def runscript():
parser = argparse.ArgumentParser()
for arg in arguments:
parser.add_argument(*arg['flags'], **arg['parameters'])
run_args = parser.parse_args()
lab = Laboratory(run_args.model_type, run_args.config_path,
run_args.lab_path)
expt = Experiment(lab, reproduce=run_args.reproduce, force=run_args.force)
n_runs_per_submit = expt.config.get('runspersub', 1)
subrun = 1
while True:
print('nruns: {0} nruns_per_submit: {1} subrun: {2}'
''.format(expt.n_runs, n_runs_per_submit, subrun))
expt.setup()
expt.run()
expt.archive()
# Finished runs
if expt.n_runs == 0:
break
# Need to manually increment the run counter if still looping
if n_runs_per_submit > 1 and subrun < n_runs_per_submit:
expt.counter += 1
# Re-initialize manifest: important to clear out restart manifest
# note no attempt to preserve reproduce flag, it makes no sense
# to on subsequent runs
expt.manifest = Manifest(expt.config.get('manifest', {}),
reproduce=False)
expt.set_output_paths()
# Does not make sense to reproduce a multiple run.
# Take care of this with argument processing?
expt.reproduce = False
else:
break
subrun += 1
if expt.n_runs > 0:
expt.resubmit()
def runscript():
parser = argparse.ArgumentParser()
for arg in arguments:
parser.add_argument(*arg['flags'], **arg['parameters'])
run_args = parser.parse_args()
lab = Laboratory(run_args.model_type, run_args.config_path,
run_args.lab_path)
expt = Experiment(lab)
expt.setup()
expt.run()
expt.archive()
if expt.n_runs > 0:
expt.resubmit()
def runscript():
parser = argparse.ArgumentParser()
for arg in arguments:
parser.add_argument(*arg['flags'], **arg['parameters'])
run_args = parser.parse_args()
lab = Laboratory(run_args.model_type, run_args.config_path,
run_args.lab_path)
expt = Experiment(lab)
expt.setup()
expt.run()
expt.archive()
if expt.n_runs > 0:
expt.resubmit()
def runscript():
parser = argparse.ArgumentParser()
for arg in arguments:
parser.add_argument(*arg['flags'], **arg['parameters'])
run_args = parser.parse_args()
lab = Laboratory(run_args.model_type, run_args.config_path,
run_args.lab_path)
expt = Experiment(lab, reproduce=run_args.reproduce)
n_runs_per_submit = expt.config.get('runspersub', 1)
subrun = 1
while True:
print('nruns: {0} nruns_per_submit: {1} subrun: {2}'
''.format(expt.n_runs, n_runs_per_submit, subrun))
expt.setup()
expt.run()
expt.archive()
# Finished runs
if expt.n_runs == 0:
break
# Need to manually increment the run counter if still looping
if n_runs_per_submit > 1 and subrun < n_runs_per_submit:
expt.counter += 1
expt.set_output_paths()
# Does not make sense to reproduce a multiple run. Take care of
# this with argument processing?
expt.reproduce = False
else:
break
subrun += 1
if expt.n_runs > 0:
expt.resubmit()
def runscript():
parser = argparse.ArgumentParser()
for arg in arguments:
parser.add_argument(*arg['flags'], **arg['parameters'])
run_args = parser.parse_args()
lab = Laboratory(run_args.model_type, run_args.config_path,
run_args.lab_path)
expt = Experiment(lab)
expt.setup()
n_runs_per_submit = expt.config.get('runspersub', 1)
subrun = 1
while subrun <= n_runs_per_submit and expt.n_runs > 0:
print('nruns: {0} nruns_per_submit: {1} subrun: {2}'
''.format(expt.n_runs, n_runs_per_submit, subrun))
expt.setup()
expt.run()
expt.archive()
# Need to manually increment the run counter if still looping
if n_runs_per_submit > 1 and subrun < n_runs_per_submit:
expt.counter += 1
expt.set_output_paths()
subrun += 1
if expt.n_runs > 0:
expt.resubmit()
def runscript():
parser = argparse.ArgumentParser()
for arg in arguments:
parser.add_argument(*arg['flags'], **arg['parameters'])
run_args = parser.parse_args()
lab = Laboratory(run_args.model_type, run_args.config_path,
run_args.lab_path)
expt = Experiment(lab)
expt.setup()
n_runs_per_submit = expt.config.get('runspersub', 1)
subrun = 1
while subrun <= n_runs_per_submit and expt.n_runs > 0:
print('nruns: {} nruns_per_submit: {} subrun: {}'
''.format(expt.n_runs, n_runs_per_submit, subrun))
expt.setup()
expt.run()
expt.archive()
# Need to manually increment the run counter if still looping
if n_runs_per_submit > 1 and subrun < n_runs_per_submit:
expt.counter += 1
expt.set_output_paths()
subrun += 1
if expt.n_runs > 0:
expt.resubmit()
def runcmd(model_type, config_path, lab_path):
lab = Laboratory(model_type, config_path, lab_path)
expt = Experiment(lab)
expt.archive()