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Current implementation is O(n^2), this implementation is O(n)
wkcn
reviewed
Sep 2, 2019
for name in self.output_names] | ||
self.num_outputs = len(self.symbol.list_outputs()) | ||
self.num_outputs = len(self.output_names) | ||
self.output_layouts = [i for i in range(self.num_outputs)] |
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Thank you for the contribution!
The following code may be faster : )
self.num_outputs = len(self.output_names)
self.output_layouts = [DataDesc.get_batch_axis(self.symbol[index].attr('__layout__'))
for index in range(self.num_outputs)]
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Thanks!
Current implementation is O(n^2), this implementation is O(n)
wkcn
approved these changes
Sep 2, 2019
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LGTM. Thank you : )
gyshi
pushed a commit
to gyshi/incubator-mxnet
that referenced
this pull request
Sep 7, 2019
* Speed up group executor Current implementation is O(n^2), this implementation is O(n) * Speed up group executor Current implementation is O(n^2), this implementation is O(n) * CI
gyshi
pushed a commit
to gyshi/incubator-mxnet
that referenced
this pull request
Sep 7, 2019
* Speed up group executor Current implementation is O(n^2), this implementation is O(n) * Speed up group executor Current implementation is O(n^2), this implementation is O(n) * CI
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Description
We ran into an issue where mxnet took over 15 minutes of real-time to process large symbols, this change was the root cause. The square-brackets implementation of symbol looks up the symbol using a loop, so the implementation was O(n^2) where it should have been O(n)