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CLAassistant commented Nov 14, 2024

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Layer normalization might experience a slowdown when the normalized_shape exceeds 6000. However, it should be noted that layer normalization does not consume additional memory. Hence, there is no necessity to split the input into chunks.

@zhangyuxuann zhangyuxuann merged commit 9fc77e3 into bytedance:main Nov 14, 2024
thalahors pushed a commit to thalahors/Protenix that referenced this pull request Feb 17, 2025
…tch-1

remove layernorm chunk code which will make train/inference slow down
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3 participants