Command Line Interfaces (CLIs)
Overview
# log in to the MLOps Platform
fedml login
# build packages for the MLOps Platform
fedml build
# Logout from the MLOps platform
fedml logout
# Display logs during training
fedml logs
# Display FedML environment
fedml env
# Display FedML version
fedml version
1. Login to the TensorOpera AI platform (fedml.ai)
login as client with local pip mode:
fedml login userid(or API Key)
login as client with docker mode:
fedml login userid(or API Key) --docker --docker-rank rank_index
login as edge server with local pip mode:
fedml login userid(or API Key) -s
login as edge simulator with local pip mode:
fedml login userid(or API Key) -c -r edge_simulator
login as edge server with docker mode:
fedml login userid(or API Key) -s --docker --docker-rank rank_index
1.1. Examples for Logging in to the TensorOpera AI platform (fedml.ai)
fedml login 90
Notes: this will login the production environment for TensorOpera AI platform
fedml login 90 --docker --docker-rank 1
Notes: this will login the production environment with docker mode for TensorOpera AI platform
2. Build the client and server package in the TensorOpera AI platform (fedml.ai)
fedml build -t client(or server) -sf source_folder -ep entry_point_file -cf config_folder -df destination_package_folder --ignore ignore_file_and_directory(concat with ,)
2.1. Examples for building the client and server package
# build client package
SOURCE=./../cross_silo/client/
ENTRY=torch_client.py
CONFIG=./../cross_silo/config
DEST=./
IGNORE=__pycache__,*.git
fedml build -t client \
-sf $SOURCE \
-ep $ENTRY \
-cf $CONFIG \
-df $DEST \
--ignore $IGNORE
# build server package
SOURCE=./../cross_silo/server/
ENTRY=torch_server.py
CONFIG=./../cross_silo/config
DEST=./
IGNORE=__pycache__,*.git
fedml build -t server \
-sf $SOURCE \
-ep $ENTRY \
-cf $CONFIG \
-df $DEST \
--ignore $IGNORE
3. Log out the MLOps platform (fedml.ai)
logout from client with local pip mode:
fedml logout
logout from client with docker mode:
fedml logout --docker --docker-rank 1
logout from edge server with local pip mode:
fedml logout -s
logout from edge server with docker mode:
fedml logout -s --docker --docker-rank 1
4. Display FedML Environment and Version
fedml env
fedml version
5. Display logs
logs from client with local pip mode:
fedml logs
logs from client with docker mode:
fedml logs --docker --docker-rank 1
logs from edge server with local pip mode:
fedml logs -s
logs from edge server with docker mode:
fedml logs --docker --docker-rank 1
6. Diagnosis
Diagnosis for connection to https://tensoropera.ai, AWS S3 and MQTT (mqtt.fedml.ai:1883)
fedml diagnosis --open --s3 --mqtt
7. Jobs
Start a job at the MLOps platform.
Usage: fedml jobs start [OPTIONS]
Start a job at the MLOps platform.
Options:
-pf, --platform TEXT The platform name at the MLOps platform
(options: octopus, parrot, spider, beehive).
-prj, --project_name TEXT The project name at the MLOps platform.
-app, --application_name TEXT Application name in the My Application list
at the MLOps platform.
-d, --devices TEXT The devices with the format: [{"serverId":
727, "edgeIds": ["693"], "account": 105}]
-u, --user TEXT user id or api key.
-k, --api_key TEXT user api key.
-v, --version TEXT start job at which version of MLOps platform.
It should be dev, test or release
--help Show this message and exit.
Example:
fedml jobs start -pf octopus -prj test-fedml -app test-alex-app -d '[{"serverId":706,"edgeIds":["705"],"account":214}]' -u 214 -k c9356b9c4ce44363bb66366d210301
You can also refer to a sanity check test example here: https://github.com/FedML-AI/FedML/blob/master/python/tests/smoke_test/cli/build.sh