Incubator-mxnet: Correct Speedometer Callback Usage

[JonBoyleCoding]

I tried to follow the example here on how to use the callback Speedometer:

https://github.com/dmlc/mxnet/blob/master/example/notebooks/tutorial.ipynb

But when I used it, it didn't produce anything throughout the entire training. I'm using my own images, approx 7000 training exemplars of (3, 256, 256). I used an epoch callback, and that saved things as I expected (every 10 epochs).

import mxnet
import symbol_alexnet

train_iter = mxnet.io.NDArrayIter(exemplars_train, labels_train, 100)
test_iter = mxnet.io.NDArrayIter(exemplars_test, labels_test, 100)

alexnet = symbol_alexnet.get_symbol(len(class_list))
epochs = 80

model = mxnet.model.FeedForward(
ctx = mxnet.gpu(0),
symbol=alexnet,
num_epoch=epochs,
learning_rate = 0.1,
momentum = 0.9)

model.fit(
X=train_iter,
eval_data=test_iter,
epoch_end_callback = mxnet.callback.do_checkpoint("chks/train", 10),
batch_end_callback = mxnet.callback.Speedometer(100,10))

Could anyone tell me what I got wrong? I presume it has to do with the batch_size, but I'm a little uncertain on it's exact meaning.

[piiswrong]

import logging and set logging level to debug

[Qunal]

I had same issue but it turns out the Spyder the python IDE that came with Anaconda sets a logger at startup and subsequent python configuration does not change that. So log messages go to console or in some cases disappear and not a file. After tinkering with the code in python folder of MXNET esp callback.py managed to get speedometer logs. I think should use log handlers .cleaner and can save to file

[JonBoyleCoding]

Can confirm this is working, just for future reference so people don't have to go searching on how to use logging:

import logging

logging.basicConfig(level=logging.DEBUG)