FlexAttention

New PyTorch API: Implementing Various Attention Variants with FlashAttention Performance

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New PyTorch API: Implementing Various Attention Variants with FlashAttention Performance

MLNLP community is a well-known machine learning and natural language processing community both domestically and internationally, covering NLP graduate students, university professors, and corporate researchers. The vision of the community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning both domestically and internationally, especially for … Read more

New PyTorch API: Implementing Different Attention Variants with Just a Few Lines of Code!

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New PyTorch API: Implementing Different Attention Variants with Just a Few Lines of Code!

Click on the above“Beginner’s Guide to Vision” to choose to addto favorites or “pin” Important information delivered promptly Reprinted from: Machine Heart | Edited by: Chen Chen Try a new attention pattern with FlexAttention. In theory, the attention mechanism is everything you need. However, in practice, we also need to optimize implementations of attention mechanisms … Read more

Practical Implementation of PyTorch FlexAttention: Causal Attention and Variable-Length Sequence Processing Based on BlockMask

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Practical Implementation of PyTorch FlexAttention: Causal Attention and Variable-Length Sequence Processing Based on BlockMask

Source: DeepHub IMBA This article is approximately 2000 words long and is recommended for a 5-minute read. This article introduces how to use the new FlexAttention and BlockMask features introduced in PyTorch version 2.5 and above to implement causal attention mechanisms and handle padded inputs. Given the current lack of complete code examples and technical … Read more