- スーパーコンピュータ. 小柳義夫 [ほか] 著. 岩波書店, 2012 (岩波講座計算科学:別巻).
- コンパイラの構成と最適化, 第2版. 中田育男著. 朝倉書店, 2009.
- 宇宙ロケット工学入門. 宮澤政文著. 朝倉書店, 2016.
- ネットワーク分析, 第2版. 鈴木努著. 共立出版, 2017 (Rで学ぶデータサイエンス:8).
- きつねさんでもわかるLLVM : コンパイラを自作するためのガイドブック. 柏木餅子, 風薬著/矢上栄一イラスト. インプレスジャパン/インプレスコミュニケーションズ, 2013.
- Chainer v2による実践深層学習. 新納浩幸著. オーム社, 2017.
- 異常検知と変化検知. 井手剛, 杉山将著. 講談社, 2015 (MLP機械学習プロフェッショナルシリーズ).
- 基礎からわかる時系列分析 : Rで実践するカルマンフィルタ・MCMC・粒子フィルタ. 萩原淳一郎, 瓜生真也, 牧山幸史著. 技術評論社, 2018 (Data science library).
- データ分析プロセス. 福島真太朗著. 共立出版, 2015 (シリーズUseful R:2).
- Rで学ぶクラスタ解析. 新納浩幸著. オーム社, 2007.
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/****************************************************************************************** | |
Copyright (C) 2008 Niklas Sondell, Storm Weather Center | |
This file is part of wgrib2 and could be distributed under terms of the GNU General Public License | |
*/ | |
#include <stdio.h> | |
#include <stdlib.h> | |
#include <string.h> | |
#include "grb2.h" |
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/****************************************************************************************** | |
Copyright (C) 2008 Niklas Sondell, Storm Weather Center | |
This file is part of wgrib2 and could be distributed under terms of the GNU General Public License | |
*/ | |
#include <stdio.h> | |
#include <stdlib.h> | |
#include <string.h> | |
#include "grb2.h" |
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from PIL import Image | |
import numpy as np | |
import argparse | |
import glob | |
import sys | |
import concurrent.futures | |
def is_gray_scale(path): | |
try: |
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import pynvml | |
pynvml.nvmlInit() | |
handle0 = pynvml.nvmlDeviceGetHandleByIndex(0) | |
handle1 = pynvml.nvmlDeviceGetHandleByIndex(1) | |
util_rate0 = pynvml.nvmlDeviceGetUtilizationRates(handle0) | |
util_rate1 = pynvml.nvmlDeviceGetUtilizationRates(handle1) |
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import argparse | |
import csv | |
import json | |
import glob | |
import numpy as np | |
parser = argparse.ArgumentParser() | |
parser.add_argument('--input', type=str, required=True) | |
parser.add_argument('--output', default='result.csv') | |
args = parser.parse_args() |
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#include <stdio.h> | |
#include <nvml.h> | |
int main(int argc, char **argv) | |
{ | |
nvmlReturn_t result; | |
result = nvmlInit(); | |
if (NVML_SUCCESS != result) | |
{ |
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diff --git a/digdag-standards/src/main/java/io/digdag/standards/operator/td/BaseTdJobOperator.java b/digdag-standards/src/main/java/io/digdag/standards/operator/td/BaseTdJobOperator.java | |
index 386a1499e..15c22ecd4 100644 | |
--- a/digdag-standards/src/main/java/io/digdag/standards/operator/td/BaseTdJobOperator.java | |
+++ b/digdag-standards/src/main/java/io/digdag/standards/operator/td/BaseTdJobOperator.java | |
@@ -61,7 +61,10 @@ abstract class BaseTdJobOperator | |
// Set last_job_id param | |
taskResult.getStoreParams() | |
.getNestedOrSetEmpty("td") | |
- .set("last_job_id", job.getJobId()); | |
+ .set("last_job_id", job.getJobId()) // for compatibility with old style |
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import os | |
import time | |
import random | |
import digdag | |
class ParamSet(object): | |
def set_param(self): | |
time.sleep(int(os.environ['sleep'])) | |
digdag.env.store({'value': os.environ['value']}) | |
print(f"{os.environ['value']} finished") |