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You can no longer try out a new attention variant by writing a few PyTorch operators – you often need to write a new custom kernel
from the top result below
https://pytorch.org/blog/flexattention/
You can no longer try out a new attention variant by writing a few PyTorch operators – you often need to write a new custom kernel
https://docs.pytorch.org/vision/stable/training_references.html
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https://docs.pytorch.org/TensorRT/tutorials/_rendered_examples/dynamo/converter_overloading.html
Overloading Torch-TensorRT Converters with Custom Converters#
If for some reason you want to change the conversion behavior of a specific PyTorch operation to TensorRT, you can do so by writing a custom converter and overloading Torch-TensorRT’s
https://pytorch.org/tutorials/intermediate/seq2seq_translation_tutorial.html
NLP From Scratch: Translation with a Sequence to Sequence Network and Attention — PyTorch Tutorials 2
https://docs.pytorch.org/docs/main/generated/torch.compiler.keep_tensor_guards_unsafe.html
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