README.md

PyTorch Transformer

A simple clean-readable and shape-annotated implementation of Attention is All You Need in PyTorch. A sample onnx file can be found in assets/transformer.onnx for visualization purposes.

It was tested on synthetic data, try to use the attention plots to figure out the transformation used to create the data!

Implementation Details

• Positional Embeddings not included, similar to nn.Transformer but you can find an implementation in usage.ipynb.
• Parallel MultiHeadAttention outperforms the for loop implementation significantly, as expected.
• Assumes batch_first=True input by default and cna't be changed.
• Uses einsum for attention computation rather than bmm for readability, this might impact performance.