def push():
"""
Create a pre-trained model from model store
"""
model_id = flask.request.args.get('id')
model_grand_list = app.config['store_cache'].read()
found = False
if model_grand_list is not None:
for store in model_grand_list:
for model in model_grand_list[store]['model_list']:
if model['id'] == model_id:
url = model_grand_list[store]['base_url']
directory = model['dir_name']
found = True
break
if found:
break
if not found:
return 'Unable to find requested model', 404
else:
progress = Progress(model_id)
weights, model, label, meta_data, python_layer = retrieve_files(url, directory, progress)
job = PretrainedModelJob(
weights,
model,
label,
meta_data['framework'],
username=auth.get_username(),
name=meta_data['name']
)
scheduler.add_job(job)
response = flask.make_response(job.id())
return response
def push():
"""
Create a pre-trained model from model store
"""
model_id = flask.request.args.get('id')
model_grand_list = app.config['store_cache'].read()
found = False
if model_grand_list is not None:
for store in model_grand_list:
for model in model_grand_list[store]['model_list']:
if model['id'] == model_id:
url = model_grand_list[store]['base_url']
directory = model['dir_name']
found = True
break
if found:
break
if not found:
return 'Unable to find requested model', 404
else:
progress = Progress(model_id)
weights, model, label, meta_data, python_layer = retrieve_files(
url, directory, progress)
job = PretrainedModelJob(weights,
model,
label,
meta_data['framework'],
username=auth.get_username(),
name=meta_data['name'])
scheduler.add_job(job)
response = flask.make_response(job.id())
return response
