Charles Earl

With the goal of eventually providing a Racket module, documentation should be developed that conforms to Racket best practices.

Examples should be provided in the repository for defining and training neural network architectures in DyNet.

Develop a DSL for specifying DyNet networks

1

The strength of Racket is its support for advanced DSL design. This should be used to develop a facility to easily specify network architectures.

The DyNet library now provides a C API. Using this should be more in line with the foreign function interface provided by Racket.

The code base consists of code that wraps the NVIDIA cuDNN library and the higher level Dynet Deep Learning API. These should be at least separated into two directories, if...

Loading a pdf results in a StopIteration error

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### Bug Running spacy-layout on a Apple M3 Pro with 36GB memory. Python version 3.11.7 The following code is invoked in a python Jupyter notebook: ``` from docling.document_converter import DocumentConverter...