mikigom

import numpy as np
from sklearn.metrics import roc_auc_score

n_class_0 = 50000
n_class_1 = 100

def main():
    # Suppose imblanced classification dataset
    labels = n_class_0 * [False] + n_class_1 * [True]
    y_true = n_class_0 * [0] + n_class_1 * [1]

mikigom

import ogr
import osr

high_ref = osr.SpatialReference()
low_ref = osr.SpatialReference()

coord_topleft = pixel2coord(high_res_raster, (col_high_res, row_high_res))

high_ref.ImportFromWkt(high_res_raster.GetProjection())
low_ref.ImportFromWkt(low_res_raster.GetProjection())

mikigom

import tensorflow as tf

"""
Author : @MikiBear_
Tensorflow Implementation of Bilinear Additive Upsampling.
Reference : https://arxiv.org/abs/1707.05847
"""
def bilinear_additive_upsampling(x, to_channel_num, name):
    from_channel_num = x.get_shape().as_list()[3]
    assert from_channel_num % to_channel_num == 0

mikigom

Task 1) Pintos Thread System

1. How the switching between threads occur?

schedule() is responsible for switching threads in threads/thread.c.

static void
schedule (void) 
{

mikigom

#include <stdio.h>
#include <string.h>
#include <stdlib.h>

struct nameTag{
    char fname[20]; char lname[20];
};

struct nameTag * wrong_getname(void){
    struct nameTag newname;

mikigom

import tensorflow as tf
slim = tf.contrib.slim

class Unet(object):
	def __init__(self, input, class_num, reuse = False):
		self.input = input
		self.reuse = reuse
		self.class_num = class_num
		self.build_model()

mikigom

module multiplexer(Y, A, B, C, D);
	output Y;
	input A, B, C, D;

	assign Y = (A&B)|(C&D);
endmodule

module D_ff(Q, CLK, D);
	output Q;
	input CLK, D;

mikigom

import subprocess
import unittest
import sys
import filecmp

bash_call = './' + sys.argv[1]

def subprocess_pipe(cmd_list):
    prev_stdin = None
    last_p = None

mikigom

#include <stdlib.h>
#include <stdio.h>
#include <string.h>
#include <unistd.h>
#include <unistd.h>
#include <wait.h>

#define CHUNK 1

char** res = NULL;

mikigom