зеркало из https://github.com/microsoft/archai.git
Finished processing local search results on natsbench tss.
This commit is contained in:
Debadeepta Dey
Gustavo Rosa
Родитель
71b96dadd2
Коммит
d06f4ec922
13
.amltignore
13
.amltignore
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@ -1,10 +1,5 @@
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# Copyright (c) Microsoft Corporation.
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# Licensed under the MIT license.
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# Folders to be ignored when using AMLT
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devices/
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dockers/
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docs/
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scripts/
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tests/
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tools/
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tools/
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archived/
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dockers/
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docs/
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@ -803,8 +803,9 @@
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"request": "launch",
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"program": "${cwd}/scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py",
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"console": "integratedTerminal",
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"args": ["--results-dir", "F:\\archaiphilly\\phillytools\\ls_far_ftt0.6_max300_ratio2.0_fixedseeds",
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"--out-dir", "F:\\archai_experiment_reports"]
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"args": ["--results-dir", "F:\\archaiphilly\\phillytools\\ls_far_c100_ftt0.3_max300_ratio4.0_fixedseeds",
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"--out-dir", "F:\\archai_experiment_reports", "--natsbench_loc", "C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple",
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"--dataset", "cifar100"]
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},
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{
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"name": "CurrentFile",
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@ -44,7 +44,7 @@ dataset: {} # default dataset settings comes from __include__ on the top
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nas:
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search:
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use_fear: False
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use_fear: True
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max_num_models: 300
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ratio_fastest_duration: 1.2
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natsbench:
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@ -62,9 +62,9 @@ nas:
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aug: '' # additional augmentations to use
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cutout: 0 # cutout length, use cutout augmentation when > 0
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load_train: True # load train split of dataset
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train_batch: 1024
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train_batch: 256
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freeze_loader:
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train_batch: 1024 # batch size for freeze training.
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train_batch: 512 # batch size for freeze training.
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train_workers: 4 # if null then gpu_count*4
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test_workers: '_copy: ../train_workers' # if null then 4
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load_test: False # load test split of dataset
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@ -84,7 +84,7 @@ nas:
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grad_clip: 5.0 # grads above this value is clipped
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logger_freq: 1000 # after every N updates dump loss and other metrics in logger
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title: 'arch_train'
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epochs: 2
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epochs: 200
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batch_chunks: 1 # split batch into these many chunks and accumulate gradients so we can support GPUs with lower RAM
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# additional vals for the derived class
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plotsdir: '' #empty string means no plots, other wise plots are generated for each epoch in this dir
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@ -54,7 +54,7 @@
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@REM python scripts/reports/analysis_freeze_natsbench_space_new.py --results-dir D:\\archaiphilly\\phillytools\\ft_fb256_ftlr0.1_fte15_ct256_ftt0.6 --out-dir D:\\archai_experiment_reports
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@REM python scripts/reports/analysis_freeze_natsbench_space_new.py --results-dir D:\\archaiphilly\\phillytools\\ft_fb1024_ftlr1.5_fte5_ct256_ftt0.6_scu --out-dir D:\\archai_experiment_reports
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python scripts/reports/analysis_freeze_natsbench_space_new.py --results-dir D:\\archaiphilly\\phillytools\\ft_fb1024_ftlr1.5_fte10_ct256_ftt0.6_scu --out-dir D:\\archai_experiment_reports
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@REM python scripts/reports/analysis_freeze_natsbench_space_new.py --results-dir D:\\archaiphilly\\phillytools\\ft_fb1024_ftlr1.5_fte10_ct256_ftt0.6_scu --out-dir D:\\archai_experiment_reports
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@REM python scripts/reports/analysis_freeze_natsbench_space_new.py --results-dir D:\\archaiphilly\\phillytools\\ft_fb1024_ftlr0.1_fte5_ct256_ftt0.6_scu --out-dir D:\\archai_experiment_reports
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@REM python scripts/reports/analysis_freeze_natsbench_space_new.py --results-dir D:\\archaiphilly\\phillytools\\ft_fb1024_ftlr0.1_fte10_ct256_ftt0.6_scu --out-dir D:\\archai_experiment_reports
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@ -354,3 +354,34 @@ python scripts/reports/analysis_freeze_natsbench_space.py --results-dir D:\\arch
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@REM python scripts/reports/analysis_regular_natsbench_space.py --results-dir D:\\archaiphilly\\phillytools\\nb101_reg_b256_e30 --out-dir D:\\archai_experiment_reports
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@REM python scripts/reports/analysis_regular_natsbench_space.py --results-dir D:\\archaiphilly\\phillytools\\nb101_reg_b256_e108 --out-dir D:\\archai_experiment_reports
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@REM python scripts/reports/analysis_regular_natsbench_space.py --results-dir D:\\archaiphilly\\phillytools\\nb101_reg_b256_e108_rms --out-dir D:\\archai_experiment_reports
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@REM Local Search
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_far_ftt0.6_max300_ratio2.0_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar10
