서로 다른 stance에 서서 토론하는 것을 시각적으로 잘 표현한 댓글 시스템을 만들려는 시도.
첫 프로토타입으로 나왔으나 관심을 못 받아서 묻힘-_-;
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license: gpl-3.0 |
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# Copyright (C) 2013 Istituto per l'Interscambio Scientifico I.S.I. | |
# You can contact us by email (isi@isi.it) or write to: | |
# ISI Foundation, Via Alassio 11/c, 10126 Torino, Italy. | |
# | |
# This work is licensed under a Creative Commons 4.0 | |
# Attribution-NonCommercial-ShareAlike License | |
# You may obtain a copy of the License at | |
# http://creativecommons.org/licenses/by-nc-sa/4.0/ | |
# | |
# This program was written by Andre Panisson <panisson@gmail.com> at |
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license: gpl-3.0 | |
redirect: https://observablehq.com/@d3/multi-line-chart |
글쓴이: 김정주(haje01@gmail.com)
최근 딥러닝 관련 패키지들은 대부분 CPU와 GPU를 함께 지원하고 있습니다. GPU를 사용하면 보다 빠르게 학습 결과를 낼 수 있지만, GPU를 활용하기 위해서는 NVIDIA계열의 그래픽 카드, 드라이버 S/W 그리고 CUDA의 설치를 필요로 합니다.
이 글에서는 AWS의 GPU 인스턴스와 도커를 활용해 딥러닝 패키지(Caffe)를 편리하게 사용하는 방법을 소개합니다.
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diff --git a/screen-write.c b/screen-write.c | |
index 15f8d07..8a175a6 100644 | |
--- a/screen-write.c | |
+++ b/screen-write.c | |
@@ -1334,6 +1334,7 @@ screen_write_cell(struct screen_write_ctx *ctx, const struct grid_cell *gc) | |
ctx->cells++; | |
/* If the width is zero, combine onto the previous character. */ | |
+ /* | |
if (width == 0) { |
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import tensorflow as tf | |
import numpy as np | |
import time | |
N=10000 | |
K=4 | |
MAX_ITERS = 1000 | |
start = time.time() |
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