jeasinema

#include "keymap_common.h"
#include "led.h"
#include "action_layer.h"

/*
 * HHKB Layout
 */
const uint8_t PROGMEM keymaps[][MATRIX_ROWS][MATRIX_COLS] = {
    /* 0: Default layer
     * ,-----------------------------------------------------------.

jeasinema

# !/bin/bash
# $date: 09-16-16 
# $purpose: basic configuration
# $author: jeasinema [jeasinema[at]gmail[dot]com]

CREATE_USER_NAME="jeasinema"

# Create account
echo "============= now create an account ============="
sudo useradd -s /usr/bin/fish -m $CREATE_USER_NAME

jeasinema

# !/bin/bash
# $date: 09-16-16 
# $purpose: basic configuration
# $author: jeasinema [jeasinema[at]gmail[dot]com]

UNAME="jeasinema"
DOT_FILE="https://github.com/jeasinema/.dotfile.git"
DOT_NAME=".dotfile"
VIM_REPO_NAME="vim-config"

jeasinema

#!/usr/bin/env python
# -*- coding:UTF-8 -*-

# File Name : train_hook.py
# Purpose :
# Creation Date : 14-12-2017
# Last Modified : 2017-12-14 Thu 00:59:06
# Created By : Jeasine Ma [jeasinema[at]gmail[dot]com]

import os

jeasinema

#!/usr/bin/env python
# -*- coding:UTF-8 -*-

# File Name : colorize.py
# Purpose :
# Creation Date : 21-12-2017
# Created By : Jeasine Ma [jeasinema[at]gmail[dot]com]

# ref: https://gist.github.com/jimfleming/c1adfdb0f526465c99409cc143dea97b

jeasinema

require 'formula'

class BsdgamesOsx < Formula
   desc 'The classic bsdgames of yore for Mac OS X and macOS.'
   homepage 'https://github.com/ctdk/bsdgames-osx'
   url 'https://github.com/ctdk/bsdgames-osx/archive/bsdgames-osx-2.19.3.tar.gz'
   sha256 '699bb294f2c431b9729320f73c7fcd9dcf4226216c15137bb81f7da157bed2a9'
   head 'https://github.com/ctdk/bsdgames-osx.git'
   version '2.19.3'
   depends_on "bsdmake" => ':build'

jeasinema

"""Simple example on how to log scalars and images to tensorboard without tensor ops.

License: Copyleft
"""
__author__ = "Jeasine Ma"

import tensorflow as tf
from PIL import Image
import numpy as np
from io import BytesIO

jeasinema

#!/usr/bin/env python
# -*- coding:UTF-8 -*-

import torch
import torch.nn as nn
import torch.nn.init as init


def weight_init(m):
    '''

jeasinema

def bar(current, total, prefix="", suffix="", bar_sz=25, end_string=None):
    '''
    Usage:
      bar(iter+1, epoch_amount, "Iters:{}/{}".format(iter, epoch_amount), end_string='')
    '''
    sp = ""
    print("\x1b[2K\r", end='')
    for i in range(bar_sz):
        if current * bar_sz // total > i:
            sp += '='

jeasinema

import torch
import torch.nn.functional as F
from torch.nn.parameter import Parameter
import numpy as np


class SpatialSoftmax(torch.nn.Module):
    def __init__(self, height, width, channel, temperature=None, data_format='NCHW'):
        super(SpatialSoftmax, self).__init__()
        self.data_format = data_format