算法神经网络训练的相关内容

文章 2024-06-28 来自：开发者社区

反向传播算法在多层神经网络训练中至关重要，它包括前向传播、计算损失、反向传播误差和权重更新。

反向传播算法（Backpropagation Algorithm）是训练人工神经网络中最为广泛使用的算法之一，特别是在多层前馈神经网络中。以下是反向传播算法的基本工作原理：前向传播（Feedforward）阶段：输入数据首先通过网络的输入层进入，经过一系列的隐藏层（如...

文章 2023-07-02 来自：开发者社区

类GPT模型训练提速26.5%，清华朱军等人用INT4算法加速神经网络训练

我们知道，将激活、权重和梯度量化为 4-bit 对于加速神经网络训练非常有价值。但现有的 4-bit 训练方法需要自定义数字格式，而当代硬件不支持这些格式。在本文中，清华朱军等人提出了一种使用 INT4 算法实现所有矩阵乘法的 Transformer 训练方法。模型训练得快不快，这与激活值、权重、梯度等因素的要求紧密相关。神经网络训练需要一定计算量，使用低精度算法（全量化训练或 FQT 训练）有....

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更新时间 2024-06-29 11:13:54

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