Stuck on an issue?

Lightrun Answers was designed to reduce the constant googling that comes with debugging 3rd party libraries. It collects links to all the places you might be looking at while hunting down a tough bug.

And, if you’re still stuck at the end, we’re happy to hop on a call to see how we can help out.

Add a BlockTransformer helper

See original GitHub issue

This would be similar in spirit to http://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.FunctionTransformer.html#sklearn.preprocessing.FunctionTransformer

Users provide a func that is assumed to operate on ndarrays / pandas dataframes. The BlockTransformer will take care of mapping it to each block / partition.

We may need some information from the user when the function changes dtype / shape.

Issue Analytics

State:
Created 5 years ago
Comments:9 (9 by maintainers)

Top GitHub Comments

1reaction

TomAugspurgercommented, Oct 7, 2018

But we’ll import it in preprocessing.init

0reactions

TomAugspurgercommented, Oct 7, 2018

New module seems reasonable.

Top Results From Across the Web

Implement two- or three-winding linear transformer - Simulink

The Linear Transformer block model shown consists of three coupled windings wound on the same core. The model takes into account the winding...

🤗 Transformers

Transformers support framework interoperability between PyTorch, TensorFlow, ... INTERNAL HELPERS details utility classes and functions used internally.

itsdouges/typescript-transformer-handbook

A comprehensive handbook on how to create transformers for TypeScript with code ... With it we can do powerful things like updating, replacing,...

Block-Recurrent Transformers

We introduce the Block-Recurrent Transformer, which applies a transformer layer in a recurrent fashion along a sequence, and has linear ...

Tutorial 6: Transformers and Multi-Head Attention

We first start by implementing a single encoder block. Additionally to the layers described above, we will add dropout layers in the MLP...