$ uname -r
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{-# LANGUAGE TupleSections #-} | |
module Main where | |
import Graphics.Gloss | |
import Graphics.Gloss.Raster.Field | |
import System.Random | |
import Data.Semigroup | |
import GHC.Base (NonEmpty(..)) |
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{-# LANGUAGE TupleSections #-} | |
module Main where | |
import Graphics.Gloss | |
import Graphics.Gloss.Raster.Field | |
import System.Random | |
import Data.Semigroup | |
import GHC.Base (NonEmpty(..)) |
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// http://journal.stuffwithstuff.com/2013/12/08/babys-first-garbage-collector/ | |
// | |
#define STACK_MAX 256 | |
#define INITIAL_GC_THRESHOLD 2 | |
#include <stdio.h> | |
#include <stdlib.h> | |
void gc(); // Pre-Declared for co-recursive usage |
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""" | |
Example of a Streamlit app for an interactive Prodigy dataset viewer that also lets you | |
run simple training experiments for NER and text classification. | |
Requires the Prodigy annotation tool to be installed: https://prodi.gy | |
See here for details on Streamlit: https://streamlit.io. | |
""" | |
import streamlit as st | |
from prodigy.components.db import connect | |
from prodigy.models.ner import EntityRecognizer, merge_spans, guess_batch_size |
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""" | |
Example of a Streamlit app for an interactive Prodigy dataset viewer that also lets you | |
run simple training experiments for NER and text classification. | |
Requires the Prodigy annotation tool to be installed: https://prodi.gy | |
See here for details on Streamlit: https://streamlit.io. | |
""" | |
import streamlit as st | |
from prodigy.components.db import connect | |
from prodigy.models.ner import EntityRecognizer, merge_spans, guess_batch_size |
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pip install streamlit | |
pip install spacy | |
python -m spacy download en_core_web_sm | |
python -m spacy download en_core_web_md | |
python -m spacy download de_core_news_sm |
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{-# LANGUAGE GeneralizedNewtypeDeriving #-} | |
{-# LANGUAGE LambdaCase #-} | |
{-# LANGUAGE MultiWayIf #-} | |
{-# LANGUAGE RecordWildCards #-} | |
module Game.THLPE | |
( THLPE () | |
, GodAnswer (..) | |
, GodType (..) | |
, GodName (..) |
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### JHW 2018 | |
import numpy as np | |
import umap | |
# This code from the excellent module at: | |
# https://stackoverflow.com/questions/4643647/fast-prime-factorization-module | |
import random |
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#include <stdio.h> | |
#include <stdlib.h> | |
#include <stdint.h> | |
#ifdef _MSC_VER | |
#include <intrin.h> /* for rdtscp and clflush */ | |
#pragma optimize("gt",on) | |
#else | |
#include <x86intrin.h> /* for rdtscp and clflush */ | |
#endif |