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seq2seq:基于RNN的序列到序列架构的PyTorch实现
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2021-05-26
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seq2seq seq2seq-pytorch是一个框架,用于在实现的基于注意力的序列到序列模型。 该框架具有用于seq2seq模型,训练,推理,检查点等的模块化和可扩展组件。 介绍 Seq2seq将一个序列转换为另一序列。 它通过使用递归神经网络(RNN)或更经常使用LSTM或GRU来避免梯度消失的问题。 每个项目的上下文是上一步的输出。 主要组件是一个编码器和一个解码器网络。 编码器将每个项目转换为包含该项目及其上下文的相应隐藏向量。 解码器使用先前的输出作为输入上下文来逆转该过程,将向量转换为输出项。 安装 此项目建议使用Python 3.6或更高版本。 我建议为此项目创建一个新的虚拟环境(使用virtualenv或conda)。 先决条件 Numpy: pip install numpy (有关安装Numpy的问题,请参阅)。 PyTorch:请访问以在您的环境中安装该版本。
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