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"""
The most atomic way to train and inference a GPT in pure, dependency-free Python.
This file is the complete algorithm.
Everything else is just efficiency.

@karpathy
"""

import os       # os.path.exists
import math     # math.log, math.exp

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A series of reading lists mostly related to functional programming.

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data Todo = Todo {
  id :: Text,
  created :: UTCTime,
  title :: Text,
  description :: Text,
  priority :: Int
}

data Command
  = Add Main.Todo

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Common

export OPT=/opt
export BUILDS=/some/where/mini_linux
mkdir -p $BUILDS

Linux kernel

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Basic unit type:

λ> replTy "()"
() :: ()

Basic functions:

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Laws that apply to our industry (and others) are interesting to me, and I'm writing up here the ones that often come to mind. I usually forget the name, so writing them up might be helpful for remembering in future.

Parkinson's law

C. Northcote Parkinson's law: Work expands so as to fill the time available for its completion. Similarly, in computing, data expands to fill the space available for storage,

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Typing Haskell in Haskell

MARK P. JONES

Pacific Software Research Center

Department of Computer Science and Engineering

Oregon Graduate Institute of Science and Technology

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{-# LANGUAGE DataKinds #-}

-- | My database API.

module DBAPI where

import Data.Defaults

data ConnSpec p = ConnSpec
  { username :: !(Required p String)

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Sample types:

isDigit :: Monad f => Char -> f Bool
any :: Monad f => (a -> f Bool) -> [a] -> f Bool
reverse :: Monad f => [a] -> f [a]
map :: Monad f => (a -> f b) -> [a] -> f [b]
"hello" :: Monad f => f String
putStrLn :: (MonadIO f) => String -> f ()
show :: (Show a,Monad f) => a -> f String

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*** Exception: Couldn't resolve constraint

  <record getter>

due to problem

  missing field for field access

arising from record-error.hell:2:24