Raft

An attempt to implement the Raft distributed protocol using OCaml 5 Eio, Effect Handlers, and capnp-rpc, which is a RPC library based on Eio(This is still in a branch waiting to be merged). Everything involved in this has to be learned.

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Collaborative Editor

Collaborative editor patterns that I try to code could be of many kinds. There are string manipulation algorithms, CRDTs and even LLM inference. So even though a full-fledged editor is not in scope here, many algorithms like these can be explored and a functional editor can be created.

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Game Of Life in Racket

I know of a few methods to learn Functional Programming languages. One could read a book or read source code. My attempt involves source code that I port to my favorite language. And I learn two different languages at the same time. The source and the target. It has been very productive for me.

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Semantics of Simple Programming Languages

I am reading about Semantics of Programming Languages and here is an attempt to code Racket to parse and interpret toy languages. More details will be added. The code here is not the final version but it compiles. It shows the progress made as I learn the nuances of Racket and types.

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BTree Variants

Whenever I code Data structures like BTree,LSM etc. in OCaml I read SML,Rust or C++ code. The code I read is in a repo. that implements a caching layer or DBs like https://rethinkdb.com. I don’t find any direct OCaml references. So I ported this Haskell two-three tree by http://matthew.brecknell.net/post/btree-gadt/…. Moreover since I am learning it is hard to identify succinct functional code as some examples seem to be imperative.

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Probabilistic and other Data Structures

tl;dr

  1. The code will be gradually improved and be committed to git finally.
  2. Performance considerations are not paramount here.
  3. The language is OCaml and it is imperative even though I will attempt to use functional Data structures.
  4. The repository is this
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Llama Architecture(GPT)

tl;dr

  1. The architecture is described in Llama: Open and Efficient Foundation Language Models
  2. The code is ported from PyTorch to TensorFlow 2.x using various references. (e.g) https://nn.labml.ai/transformers/rope/index.html TensorFlow is very verbose and sometimes it poses difficulties as every line of PyTorch has to be ported.
  3. In very few cases the code can be directly ported with minimal changes. But this situation isn’t common.
  4. The math supporting the algorithm is only partially understood. There are several research papers to read.
  5. The RoPE embeddings and attention need more insight and explanation.In fact each section will need multiple diagrams and descriptions.
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Learning Coq(Work in Progress)

I started dabbling in Programs and proofs recently by using Spacemacs and its Coq layer. Since I didn’t study this subject before I start by setting up and using the tools.

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TensorFlow Recipes

As part of my effort to engage with the Open-source community I started answering Stackoverflow questions. I started by asking a few decent questions and then answered some of my own questions and accepted them. Gradually I understood that this community site is not only about answering but also asking good questions that others can answer.

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Joy of OCaml - Part III

At this time this article is quite unwieldy and contains hundreds of lines of code without proper explanation. It has to be split up , edited and published as another series. Moreover I learnt more about how to code a functional language by consulting some experts. I will edit it in due course.

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Joy of OCaml - Part I

Many programming problems lend themselves easily to solutions based on Functional Programming languages. It is not hard to convince ourselves of this after coding a Language like OCaml or Haskell.

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