iicd/swap-nas
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compare: iicd:aa4b38a0cc14359bbf6b892d0b023c00937862bb
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iicd:main

3 Commits
aead4df707 ... aa4b38a0cc

Author SHA1 Message Date
Mhrooz
aa4b38a0cc fix the index bug in the output 2024-08-26 10:58:20 +02:00
Mhrooz
f72990a675 update .gitignore file and change the correlation config 2024-08-26 10:53:21 +02:00
Mhrooz
ff85bba9cd change 201 acc to more info func 2024-08-26 10:50:54 +02:00
2 changed files with 13 additions and 9 deletions
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3
.gitignore vendored
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@ -1,2 +1,3 @@
__pycache__/ __pycache__/
datasets/ datasets/
swap_results.csv

19
correlation.py
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@ -55,19 +55,22 @@ if __name__ == "__main__":
results = [] results = []
# nasbench_len = 15625
nasbench_len = 15625 nasbench_len = 15625
# for index, i in arch_info.iterrows(): # for index, i in arch_info.iterrows():
for i in range(nasbench_len): for ind in range(nasbench_len):
# print(f'Evaluating network: {index}') # print(f'Evaluating network: {index}')
print(f'Evaluating network: {i}') print(f'Evaluating network: {ind}')
config = api.get_net_config(i, 'cifar10') config = api.get_net_config(ind, 'cifar10')
network = get_cell_based_tiny_net(config) network = get_cell_based_tiny_net(config)
nas_results = api.query_by_index(i, 'cifar10') # nas_results = api.query_by_index(i, 'cifar10')
acc = nas_results[111].get_eval('ori-test') # acc = nas_results[111].get_eval('ori-test')
nas_results = api.get_more_info(ind, 'cifar10', None, hp=200, is_random=False)
acc = nas_results['test-accuracy']
print(type(network)) # print(type(network))
start_time = time.time() start_time = time.time()
# network = Network(3, 10, 1, eval(i.genotype)) # network = Network(3, 10, 1, eval(i.genotype))
@ -93,13 +96,13 @@ if __name__ == "__main__":
print(f'Average SWAP score: {np.mean(swap_score)}') print(f'Average SWAP score: {np.mean(swap_score)}')
print(f'Elapsed time: {end_time - start_time:.2f} seconds') print(f'Elapsed time: {end_time - start_time:.2f} seconds')
results.append([np.mean(swap_score), acc, i]) results.append([np.mean(swap_score), acc, ind])
results = pd.DataFrame(results, columns=['swap_score', 'valid_acc', 'index']) results = pd.DataFrame(results, columns=['swap_score', 'valid_acc', 'index'])
results.to_csv('output/swap_results.csv', float_format='%.4f', index=False)
print() print()
print(f'Spearman\'s Correlation Coefficient: {stats.spearmanr(results.swap_score, results.valid_acc)[0]}') print(f'Spearman\'s Correlation Coefficient: {stats.spearmanr(results.swap_score, results.valid_acc)[0]}')
results.to_csv('swap_results.csv', float_format='%.4f', index=False)