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Increase of memory and excecution time #45
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I figured out the issue. In the utils.py, there are Ops that get added to the graph with each iteration of the loop in both the "crop_batch" functions, which led to an increase in memory usage. I solved it by restructuring the "ImageCoder" class such that the ops are added to the graph just once. |
Hi, sorry I did not get back to you sooner, have been swamped. I would consider merging a PR if you have something that solves the issue cleanly. |
Hello, |
Its sad to say the execution time is still add ( little ) when I try to run guess.py for a batch of images. I am try ing to solve it, however I am not do well in it. My computer is two titian-xp, it still cost 1s to comput a pic (gender) in the beginning, how can i do fast, because i have to deal a huge image data. |
I manage to make it faster by applying TensorFlow-Serving-API and i suggest you to do so. |
thanks |
Many thanks! I had the same problem and fixed it thanks to your inspiration. By the way, your modified code of "utils.py" remains a small probelm: missed the standardize_image operation after flip operation |
Hi @dpressel ,
First of, thank you for this amazing project!
Coming to my issue, when I try running guess.py for a batch of images, the memory and execution time increases for each image. I checked memory using the 'top' and noticed the memory and cpu usage would constantly increase and eventually the program would crash.
I did a bit of digging and found this link where mrry suggests tcmalloc. I also came across couple of other links where this has been suggested but this didn't seem to make a difference.
Any ideas as to how to solve this?
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