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LLM Math: Forward and Backward Pass Computations Explained

By PulseAugur Editorial · [1 sources] ·

This item discusses a mathematical concept related to neural network computations, specifically concerning the forward and backward passes. It explains that a summation in the forward pass leads to replication in the backward pass, and conversely, replication in the forward pass implies variable reuse, necessitating a summation in the backward pass to account for this reuse. AI

IMPACT Explains a fundamental computational concept relevant to understanding LLM mechanics.

RANK_REASON The item is a social media post discussing a technical concept, not a primary source release or significant industry event.

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AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLM Math: Forward and Backward Pass Computations Explained

COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · xElliMoo ·

    If you see sum in forward pass, there will be a replication (broadcasting) in backward pass; while if you see a replication in forward pass, which indicates the

    If you see sum in forward pass, there will be a replication (broadcasting) in backward pass; while if you see a replication in forward pass, which indicates there is variable reuse, so during backward pass, there will be a sum over the same dimension to count for all the reuse. #…

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