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Final check

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jack-willturner
2020-06-03 17:10:23 +01:00
parent 656e75cba8
commit 6fbaee7a6d
4 changed files with 30 additions and 26 deletions
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16
process_results.py
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@@ -63,25 +63,25 @@ for n_samples in [10, 100]:
full_scores = torch.load(filename)
if dataset == 'CIFAR-10 (test)':
time = median(full_scores['times'])
dataset_top1s['Search time (s)'] = time
time = f"{time:.2f}"
accs = []
for n in range(args.n_runs):
acc = full_scores[acc_type][n]
accs.append(acc)
dataset_top1s[dataset] = accs
cifar10_val = f"{mean(dataset_top1s['CIFAR-10 (val)']):.2f} $\pm$ {std(dataset_top1s['CIFAR-10 (val)']):.2f}"
cifar10_test = f"{mean(dataset_top1s['CIFAR-10 (test)']):.2f} $\pm$ {std(dataset_top1s['CIFAR-10 (test)']):.2f}"
cifar10_val = f"{mean(dataset_top1s['CIFAR-10 (val)']):.2f} +- {std(dataset_top1s['CIFAR-10 (val)']):.2f}"
cifar10_test = f"{mean(dataset_top1s['CIFAR-10 (test)']):.2f} +- {std(dataset_top1s['CIFAR-10 (test)']):.2f}"
cifar100_val = f"{mean(dataset_top1s['CIFAR-100 (val)']):.2f} $\pm$ {std(dataset_top1s['CIFAR-100 (val)']):.2f}"
cifar100_test = f"{mean(dataset_top1s['CIFAR-100 (test)']):.2f} $\pm$ {std(dataset_top1s['CIFAR-100 (test)']):.2f}"
cifar100_val = f"{mean(dataset_top1s['CIFAR-100 (val)']):.2f} +- {std(dataset_top1s['CIFAR-100 (val)']):.2f}"
cifar100_test = f"{mean(dataset_top1s['CIFAR-100 (test)']):.2f} +- {std(dataset_top1s['CIFAR-100 (test)']):.2f}"
imagenet_val = f"{mean(dataset_top1s['ImageNet16-120 (val)']):.2f} $\pm$ {std(dataset_top1s['ImageNet16-120 (val)']):.2f}"
imagenet_test = f"{mean(dataset_top1s['ImageNet16-120 (test)']):.2f} $\pm$ {std(dataset_top1s['ImageNet16-120 (test)']):.2f}"
imagenet_val = f"{mean(dataset_top1s['ImageNet16-120 (val)']):.2f} +- {std(dataset_top1s['ImageNet16-120 (val)']):.2f}"
imagenet_test = f"{mean(dataset_top1s['ImageNet16-120 (test)']):.2f} +- {std(dataset_top1s['ImageNet16-120 (test)']):.2f}"
df.append([method, time, cifar10_val, cifar10_test, cifar100_val, cifar100_test, imagenet_val, imagenet_test])
df = pd.DataFrame(df, columns=['Method','Search time (s)','CIFAR-10 (val)','CIFAR-10 (test)','CIFAR-100 (val)','CIFAR-100 (test)','ImageNet16-120 (val)','ImageNet16-120 (test)' ])
df.round(2)
print(tabulate.tabulate(df.values,df.columns, tablefmt="pipe"))