Hi, I am facing problem to retrieve scalar params corresponding to a layer after importing a trained model from a frozen graph(.pb). The documentation mentions a class "Dict" that manages this, but no example has been provided to work it out.
sadly, as of now, it's not possible (they are not exposed to the public api).
you can traverse the layers, get their names, shapes, input connections, blobs, but that's about it, the LayerParams are hidden in the (private) DnnImpl class.
you could try to generate a (human readable) pbtxt file from the tensorflow api, which has all that information .
Thanks for your input. I am already using the human readable format (.pbtxt) for this information. Just wanted to know if in-build method was available. After trying out different hacks myself and the information provided by you, I guess I will have to settle with .pbtxt method.
Asked: 2018-06-05 02:00:57 -0600
Seen: 314 times
Last updated: Jun 05 '18
To get weights I use :
@LBerger, e.g. conv layers have attributes, like stride and padding. and those are not accessible from c++