Efficiency issue

[LLCF]

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

This way is very slowly.

[abin24]

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

[LLCF]

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.

[abin24]

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 45 faster than the original version. BTW, the original version will get 23times slower after about 1-2 hour

[duyanfang123]

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