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_far_ftt0.6_max300_ratio2.0_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar10
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_far_ftt0.6_max300_ratio2.0_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar10
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_max300_b1024_e02_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar10
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_max300_b1024_e20_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar10
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_max300_b1024_e30_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar10
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_max300_b1024_e40_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar10
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_max300_b1024_e50_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar10
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_far_c100_ftt0.3_max300_ratio2.0_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar100
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_far_c100_ftt0.3_max300_ratio4.0_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar100
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_far_c100_ftt0.3_max300_ratio8.0_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar100
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_c100_max300_b1024_e02_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar100
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_c100_max300_b1024_e20_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar100
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_c100_max300_b1024_e30_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar100
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_c100_max300_b1024_e40_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar100
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_c100_max300_b1024_e50_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset cifar100
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_far_i16_ftt0.2_max300_ratio2.0_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset ImageNet16-120
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_far_i16_ftt0.2_max300_ratio4.0_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset ImageNet16-120
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_far_i16_ftt0.2_max300_ratio8.0_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset ImageNet16-120
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_i16_max300_b1024_e02_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset ImageNet16-120
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_i16_max300_b1024_e20_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset ImageNet16-120
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_i16_max300_b1024_e30_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset ImageNet16-120
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_i16_max300_b1024_e40_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset ImageNet16-120
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@REM python scripts/reports/fear_analysis/analysis_local_search_natsbench_tss.py --results-dir F:\\archaiphilly\\phillytools\\ls_reg_i16_max300_b1024_e50_fixedseeds --out-dir F:\\archai_experiment_reports --natsbench_loc C:\\Users\\dedey\\dataroot\\natsbench\\NATS-tss-v1_0-3ffb9-simple --dataset ImageNet16-120
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@ -30,7 +30,7 @@ import multiprocessing
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from multiprocessing import Pool
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from archai.common import utils
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from archai.common.ordereddict_logger import OrderedDictLogger
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from archai.algos.natsbench.natsbench_utils import create_natsbench_tss_api
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from archai.common.analysis_utils import epoch_nodes, parse_a_job, fix_yaml, remove_seed_part, group_multi_runs, collect_epoch_nodes, EpochStats, FoldStats, stat2str, get_epoch_stats, get_summary_text, get_details_text, plot_epochs, write_report
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import re
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@ -43,6 +43,10 @@ def main():
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help='folder with experiment results from pt')
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parser.add_argument('--out-dir', '-o', type=str, default=r'~/logdir/reports',
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help='folder to output reports')
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parser.add_argument('--natsbench_loc', '-n', type=str,
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help='location of natsbench')
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parser.add_argument('--dataset', type=str,
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help='dataset name')
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args, extra_args = parser.parse_known_args()
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# root dir where all results are stored
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@ -77,6 +81,11 @@ def main():
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logs[key] = val[0]
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confs[key] = val[1]
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# create the natsbench api
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api = create_natsbench_tss_api(args.natsbench_loc)
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ds_name = args.dataset
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raw_data = {}
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@ -84,10 +93,15 @@ def main():
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# Get total duration of the run
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# which is the sum of all conditional and freeze
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# trainings over all architectures
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# or all regular runs if it is shortened regular evaluation
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duration = 0.0
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arch_ids_touched = []
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# best test accuracy as function of time
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best_train_till_now = -ma.inf
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best_test_duration_storage = []
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archs_touched_counter = 0
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for skey in logs[key].keys():
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if 'conditional' in skey or 'freeze' in skey:
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@ -98,11 +112,28 @@ def main():
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for ekey in logs[key][skey][train_key]['epochs'].keys():
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eduration = logs[key][skey][train_key]['epochs'][ekey]['train']['duration']
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duration += eduration
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train_acc = logs[key][skey][train_key]['best_train']['top1']
