Improve layer_norm speed#9355
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panyx0718 merged 2 commits intoPaddlePaddle:developfrom Mar 26, 2018
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transfomer on a single device step time
reduces from 0.157 to 0.125
chengduoZH
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Mar 25, 2018
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That is great!!
The functions in Eigen are too extensive and are very slow in many places.
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| #ifdef PADDLE_WITH_CUDA | ||
| template <typename T> | ||
| class RowwiseMean2D<platform::CUDADeviceContext, T> { |
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I think it might be better to write this function in math_function.
| template <typename T> | ||
| class ColwiseSum2D<platform::CUDADeviceContext, T> { | ||
| public: | ||
| ColwiseSum2D(int left, int right, const platform::DeviceContext& dev_ctx) |
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ColwiseSum is used in lstm_op, gru_op, sequence_expand_op and lstmp_op, maybe those ops' performance can be improved too.
chengduoZH
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Mar 26, 2018
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This PR can be merged first and fixing the comments in next PR.
blacksheep-Aristotle
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Nov 22, 2024
* Fix exitcode bug * Fix `track_case_status` func match bug * Fix return code * Fix print_info func with exit -6 * set output format of fail tests modify verification check failed
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layer_norm forward and backward overall speed up 3x ~ 4x
transfomer on a single device step time
reduces from 0.157 to 0.125
the precommit also automatically formatted some codes.