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run_multiple_evals.py
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run_multiple_evals.py
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'''run evaluations on multiple models'''
import os
models_to_evaluate = [
# model trained on BC1Song
"UMSS_4s_bc1song",
"unet_4s_bc1song",
# "Sf-Sf_bc1song",
# "Sft-Sft_bc1song",
# "Sf-Sft_bc1song",
# "W-Up_bc1song",
# model trained on BCBQ
"UMSS_4s_bcbq",
"unet_4s_bcbq",
# "Sf-Sf_bcbq",
# "Sft-Sft_bcbq",
# "Sf-Sft_bcbq",
# "W-Up_bcbq",
]
eval_mode='default' # default evaluation
# eval_mode='fast' # fast evaluation
# eval_mode='robustness' # run many unique evaluations for each model, following different types of robustness tests
# eval_mode='robustness_vad' # run many unique evaluations for each model, with vad error tests only
for tag in models_to_evaluate:
if eval_mode=='robustness_vad' :
for i in range(5):
command="python eval_robustness_tests.py --tag '{}' --f0-from-mix --test-set 'CSD' --teststocompute baseline_gtf0 gtf0_strict_error_percent --vadseed {}".format(tag,i)
print(command)
os.system(command)
else:
if eval_mode=='original_paper':
command="python eval.py --tag '{}' --f0-from-mix --test-set 'CSD'".format(tag)
elif eval_mode=='default':
# mf0 extract with Crepe
command="python eval.py --tag '{}' --test-set 'CSD' --show-progress --compute all".format(tag)
# mf0 extract with Cuesta et al. (model 3) model
# command="python eval.py --tag '{}' --f0-from-mix --test-set 'CSD' --show-progress --compute all".format(tag)
elif eval_mode=='fast':
command="python eval.py --tag '{}' --f0-from-mix --test-set 'CSD' --show-progress --compute SI-SDR_mask".format(tag)
elif eval_mode=='robustness':
command="python eval_robustness_tests.py --tag '{}' --f0-from-mix --test-set 'CSD' --teststocompute all".format(tag)
elif eval_mode=='robustness_vad':
command="python eval_robustness_tests.py --tag '{}' --f0-from-mix --test-set 'CSD' --teststocompute baseline_gtf0 gtf0_strict_error_percent --vadseed 0".format(tag)
print(command)
os.system(command)