format(torch.version.cuda), log)
print_log("cuDNN version : {:}".format(cudnn.version()), log)
print_log("Num of GPUs : {:}".format(torch.cuda.device_count()), log)
args.dataset = args.dataset.lower()
config = load_config(args.model_config)

6
exps-cnn/train_utils.py
View File

@@ -21,7 +21,7 @@ def obtain_best(accuracies):
def main_procedure(config, dataset, data_path, args, genotype, init_channels, layers, log):
train_data, test_data, class_num = get_datasets(dataset, data_path, args.cutout)
train_data, test_data, class_num = get_datasets(dataset, data_path, config.cutout)
print_log('-------------------------------------- main-procedure', log)
print_log('config : {:}'.format(config), log)
@@ -39,9 +39,9 @@ def main_procedure(config, dataset, data_path, args, genotype, init_channels, la
print_log('genotype : {:}'.format(genotype), log)
print_log('args : {:}'.format(args), log)
print_log('Train-Dataset : {:}'.format(train_data), log)
print_log('Train-Trans : {:}'.format(train_transform), log)
print_log('Train-Trans : {:}'.format(train_data.transform), log)
print_log('Test--Dataset : {:}'.format(test_data ), log)
print_log('Test--Trans : {:}'.format(test_transform ), log)
print_log('Test--Trans : {:}'.format(test_data.transform ), log)
train_loader = torch.utils.data.DataLoader(train_data, batch_size=config.batch_size, shuffle=True,

4
exps-cnn/train_utils_imagenet.py
View File

@@ -62,7 +62,7 @@ def main_procedure_imagenet(config, data_path, args, genotype, init_channels, la
total_param, aux_param = count_parameters_in_MB(basemodel), count_parameters_in_MB(basemodel.auxiliary_param())
print_log('Network =>\n{:}'.format(basemodel), log)
#print_FLOPs(basemodel, (1,3,224,224), [print_log, log])
print_FLOPs(basemodel, (1,3,224,224), [print_log, log])
print_log('Parameters : {:} - {:} = {:.3f} MB'.format(total_param, aux_param, total_param - aux_param), log)
print_log('config : {:}'.format(config), log)
print_log('genotype : {:}'.format(genotype), log)
@@ -75,7 +75,7 @@ def main_procedure_imagenet(config, data_path, args, genotype, init_channels, la
criterion_smooth = CrossEntropyLabelSmooth(class_num, config.label_smooth).cuda()
optimizer = torch.optim.SGD(model.parameters(), config.LR, momentum=config.momentum, weight_decay=config.decay, nestero=True)
optimizer = torch.optim.SGD(model.parameters(), config.LR, momentum=config.momentum, weight_decay=config.decay, nesterov=True)
if config.type == 'cosine':
scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, float(config.epochs))
elif config.type == 'steplr':