YukiNagato’s gists

YukiNagato / Summation-of-primes.cpp

Created September 22, 2020 08:06 — forked from luochen1990/Summation-of-primes.cpp

Summation of primes https://projecteuler.net/problem=10

YukiNagato / waya-dl-setup.sh

Created April 30, 2019 13:25 — forked from mjdietzx/waya-dl-setup.sh

Install CUDA Toolkit v8.0 and cuDNN v6.0 on Ubuntu 16.04

	#!/bin/bash

	# install CUDA Toolkit v8.0
	# instructions from https://developer.nvidia.com/cuda-downloads (linux -> x86_64 -> Ubuntu -> 16.04 -> deb (network))
	CUDA_REPO_PKG="cuda-repo-ubuntu1604_8.0.61-1_amd64.deb"
	wget http://developer.download.nvidia.com/compute/cuda/repos/ubuntu1604/x86_64/${CUDA_REPO_PKG}
	sudo dpkg -i ${CUDA_REPO_PKG}
	sudo apt-get update
	sudo apt-get -y install cuda

YukiNagato / BGRA2RGBA

Created March 25, 2019 07:27 — forked from micahpearlman/BGRA2RGBA

BGRA to RGBA

	// Really awesome code taken from: http://apangborn.com/2011/05/pixel-processing-using-arm-assembly/
	inline static void neon_rgba_to_bgra(unsigned char src, unsigned char dst, int numPixels)
	{
	#ifdef __ARM_NEON__
	int simd_pixels = numPixels & ~7; // round down to nearest 8
	int simd_iterations = simd_pixels >> 3;
	int col;
	if(simd_iterations) { // make sure at least 1 iteration
	__asm__ __volatile__ ("1: \n\t"
	// structured load of 8 pixels into d0-d3 (64-bit) NEON registers

YukiNagato / infinite_dataloader.py

Created March 4, 2019 01:56 — forked from MFreidank/infinite_dataloader.py

A pytorch DataLoader that generates an unbounded/infinite number of minibatches from the dataset.

	from torch.utils.data import DataLoader


	class InfiniteDataLoader(DataLoader):
	def __init__(self, args, *kwargs):
	super().__init__(args, *kwargs)
	# Initialize an iterator over the dataset.
	self.dataset_iterator = super().__iter__()

	def __iter__(self):

YukiNagato / dict_merge.py

Created March 1, 2019 06:47 — forked from angstwad/dict_merge.py

Recursive dictionary merge in Python

	# Recursive dictionary merge
	# Copyright (C) 2016 Paul Durivage <pauldurivage+github@gmail.com>
	#
	# This program is free software: you can redistribute it and/or modify
	# it under the terms of the GNU General Public License as published by
	# the Free Software Foundation, either version 3 of the License, or
	# (at your option) any later version.
	#
	# This program is distributed in the hope that it will be useful,
	# but WITHOUT ANY WARRANTY; without even the implied warranty of

YukiNagato / README.md

Created July 23, 2018 07:33 — forked from kanhua/README.md

A template of writing C or C++ extension for python and numpy

This gist demonstrates how to setup a python project that process a numpy array from C language.

To compile the project, run

make all

To test it, run

make test

YukiNagato / upsampling-with-deconv-layer.ipynb

Created June 21, 2018 11:12 — forked from tnarihi/upsampling-with-deconv-layer.ipynb

Upsampling with DeconvolutionLayer in Caffe. Open as a notebook here: http://nbviewer.ipython.org/gist/tnarihi/54744612d35776f53278

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YukiNagato / min-char-rnn.py

Created June 15, 2018 01:12 — forked from karpathy/min-char-rnn.py

Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy

	"""
	Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
	BSD License
	"""
	import numpy as np

	# data I/O
	data = open('input.txt', 'r').read() # should be simple plain text file
	chars = list(set(data))
	data_size, vocab_size = len(data), len(chars)

Siyuan Yang YukiNagato