def manage_forms(request):
if not request.user.is_staff:
return HttpResponseForbidden('admin access required')
return render(request, 'manage_forms.html', {
'formlist': json.dumps(util.get_latest()),
})
def form_pull(request, study_id):
study_id = int(study_id)
study = Study.objects.get(id=study_id)
errors = util.pull_latest(study.identifier)
study_metadata = util.map_reduce(util.get_latest(), lambda s: [(s['id'], s)], lambda v: v[0])[study_id]['events']
payload = {'study_data': study_metadata, 'errors': errors}
return HttpResponse(json.dumps(payload), 'text/json')
def run_training(self):
self.log_path = os.path.join(self.logs_path, 'log.txt')
binary_path = os.path.join(self.caffe_root, 'build/tools/caffe')
# Check if there are any available snapshots and pick the
# latest one for training continuation
latest_snapshot = get_latest(self.snapshots_path, '*solverstate')
if self.custom_command:
training_string = 'srun --gres=gpu:1 {} 2>> {}'.format(
self.custom_command, self.log_path)
elif latest_snapshot:
latest_snapshot = os.path.join(self.snapshots_path,
latest_snapshot)
training_string = ('srun --gres=gpu:1 '
'{} train '
'--solver={} '
'--snapshot={} '
'--gpu={} 2>> {}').format(
binary_path, self.solver_path,
latest_snapshot, GPU_ID, self.log_path)
else:
if self.experiment['weights']:
weights_string = '--weights=' + self.experiment['weights']
else:
weights_string = ''
training_string = ('srun --gres=gpu:1 '
'{} train '
'--solver={} {} '
'--gpu={} 2>> {}').format(
binary_path, self.solver_path,
weights_string, GPU_ID, self.log_path)
file(os.path.join(self.path, 'training_string.txt'),
'w').write(training_string)
self.training_process = subprocess.Popen(training_string,
stdin=subprocess.PIPE,
shell=True,
preexec_fn=os.setsid)
def run_training(self):
self.log_path = os.path.join(self.logs_path, 'log.txt')
binary_path = os.path.join(self.caffe_root, 'build/tools/caffe')
# Check if there are any available snapshots and pick the
# latest one for training continuation
latest_snapshot = get_latest(self.snapshots_path, '*solverstate')
if self.custom_command:
training_string = 'srun --gres=gpu:1 {} 2>> {}'.format(
self.custom_command, self.log_path)
elif latest_snapshot:
latest_snapshot = os.path.join(self.snapshots_path, latest_snapshot)
training_string = (
'srun --gres=gpu:1 '
'{} train '
'--solver={} '
'--snapshot={} '
'--gpu={} 2>> {}').format(
binary_path, self.solver_path, latest_snapshot, GPU_ID,
self.log_path)
else:
if self.experiment['weights']:
weights_string = '--weights=' + self.experiment['weights']
else:
weights_string = ''
training_string = (
'srun --gres=gpu:1 '
'{} train '
'--solver={} {} '
'--gpu={} 2>> {}').format(
binary_path, self.solver_path, weights_string, GPU_ID,
self.log_path)
file(os.path.join(self.path, 'training_string.txt'), 'w').write(training_string)
self.training_process = subprocess.Popen(training_string,
stdin=subprocess.PIPE, shell=True, preexec_fn=os.setsid)
def get_studies(request):
util.get_studies()
return HttpResponse(json.dumps(util.get_latest()), 'text/json')
