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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