Merge plugin/0.2.1 code into master #345
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* remove the Record Window End event if the duration is larger than 1 day to workaround the high resolution clock bug in pytorch profiler * remove debug print
update doc and tooltip
* add notes of python version in case of circular import bug * update wording
… is available in Tensorboard 2.0 (#323)
* workaround for negative gpu metrics from input json file * refine
This commit makes `walk`-ing directories follow symlinks when searching for run data (on local filesystems, where it's supported!). This makes the plugin's search behavior consistent with that of tensorboard itself; using symlink trees to organize runs is one of the recommendations made in the tensorboard docs to have fine-grained control over the naming of runs and the location of the data [1]: > TensorBoard walks log directories recursively; for finer-grained > control, prefer using a symlink tree. A unit test is added to validate the new behavior. [1] https://github.com/tensorflow/tensorboard/blob/master/README.md#logdir--logdir_spec-legacy-mode
* return loading run status to frontend to fix a couple of bugs * Add message when logdir has no runs (#343) * Add message when logdir has no runs * Correct Typography import * fix test failure * remove dead code Co-authored-by: TomWildenhain-Microsoft <67606533+TomWildenhain-Microsoft@users.noreply.github.com>
gdankel
approved these changes
Jul 9, 2021
| For example, a kernel with only one thread per block can’t fully utilize each SM. | ||
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| * Est. Achieved Occupancy: The bigger, the better. The definition of occupancy is [here](https://docs.nvidia.com/gameworks/content/developertools/desktop/analysis/report/cudaexperiments/kernellevel/achievedoccupancy.htm). | ||
| * Est. Achieved Occupancy: For most cases such as memory bandwidth bounded kernels, the higher the better. [Reference](http://developer.download.nvidia.com/GTC/PDF/GTC2012/PresentationPDF/S0514-GTC2012-GPU-Performance-Analysis.pdf). The definition of occupancy is [here](https://docs.nvidia.com/gameworks/content/developertools/desktop/analysis/report/cudaexperiments/kernellevel/achievedoccupancy.htm). |
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The improvements in performance does not normally scale linearly after some point, but not sure how to best express this in a clear way.
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we will consider more clear description in next release.
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I had to fix a couple of linter warnings so I changed this as well to "a higher value often translates to better performance, especially when the starting value is very low." Sounds OK?
| on_trace_ready=torch.profiler.tensorboard_trace_handler('./result', worker_name='worker0'), | ||
| record_shapes=True, | ||
| profile_memory=True, | ||
| profile_memory=True, # This will take 1 to 2 minutes. Setting it to False could greatly speedup. |
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I suggest we also add a similar comment to with_stack
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will do in next release.
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merge 0.2.1 bug fixes into master