Tracer is a desktop app to render deep learning models:
- keep browsing history for easy trace back
- support viewing of embedded graphs
- track upstream and downstream
- search node by keyword
- support onnx, tensorflow, keras and pytorch models
- git clone the tracer project
- pip install -r requirements.txt
- pip install onnx if need to view onnx models
- pip install tf>=2.2.0 if need to view tensorflow or keras models
- pip install torch if need to view pytorch models
- run "python setup.py install"
- open python terminal and run:
from tracer import tracer
tracer.show()
Tracer keeps history of highlighted nodes, user could rely on buttons from toolbar to go back and forth:
In property panel, select corresponding attribute, click on "..." button, embedded graph will be rendered in a new frame:
In property panel, select the input and click on "..." button to go to upstream node, same for output:
Just type keyword in search input box on right-top corner, select matching item from drop-down and click on search button:
Note that searching happens recursively - nodes of embedded graph will all be included.
By far only onnx, tensorflow and keras formats are supported.
Welcome to contribute.