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# Copyright (c) 2019-present, Thomas Wolf. | |
# All rights reserved. This source code is licensed under the MIT-style license. | |
""" A very small and self-contained gist to train a GPT-2 transformer model on wikitext-103 """ | |
import os | |
from collections import namedtuple | |
from tqdm import tqdm | |
import torch | |
import torch.nn as nn | |
from torch.utils.data import DataLoader | |
from ignite.engine import Engine, Events |
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def top_k_top_p_filtering(logits, top_k=0, top_p=0.0, filter_value=-float('Inf')): | |
""" Filter a distribution of logits using top-k and/or nucleus (top-p) filtering | |
Args: | |
logits: logits distribution shape (..., vocabulary size) | |
top_k >0: keep only top k tokens with highest probability (top-k filtering). | |
top_p >0.0: keep the top tokens with cumulative probability >= top_p (nucleus filtering). | |
""" | |
top_k = min(top_k, logits.size(-1)) # Safety check | |
if top_k > 0: | |
# Remove all tokens with a probability less than the last token of the top-k |
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// Uncompressed version of | |
// https://gist.github.com/munificent/b1bcd969063da3e6c298be070a22b604 | |
#include <time.h> // Robert Nystrom | |
#include <stdio.h> // @munificentbob | |
#include <stdlib.h> // for Ginny | |
#include <stdbool.h> // 2008-2019 | |
const int HEIGHT = 40; | |
const int WIDTH = 80; |
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/.idea/ | |
/cmake-build-debug/ | |
/dungeon |
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#!/usr/bin/env bash | |
# First download cudnn to a directory /tmp/binaries. | |
# The filename should be cudnn-9.2-linux-x64-v7.1.tgz | |
set -e | |
# Install driver | |
sudo add-apt-repository ppa:graphics-drivers/ppa | |
sudo apt-get update |
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from z3 import * | |
# find the (distinct) integers in 0..9 that make this equation work: | |
# | |
# SEND | |
# + MORE | |
# ------ | |
# MONEY | |
S = Int('S') |
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from sys import version_info | |
assert version_info.major == 3 and version_info.minor >= 3, \ | |
'requires PEP 362; Python 3.3 or later; python.org/dev/peps/pep-0362/' | |
from inspect import signature | |
class memoise(dict): | |
def __init__(self, func): | |
self.func, self.signature = func, signature(func) | |
def __missing__(self, key): | |
args, kwargs = key |
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for i in {1..100}; do | |
filepath=$(printf "http://caliban.mpipz.mpg.de/haeckel/kunstformen/Tafel_%03d_300.jpg" $i) | |
wget $filepath; | |
done |