import itertools import gpuscheduler from sparselearning import funcs s = gpuscheduler.Scheduler('/home/tim/data/git/sched/config/') s.update_host_config('home', mem_threshold=2500, util_threshold=30) s.update_host_config('office', mem_threshold=2500, util_threshold=25) s.update_host_config('ari', mem_threshold=2500, util_threshold=25) cmd_mnist = 'OMP_NUM_THREADS=1 python main.py --model {4} --density {5} --seed {3} --prune {0} --growth {1} --redistribution {2} --verbose{6}' cmd_cifar = 'OMP_NUM_THREADS=1 python main.py --model {4} --decay_frequency 30000 --batch-size 128 --data cifar --epochs 250 --density {5} --seed {3} --prune {0} --growth {1} --redistribution {2} --verbose{6}' num_seeds = 20 cmd = cmd_cifar seed_offset = 0 #models_and_densities = [('wrn-16-8', 0.05), ('vgg-d', 0.05), ('alexnet-s', 0.10)] #models_and_densities = [('vgg-d', 0.05), ('alexnet-s', 0.10)] models_and_densities = [('wrn-16-10', 0.05)] #models_and_densities = [('alexnet-s', 0.10)] #models_and_densities = [('lenet300-100', 0.05), ('lenet5', 0.1)] #models_and_densities = [('lenet300-100', 0.05), ('lenet300-100', 0.02), ('lenet300-100', 0.01)] #models_and_densities = [('lenet300-100', 0.05)] jobs = [] for seed in range(num_seeds): for (model, density) in models_and_densities: #for fp16 in [True]: for fp16 in [False]: prune = 'magnitude' growth = 'momentum'
import itertools import gpuscheduler from sparselearning import funcs import argparse parser = argparse.ArgumentParser(description='Compute script.') parser.add_argument('--dry', action='store_true') parser.add_argument('--verbose', action='store_true') args = parser.parse_args() s = gpuscheduler.Scheduler('/home/tim/data/git/sched/config/', verbose=args.verbose) s.update_host_config('home', mem_threshold=1500, util_threshold=30) #s.update_host_config('office', mem_threshold=2500, util_threshold=25) #s.update_host_config('ari', mem_threshold=2500, util_threshold=25) cmd_mnist = 'OMP_NUM_THREADS=1 python main.py --model {4} --density {5} --seed {3} --prune {0} --growth {1} --redistribution {2} --verbose{6}' cmd_cifar = 'OMP_NUM_THREADS=1 python main.py --model {4} --decay_frequency 30000 --batch-size 128 --data cifar --epochs 250 --density {5} --seed {3} --prune {0} --growth {1} --redistribution {2} --verbose --prune-rate 0.2 {6}' num_seeds = 10 cmd = cmd_cifar #cmd = cmd_mnist seed_offset = 0 #models_and_densities = [('lenet300-100', 0.05), ('lenet300-100', 0.02), ('lenet300-100', 0.01)] #models_and_densities = [('vgg-d', 0.05), ('wrn-16-8', 0.05), ('alexnet-s', 0.10), ('alexnet-b', 0.1), ('vgg-c', 0.05), ('vgg-like', 0.03), ('wrn-16-10', 0.05), ('wrn-22-8', 0.05)] #models_and_densities = [('alexnet-s', 0.10), ('vgg-c', 0.05), ('wrn-16-10', 0.05)] #models_and_densities = [('alexnet-b', 0.10), ('vgg-like', 0.03), ('wrn-16-8', 0.05)] #models_and_densities = [('vgg-d', 0.05)] models_and_densities = [('vgg-d', 0.05), ('vgg-c', 0.05), ('vgg-like', 0.03)]
import itertools import gpuscheduler import argparse parser = argparse.ArgumentParser(description='Compute script.') parser.add_argument('--dry', action='store_true') args = parser.parse_args() s = gpuscheduler.Scheduler('/home/tim/git/sched/config/', git_home='/home/tim/git') s.update_host_config('home', mem_threshold=1700, util_threshold=30) s.update_host_config('office', mem_threshold=1700, util_threshold=25) #s.update_host_config('ari', mem_threshold=2500, util_threshold=25) cmd_mnist = 'OMP_NUM_THREADS=1 python main.py --model {4} --density {5} --seed {3} --prune {0} --growth {1} --redistribution {2} --verbose{6}' cmd_cifar = 'OMP_NUM_THREADS=1 python main.py --model {4} --decay_frequency 30000 --batch-size 128 --data cifar --epochs 1 --density {5} --seed {3} --prune {0} --growth {1} --redistribution {2} --verbose --prune-rate 0.2 {6} --bench' num_seeds = 1 cmd = cmd_cifar #cmd = cmd_mnist seed_offset = 0 #models_and_densities = [('lenet300-100', 0.05), ('lenet300-100', 0.02), ('lenet300-100', 0.01)] #models_and_densities = [('vgg-d', 0.05), ('wrn-16-8', 0.05), ('alexnet-s', 0.10), ('alexnet-b', 0.1), ('vgg-c', 0.05), ('vgg-like', 0.03), ('wrn-16-10', 0.05), ('wrn-22-8', 0.05)] #models_and_densities = [('alexnet-s', 0.10), ('vgg-c', 0.05), ('wrn-16-10', 0.05)] #models_and_densities = [('alexnet-b', 0.10), ('vgg-like', 0.03), ('wrn-16-8', 0.05)] models_and_densities = [('vgg-d', 0.05)] #models_and_densities = [('wrn-16-10', 0.05), ('wrn-22-8', 0.05)] #models_and_densities = [('vgg-c', 0.05), ('vgg-like', 0.03)] #models_and_densities = [('alexnet-s', 0.10), ('alexnet-b', 0.1)] #models_and_densities = [('alexnet-s', 0.10)]