BassyKuo

Flowey Training Menu

W232 (2022/08/01-05)

• Java programming basic knowhow

  • Code style (https://www.cs.cornell.edu/courses/JavaAndDS/JavaStyle.html)
  • for-loop, while-loop, if-else
  • Normal data type object: String, Integer, Double, Boolean, Map, List, Set

BassyKuo

@@ -622,46 +622,46 @@
   { cont.erase( std::remove( cont.begin(), cont.end(), thing ), cont.end() ); }
   
   // Error macros - output goes to stderr
-#define PRINT_ERR(m) fprintf( stderr, "\033[41merr\033[0m: "m" (%s %s)\n", __FILE__, __FUNCTION__)
-#define PRINT_ERR1(m,a) fprintf( stderr, "\033[41merr\033[0m: "m" (%s %s)\n", a, __FILE__, __FUNCTION__)    
-#define PRINT_ERR2(m,a,b) fprintf( stderr, "\033[41merr\033[0m: "m" (%s %s)\n", a, b, __FILE__, __FUNCTION__) 
-#define PRINT_ERR3(m,a,b,c) fprintf( stderr, "\033[41merr\033[0m: "m" (%s %s)\n", a, b, c, __FILE__, __FUNCTION__)
-#define PRINT_ERR4(m,a,b,c,d) fprintf( stderr, "\033[41merr\033[0m: "m" (%s %s)\n", a, b, c, d, __FILE__, __FUNCTION__)
-#define PRINT_ERR5(m,a,b,c,d,e) fprintf( stderr, "\033[41merr\033[0m: "m" (%s %s)\n", a, b, c, d, e, __FILE__, __FUNCTION__)

BassyKuo

DeepLab-LargeFOV

code from https://github.com/DrSleep/tensorflow-deeplab-lfov/blob/master/deeplab_lfov/model.py

• deeplab_v1: https://bitbucket.org/deeplab/deeplab-public/src
• deeplab_v2: https://bitbucket.org/aquariusjay/deeplab-public-ver2
• deeplab models: http://liangchiehchen.com/projects/DeepLab_Models.html

• input: inputs = tf.placeholder(tf.float32, [1, 224,224, 3])
• num_classes: num_classes = 21
• label_size: label_size = tf.shape(inputs)[1:3]

BassyKuo

000	road
001	sidewalk
002	building
003	wall
004	fence
005	pole
006	traffic light
007	traffic sign
008	vegetation
009	terrain

BassyKuo

#!/usr/bin/env python3

import tensorflow as tf   # tf.VERSION == 1.4.0
from tensorflow.contrib.tensorboard.plugins import projector

# ... write something here ...

dx, x_embedding = discriminator(x, is_training=True)
dz, z_embedding = discriminator(z, is_training=True)

BassyKuo

#!/bin/bash
#
# Uasge:
#   getpasswd 64 ~/.vnc/passwd
#

length=${1:-128}
passwdfile=${2:-$HOME/.vnc/passwd}
if su -c true $USER ; then
    head /dev/urandom | tr -dc 0-9a-zA-Z_ | head -c $length | tee /dev/tty | /usr/bin/vncpasswd -f > $passwdfile

BassyKuo

#!/usr/bin/env python3

import threading
import GPUtil
import numpy as np

gpu_loading = []

num_threads = 2
th = {}

BassyKuo

import tensorflow.contrib.slim as slim
import tensorflow as tf
import numpy as np
d_w_initializer = tf.orthogonal_initializer(1.0)
def discriminator(inputs, phase_train=True, reuse=False, use_bias=False, name="deGAN_d"):                                                       
    net = inputs
    pack = (
            # [128, tf.nn.relu, d_w_initializer],
            [128, tf.nn.relu, d_w_initializer],
            [1, None, d_w_initializer]  

BassyKuo

label count
0 2600
1 2600
2 2600
3 2600
4 2600
5 2300
6 2600
7 2600
8 2600

BassyKuo

#!/usr/bin/env python3

import threading


num_threads = 5
th = {}

def main():