def run_cv_batch(cv_configs):
for job_settings in cv_configs:
results_file = job_settings['results']
data_file = job_settings['data']
if os.path.exists(results_file):
print 'Warning: results file %s already exists; aborting' % results_file
continue
if Condorizable.is_locked(results_file):
print 'WARNING: Results file %s is locked; another job may be writing to this file' % results_file
continue
if not os.path.exists(data_file):
print 'WARNING: arff file %s does not exist; aborting' % data_file
continue
if Condorizable.is_locked(data_file):
print 'WARNING: data file %s is locked; another job may be writing to this file' % data_file
continue
CrossValidationTask(kw=job_settings)
def run_cv_batch(cv_configs):
for job_settings in cv_configs:
results_file = job_settings['results']
data_file = job_settings['data']
if os.path.exists(results_file):
print 'Warning: results file %s already exists; aborting' % results_file
continue
if Condorizable.is_locked(results_file):
print 'WARNING: Results file %s is locked; another job may be writing to this file' % results_file
continue
if not os.path.exists(data_file):
print 'WARNING: arff file %s does not exist; aborting' % data_file
continue
if Condorizable.is_locked(data_file):
print 'WARNING: data file %s is locked; another job may be writing to this file' % data_file
continue
CrossValidationTask(kw=job_settings)
def run_sam_batch(vem_configs):
"""
Runs SAM on every experimental configuration defined by 'config'. Jobs that have already been run or are
current running (i.e. for which the model file already exists, or for which a lock file exists) will be skipped.
"""
for job_settings in vem_configs:
model_file = job_settings['model']
if os.path.exists(model_file):
log.warning('Model %s already exists; skipping' % os.path.basename(model_file))
continue
if Condorizable.is_locked(model_file):
log.warning('Model %s is locked; check that another job isn''t writing to this path' %\
os.path.basename(model_file))
continue
VEMTask(kw=job_settings)
def run_sam_batch(vem_configs):
"""
Runs SAM on every experimental configuration defined by 'config'. Jobs that have already been run or are
current running (i.e. for which the model file already exists, or for which a lock file exists) will be skipped.
"""
for job_settings in vem_configs:
model_file = job_settings['model']
if os.path.exists(model_file):
log.warning('Model %s already exists; skipping' %
os.path.basename(model_file))
continue
if Condorizable.is_locked(model_file):
log.warning('Model %s is locked; check that another job isn''t writing to this path' %\
os.path.basename(model_file))
continue
VEMTask(kw=job_settings)