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if train_acc >= best_train_till_now:
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best_train_till_now = train_acc
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arch_id = int(skey.split('_')[-1])
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info = api.get_more_info(arch_id, ds_name, hp=200, is_random=False)
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test_acc = info['test-accuracy']
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best_test_duration_storage.append((duration, test_acc, train_acc))
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elif 'regular_training' in skey:
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for ekey in logs[key][skey]['arch_train']['epochs'].keys():
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eduration = logs[key][skey]['arch_train']['epochs'][ekey]['train']['duration']
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duration += eduration
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train_acc = logs[key][skey]['arch_train']['best_train']['top1']
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if train_acc >= best_train_till_now:
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best_train_till_now = train_acc
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arch_id = int(skey.split('_')[-1])
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info = api.get_more_info(arch_id, ds_name, hp=200, is_random=False)
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test_acc = info['test-accuracy']
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best_test_duration_storage.append((duration, test_acc, train_acc))
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if 'conditional' in skey or 'freeze' in skey or 'regular_training' in skey:
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arch_id = int(skey.split('_')[-1])
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if arch_id not in arch_ids_touched:
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@ -111,9 +142,9 @@ def main():
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# find the test error of the best local minima (by train error)
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best_test = logs[key]['best_minimum'][2]
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raw_data[key] = (duration, best_test)
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best_test_local = logs[key]['best_minimum'][2]
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best_test = best_test_duration_storage[-1][1]
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raw_data[key] = (duration, best_test, best_test_duration_storage)
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run_durations = [raw_data[key][0] for key in raw_data.keys()]
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max_accs = [raw_data[key][1] for key in raw_data.keys()]
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@ -124,11 +155,15 @@ def main():
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avg_max_acc = statistics.mean(max_accs)
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stderr_max_acc = sem(np.array(max_accs))
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trajs = [raw_data[x][2] for x in raw_data.keys()]
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data_to_save = {}
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data_to_save['avg_duration'] = avg_duration
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data_to_save['stderr_duration'] = stderr_duration
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data_to_save['avg_max_acc'] = avg_max_acc
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data_to_save['stderr_max_acc'] = stderr_max_acc
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data_to_save['trajs'] = trajs
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savename = os.path.join(out_dir, 'raw_data.yaml')
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with open(savename, 'w') as f:
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@ -6,11 +6,54 @@ natsbench_cifar10:
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fastarchrank:
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ls_far_ftt0.6_max300_ratio2.0_fixedseeds: 'ls_far_ftt0.6_max300_ratio2.0_fixedseeds'
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ls_far_ftt0.6_max300_ratio4.0_fixedseeds: 'ls_far_ftt0.6_max300_ratio4.0_fixedseeds'
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ls_far_ftt0.6_max300_ratio8.0_fixedseeds: 'ls_far_ftt0.6_max300_ratio8.0_fixedseeds'
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regular:
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ls_reg_max300_b1024_e02_fixedseeds: 'ls_reg_max300_b1024_e02_fixedseeds'
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ls_reg_max300_b1024_e20_fixedseeds: 'ls_reg_max300_b1024_e20_fixedseeds'
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ls_reg_max300_b1024_e30_fixedseeds: 'ls_reg_max300_b1024_e30_fixedseeds'
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ls_reg_max300_b1024_e40_fixedseeds: 'ls_reg_max300_b1024_e40_fixedseeds'
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ls_reg_max300_b1024_e50_fixedseeds: 'ls_reg_max300_b1024_e50_fixedseeds'
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colors:
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fastarchrank: 'green'
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||||
regular: 'red'
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natsbench_cifar100:
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fastarchrank:
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ls_far_c100_ftt0.3_max300_ratio2.0_fixedseeds: 'ls_far_c100_ftt0.3_max300_ratio2.0_fixedseeds'
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ls_far_c100_ftt0.3_max300_ratio4.0_fixedseeds: 'ls_far_c100_ftt0.3_max300_ratio4.0_fixedseeds'
|
||||
ls_far_c100_ftt0.3_max300_ratio8.0_fixedseeds: 'ls_far_c100_ftt0.3_max300_ratio8.0_fixedseeds'
|
||||
|
||||
regular:
|
||||
ls_reg_c100_max300_b1024_e02_fixedseeds: 'ls_reg_c100_max300_b1024_e02_fixedseeds'
|
||||
ls_reg_c100_max300_b1024_e20_fixedseeds: 'ls_reg_c100_max300_b1024_e20_fixedseeds'
|
||||
ls_reg_c100_max300_b1024_e30_fixedseeds: 'ls_reg_c100_max300_b1024_e30_fixedseeds'
|
||||
ls_reg_c100_max300_b1024_e40_fixedseeds: 'ls_reg_c100_max300_b1024_e40_fixedseeds'
|
||||
ls_reg_c100_max300_b1024_e50_fixedseeds: 'ls_reg_c100_max300_b1024_e50_fixedseeds'
|
||||
|
||||
colors:
|
||||
fastarchrank: 'green'
|
||||
regular: 'red'
|
||||
|
||||
|
||||
natsbench_imagenet16-120:
|
||||
|
||||
fastarchrank:
|
||||
ls_far_i16_ftt0.2_max300_ratio2.0_fixedseeds: ls_far_i16_ftt0.2_max300_ratio2.0_fixedseeds
|
||||
ls_far_i16_ftt0.2_max300_ratio4.0_fixedseeds: ls_far_i16_ftt0.2_max300_ratio4.0_fixedseeds
|
||||
ls_far_i16_ftt0.2_max300_ratio8.0_fixedseeds: ls_far_i16_ftt0.2_max300_ratio8.0_fixedseeds
|
||||
|
||||
regular:
|
||||
ls_reg_i16_max300_b1024_e02_fixedseeds: ls_reg_i16_max300_b1024_e02_fixedseeds
|
||||
ls_reg_i16_max300_b1024_e20_fixedseeds: ls_reg_i16_max300_b1024_e20_fixedseeds
|
||||
ls_reg_i16_max300_b1024_e30_fixedseeds: ls_reg_i16_max300_b1024_e30_fixedseeds
|
||||
ls_reg_i16_max300_b1024_e40_fixedseeds: ls_reg_i16_max300_b1024_e40_fixedseeds
|
||||
ls_reg_i16_max300_b1024_e50_fixedseeds: ls_reg_i16_max300_b1024_e50_fixedseeds
|
||||
|
||||
colors:
|
||||
fastarchrank: 'green'
|
||||
regular: 'red'
|
||||
|
|
|
|||
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