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  • Created about 4 years ago
  • Updated almost 2 years ago

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Repository Details

Management Dashboard for Torchserve

Torchserve Dashboard

Total Downloads Downloads

Torchserve Dashboard using Streamlit

Related blog post

Demo

Usage

Additional Requirement: torchserve (tested on:v0.5.3, supports: v0.7.0 (no API changes between versions))

Simply run:

pip3 install torchserve-dashboard --user
# torchserve-dashboard [streamlit_options(optional)] -- [config_path(optional)] [model_store(optional)] [log_location(optional)] [metrics_location(optional)]
torchserve-dashboard
#OR change port 
torchserve-dashboard --server.port 8105 -- --config_path ./torchserve.properties
#OR provide a custom configuration 
torchserve-dashboard -- --config_path ./torchserve.properties --model_store ./model_store

❗ Keep in mind that If you change any of the --config_path,--model_store,--metrics_location,--log_location options while there is a torchserver already running before starting torch-dashboard they won't come into effect until you stop&start torchserve. These options are used instead of their respective environment variables TS_CONFIG_FILE, METRICS_LOCATION, LOG_LOCATION.

OR

git clone https://github.com/cceyda/torchserve-dashboard.git
streamlit run torchserve_dashboard/dash.py 
#OR
streamlit run torchserve_dashboard/dash.py --server.port 8105 -- --config_path ./torchserve.properties 

Example torchserve config:

inference_address=http://127.0.0.1:8443
management_address=http://127.0.0.1:8444
metrics_address=http://127.0.0.1:8445
grpc_inference_port=7070
grpc_management_port=7071
number_of_gpu=0
batch_size=1
model_store=./model_store

If the server doesn't start for some reason check if your ports are already in use!

Updates

[15-oct-2020] add scale workers tab

[16-feb-2021] (functionality) make logpath configurable,(functionality)remove model_name requirement,(UI)add cosmetic error messages

[10-may-2021] update config & make it optional. update streamlit. Auto create folders

[31-may-2021] Update to v0.4 (Add workflow API) Refactor out streamlit from api.py.

[30-nov-2021] Update to v0.5, adding support for encrypted model serving (not tested). Update streamlit to v1+

FAQs

  • Does torchserver keep running in the background?

    The torchserver is spawned using Popen and keeps running in the background even if you stop the dashboard.

  • What about environment variables?

    These environment variables are passed to the torchserve command:

    ENVIRON_WHITELIST=["LD_LIBRARY_PATH","LC_CTYPE","LC_ALL","PATH","JAVA_HOME","PYTHONPATH","TS_CONFIG_FILE","LOG_LOCATION","METRICS_LOCATION","AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY", "AWS_DEFAULT_REGION"]

  • How to change the logging format of torchserve?

    You can set the location of your custom log4j2 config in your configuration file as in here

    vmargs=-Dlog4j.configurationFile=file:///path/to/custom/log4j2.xml

  • What is the meaning behind the weird versioning?

    The minor follows the compatible torchserve version, patch version reflects the dashboard versioning

Help & Question & Feedback

Open an issue

TODOs

  • Async?
  • Better logging
  • Remote only mode