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deep learning

implementing seq2seq RNN model in tensorflow

for tackling the many-to-many(with timedistributed) is easy to implement in keras code, it does not seem to be easy to do so in pure tensorflow. Of course, one can implement it when the sequence length is fixed for all input size. However when the sequence length among batches vary, then Read more…

By admin, 4 years4 years ago
deep learning

image dataset converted to tfrecord stats

I had 658240 image dataset. Each set has image and mask. Both are png files. Each image file was size of 224 x 224. To total size was 30G.  After converting it to tfrecord, the size reduced to 27G.

By chadrick_author, 4 years4 years ago
deep learning

forcing memory release of gpu

identifying which pid is occupying the gpu can be found following this thread. However, the gpu number in the above link is not identical with the gpu number displayed with nvidia-smi. In my case, the processes that were occupying the gpu memory did not show up in nvidia-smi but it showed Read more…

By chadrick_author, 4 years ago
deep learning

Focal Loss (a.k.a RetinaNet) paper review

I have heard so much about Retinanet in the realm of object detection and recently I had the chance to read the paper. Surprisingly, the paper is titled with “focal loss” and not “RetinaNet”. The most important lesson that I learned here was that it was the “focal loss” that was Read more…

By admin, 4 years4 years ago

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