FIle issue onto Qualcomm:SNPE
Hi,
Does QNN supports weight sharing of two independent models/graphs?
I'm trying to export a single binary with two models/graphs who share the same weights, as show in the image.
Victor Escorcia escorciav
🎯
TL;DR: using syntactic pytorch data loader abstraction to feed your TF model.
WIP. The code should work. Take a look at the benchmark for a particular use case.
- CSV file loader. using "image,target" as header.
- simple transformer
- loop over the entire dataset
- make a graph
- call session
escorciav
/ plot-figure-5-daps-eccv16.ipynb
Last active
April 8, 2020 10:07
IPython notebook reproducing Figure 5 of DAPs paper (ECCV-2016)
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
Perform PCA of features on Thumos14-val.
A is [n_samples, feat_dim] tall matrix i.e. n_samples >> feat_dim. We compute A^T A out of core to perform dimensionality reduction of feat_dim using in-memory eigen-decomposition.
Wouldn't it be cool to annotate a box inside the IPython notebook and use it to test your algorithm? This notebook will show you how to do that.
Usage: run the first and second cell of the notebook, select a rectangle on the figure in the second cell, run the next cells.
Motivation: I didn't find a simple exampe for doing this without setup a server or using sophisticated connections with IPython via JS. AFAIK this example was the most trivial-pythonic code to annotate boxes but it doesn't explain how to push information to IPython 1.
Acknowledgements: Bokeh for improving the documentation and interface of this package. @jakevdp for share his [pythonic perambulations](https://jakevdp.github.io/blog/2013/06/01/ipython-notebook-javascript-python-commun
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| name: 'EuclideanExample' | |
| layer { | |
| type: 'DummyData' | |
| name: 'x' | |
| top: 'x' | |
| dummy_data_param { | |
| shape: { dim: 10 dim: 3 dim: 2 } | |
| data_filler: { type: 'gaussian' } | |
| } | |
| } |
escorciav
/ trn_loss_iters.png
Last active
August 29, 2015 14:03
Caffe in ILSVCR competition CLS-LOC
This is the results that I got after ~60000 iterations (> 4 days) on ILSVCR-2014 with 1000 categories.
I'm using the same model proposed by caffe developers.
