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"""
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- - - - - -- - - - - - - - - - - - - - - - - - - - - - -
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Name - - Sliding Window Attention Mechanism
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Name - - sliding_window_attention.py
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Goal - - Implement a neural network architecture using sliding window attention for sequence modeling tasks.
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Detail: Total 5 layers neural network
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* Input layer
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@ -13,6 +13,7 @@ Date: 2024.10.20
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References:
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1. Choromanska, A., et al. (2020). "On the Importance of Initialization and Momentum in Deep Learning." *Proceedings of the 37th International Conference on Machine Learning*.
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2. Dai, Z., et al. (2020). "Transformers are RNNs: Fast Autoregressive Transformers with Linear Attention." *arXiv preprint arXiv:2006.16236*.
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3. [Attention Mechanisms in Neural Networks](https://en.wikipedia.org/wiki/Attention_(machine_learning))
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"""
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