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)]