added nadam optimizer #1408
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added nadam optimizer #1408
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Save memory by exploiting in-place operations.
Contributor
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You might would love to see this PR on your branch where in-place opts are exploited. |
Reformats my PR
Update nadam.py
Contributor
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Tried it on CPU. It gradually became very slow after a few epochs. Any ideas? |
Collaborator
Author
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It didn't happen on my machine. Can you send me the log? |
Contributor
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I guess this is not super helpful. The "[mm:ss<00:00, ]" indicates the time spent on each epoch. Problem solved by switching to Adam. |
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Try using Python line-profiler https://github.com/rkern/line_profiler#id5 to locate issue. |
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any updates? |
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zou3519
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Mar 30, 2018
Summary: My commit bab5bc broke things wiht fp16 compute, as i had tested it only with the null-input, that actually produced fp32 data (even dtype was given as float16). Also, I had confused the concepts of "float16 compute" and fp16 data. Issue pytorch#1408. This fixes those issues, tested with both Volta and M40 GPUs. Basically restored much of the previous code and fixed the null input to do FloatToHalf. Reviewed By: pietern Differential Revision: D6211849 fbshipit-source-id: 5b41cffdd605f61a438a4c34c56972ede9eee28e
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The PR added the new optimizer of Nadam. I wrote this code according to the Nadam code in Keras and the Adam code in the PyTorch repo. I've tested the code and it shows better performance in MNIST than original Adam.