Comments (3)
The amount of training is determined by the parameters max_steps
and num_train_epochs
, whichever is minimum. The former defaults to -1. The throughput computation accounts for these parameters in the if else
clause.
You throughput should reach a steady state after running a minimum number of steps > 100. If max_steps is higher than what is determined by num_epochs, your throughput will be artificially inflated by the max_steps set, which is a bug. I can fix this soon, feel free to send in a PR.
from deeplearningexamples.
Need to add args.max_steps = min(args.max_steps, len(train_features) * args.num_train_epochs)
before line 1203 to fix the discrepancy you are seeing.
from deeplearningexamples.
Thanks @sharathts , will raise a pr with above change
from deeplearningexamples.
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from deeplearningexamples.