module cli.make_ml_upload
¶
Short summary¶
module lightmlrestapi.cli.make_ml_upload
Creates and runs an Falcon application.
Functions¶
function |
truncated documentation |
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Uplaods a machine learned models to a REST API defined by |
Documentation¶
Creates and runs an Falcon application.
- lightmlrestapi.cli.make_ml_upload.upload_model(login='', pwd='', name='', pyfile='', data='', url='127.0.0.1:8081', timeout=50, fLOG=<built-in function print>)¶
Uplaods a machine learned models to a REST API defined by
MLStoragePost
.- Parameters:
login – user login
pwd – user pasword
name – name of the model, should be unique and not already used
pyfile – python file which computes the prediction, the file must follows the specification defined in Templates
data – files to upload
url – url of the REST API
timeout – timeout
fLOG – logging function
Uploads a machine model
Uploads a machine learned model to a REST API created with lightmlrestapi. The code of this command line is equivalent to:
from lightmlrestapi.netrest import submit_rest_request, json_upload_model req = json_upload_model(name=name, pyfile=pyfile, data=data) submit_rest_request(req, login=login, pwd=pwd, url=url)
<<<
python -m lightmlrestapi upload_model --help
>>>
usage: upload_model [-h] [-l LOGIN] [--pwd PWD] [-n NAME] [-p PYFILE] [-d DATA] [--url URL] [-t TIMEOUT] Uplaods a machine learned models to a REST API defined by :class:`MLStoragePost <lightmlrestapi.mlapp.mlstorage_rest.MLStoragePost>`. optional arguments: -h, --help show this help message and exit -l LOGIN, --login LOGIN user login (default: ) --pwd PWD user pasword (default: ) -n NAME, --name NAME name of the model, should be unique and not already used (default: ) -p PYFILE, --pyfile PYFILE python file which computes the prediction, the file must follows the specification defined in :ref:`l-template-ml` (default: ) -d DATA, --data DATA files to upload (default: ) --url URL url of the REST API (default: 127.0.0.1:8081) -t TIMEOUT, --timeout TIMEOUT timeout (default: 50)