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R = TypeVar('R') | |
Rs = TypeVarTuple('Rs') | |
class Query(Generic[R]): | |
... | |
def execute(*args: *Map[Query, Rs]) -> Tuple[*Rs]: | |
... |
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GetSetVar = TypeVar('GetSetVar') | |
TagVar = TypeVarTuple('TagVar') | |
class MultiField(AbstractField[GetSetVar], Generic[*TagVar]): | |
def __init__(self, nbt_names: Sequence[str], *, default: GetSetVar = None) -> None: | |
... | |
@abc.abstractmethod | |
def to_python(self, *tags: *TagVar) -> GetSetVar: | |
... |
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{ | |
"citation": "@misc{\n author={Karpathy, Andrej},\n title={char-rnn},\n year={2015},\n howpublished={\\url{https://github.com/karpathy/char-rnn}}\n}", | |
"description": "40,000 lines of Shakespeare from a variety of Shakespeare's plays. Featured in Andrej Karpathy's blog post 'The Unreasonable Effectiveness of Recurrent Neural Networks': http://karpathy.github.io/2015/05/21/rnn-effectiveness/.\n\nTo use for e.g. character modelling:\n```\nd = tfds.load(name='tiny_shakespeare')['train']\nd = d.map(lambda x: tf.strings.unicode_split(x['text'], 'UTF-8'))\n# train split includes vocabulary for other splits\nvocabulary = sorted(set(next(iter(d)).numpy()))\nd = d.map(lambda x: {'cur_char': x[:-1], 'next_char': x[1:]})\nd = d.unbatch()\nseq_len = 100\nbatch_size = 2\nd = d.batch(seq_len)\nd = d.batch(batch_size)\n```", | |
"location": { | |
"urls": [ | |
"https://github.com/karpathy/char-rnn/blob/master/data/tinyshakespeare/input.txt" | |
] | |
}, | |
"name": "tiny_shakespeare", | |
"schema": { |
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#!/bin/bash | |
pkill -f ngrok | |
ngrok http $1 &> ~/.ngrok.log & | |
sleep 1 | |
echo -n 'ngrok http ' | |
json=$(curl -s http://localhost:4040/api/tunnels) | |
echo "$json" | python3 -c "import sys, json; print(json.load(sys.stdin)['tunnels'][0]['public_url'])" || echo $json |
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#!/usr/bin/env python3 | |
import argparse | |
import os | |
import subprocess | |
import socket | |
import tempfile | |
import getpass | |
parser = argparse.ArgumentParser() |
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#!/usr/bin/env python3 | |
import argparse | |
import pathlib | |
import subprocess | |
import os | |
import shutil | |
import tempfile |
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#!/bin/bash | |
set -o errexit | |
server=$1 | |
remote_paths="$server:\"" | |
for remote_path in "${@:2}"; do | |
remote_paths="$remote_paths '$remote_path'" | |
done | |
remote_paths="$remote_paths\"" |
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#!/usr/bin/env python3 | |
import argparse | |
import fileinput | |
import os | |
import socket | |
import sys | |
parser = argparse.ArgumentParser() | |
parser.add_argument('files', nargs='*') |
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import tensorflow as tf | |
import time | |
sess = tf.Session() | |
var = tf.Variable(0) | |
saver = tf.train.Saver(max_to_keep=1) | |
sess.run(var.initializer) | |
i = 0 | |
while True: |
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import tensorflow as tf | |
import time | |
sess = tf.Session() | |
var = tf.Variable(0) | |
saver = tf.train.Saver(max_to_keep=1) | |
sess.run(var.initializer) | |
i = 0 | |
while True: |
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