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Published 20 hours ago • verified publisher icon zizhaozhang

Efficiency issue

Open LLCF opened this issue 6 years ago • 4 comments 

 x_batch, y_batch = next(train_generator)
 feed_dict = {   img: x_batch,
                        label: y_batch
                    }

This way is very slowly.

LLCF avatar May 04 '18 01:05 LLCF

It is slow because of the memory leak of the line: global_step.assign(it).eval() this line can be deleted!!!!

abin24 avatar May 07 '18 15:05 abin24

I don't think so. When I comment "global_step.assign(it).eval()", most of the time, the GPU-Util is also 0%. I am sure that the GPU is waiting for data.

LLCF avatar May 08 '18 02:05 LLCF

Ok, I don't know what happened. I just add line sess.graph.finalize() after the line sess.run(init_op). and comment "global_step.assign(it).eval()" The train time is 4~5 faster than the original version. BTW, the original version will get 2~3times slower after about 1-2 hour

abin24 avatar May 08 '18 02:05 abin24

I want to ask where is the train data and test data???I am very urgent

duyanfang123 avatar Oct 31 '18 09:10 duyanfang123