vbkaisetsu

vim.cmd[[packadd packer.nvim]]

require'packer'.startup(function()
  use'tpope/vim-fugitive'
  use'tpope/vim-repeat'

  use{'wbthomason/packer.nvim', opt = true}

  use{'rhysd/git-messenger.vim', opt = true, cmd = {'GitMessenger'}}

vbkaisetsu

use std::cell::RefCell;
use std::rc::Rc;

use html5ever::{Attribute, LocalName, QualName};
use html5ever::driver::ParseOpts;
use html5ever::{local_name, ns, namespace_url};
use html5ever::{parse_document, parse_fragment};
use html5ever::rcdom::{Handle, Node, NodeData, RcDom};
use html5ever::serialize;
use html5ever::serialize::SerializeOpts;

vbkaisetsu

#include <algorithm>
#include <chrono>
#include <functional>
#include <iostream>
#include <random>

#define CL_HPP_ENABLE_EXCEPTIONS
#define CL_HPP_MINIMUM_OPENCL_VERSION 120
#define CL_HPP_TARGET_OPENCL_VERSION 120
#define CL_HPP_CL_1_2_DEFAULT_BUILD

vbkaisetsu

#!/bin/bash -xe

ABSPATH=$(realpath $0)
DIRNAME=$(dirname ${ABSPATH})

ANDROID_NDK_PATH=/path/to/Android/Sdk/ndk-bundle
ANDROID_ABI=armeabi-v7a
ANDROID_PLATFORM=android-15
OPENCL_INCLUDE_DIR=${DIRNAME}/OpenCL/include
OPENCL_LIBRARY=${DIRNAME}/OpenCL/lib/libOpenCL.so

vbkaisetsu

(ns xor-example.core
  (:import
    [primitiv Device Graph Parameter Shape]
    [primitiv functions functions$batch]
    [primitiv.devices Naive]
    [primitiv.initializers XavierUniform Constant]
    [primitiv.optimizers SGD]))


(defn -main []

vbkaisetsu

#define REDUCE(k, GROUP_SIZE) \
  if (GROUP_SIZE >= k << 1) { \
    if (tid < k) { \
      if (max_val[tid + k] > max_val[tid]) { \
        max_val[tid] = max_val[tid + k]; \
        argmax_val[tid] = argmax_val[tid + k]; \
      } \
    } \
    barrier(CLK_LOCAL_MEM_FENCE); \
  }

vbkaisetsu

#!/usr/bin/env python3

#
# Burrows Wheeler Transform implemented in Python
# Currently, list.sort() is not the radix sort, so the algorithm order is O(n log n log n).
# This algorithm replaces items of arr to integers, so we can use the radix sort instead.
# In that case, the algorithm order becomes O(n log n).
#

from operator import itemgetter

vbkaisetsu

#!/usr/bin/env python3

from typing import TypeVar, Generic, Any, List
from abc import ABCMeta, abstractmethod
from itertools import dropwhile, zip_longest


def euclid_gcd(a, b):
    x = a.zero()
    y = a.identity()

vbkaisetsu

#!/usr/bin/env python3

# Efficient online and batch learning using forward backward splitting
# John Duchi and Yoram Singer
# Journal of Machine Learning Research 10 (2009) 2899-2934
# http://www.jmlr.org/papers/volume10/duchi09a/duchi09a.pdf

# Efficient Elastic Net Regularization for Sparse Linear Models
# Zachary C. Lipton and Charles Elkan (2015)
# https://arxiv.org/pdf/1505.06449.pdf

vbkaisetsu

#!/usr/bin/env python3

from itertools import chain


def ranges_or(ranges):
    result = []
    depth = 0
    for p, t in sorted(chain.from_iterable(((x, -1), (y, 1)) for x, y in ranges)):
        if depth == 0 and t == -1: