Optimize FFN size dimension calculation#11
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In modern Transformer models (like SwiGLU implementations in LLaMA), padding the Feed-Forward Network size to a larger multiple (e.g., 256) instead of just 8 yields significant throughput improvements on GPUs and TPUs by allowing better utilization of Tensor Cores. Also fixes a typo in the logger output. Co-authored-by: sashimikun <57305937+sashimikun@users.noreply.github.com>
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Optimizes the Feed-Forward Network dimension calculation in
phoenix/grok.pyto pad it to a multiple of 256 instead of 8, allowing much more efficient tensor core utilization. Also fixes a small typo in the logging message.PR created automatically by Jules for task 9274861776356519902 started by @sashimikun