GitHub - Element-Research/rnn: Recurrent Neural Network library for Torch7's nn
Note: this repository is deprecated in favor of https://github.com/torch/rnn. This is a Recurrent Neural Network library that extends Torch's nn. You can use it to build RNNs, LSTMs, GRUs, BRNNs, BLSTMs, and so forth and so on. This library includes documentation for the following objects: Modules that consider successive calls to forward as different time-steps in a sequence : AbstractRecurrent :
Torch | Scientific computing for LuaJIT.
What is Torch? Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation. A summary of core features: a powerful N-dimensional array lots of routines for indexing, slicing, transposing, … amazing interface to C, via
Torch7ã®åˆ†ã‹ã‚Šã«ãã„話 - デー
FacebookãŒtorchã®æ‹¡å¼µã‚’公開ã—ãŸã“ã¨ã‚‚ã‚ã‚Šã€torchを使ã£ã¦ã¿ã¦ã„る方も出始ã‚ãŸã‚ˆã†ãªã®ã§ã€è‡ªåˆ†ãŒtorchã§ä½¿ã†ä¸Šã§åˆ†ã‹ã‚Šã«ãã‹ã£ãŸã“ã¨ã‚„ãƒãƒžã£ãŸã“ã¨ãªã©ã‚’上ã’ã¦ã„ãã¾ã™ã€‚ ã‚る程度使ã£ã¦ã„る方をå‰æã¨ã—ã¦ã„ã¾ã™ã€‚ ã²ã©ã„ã“ã¨ã‚’ãŸãã•ã‚“書ãã¾ã™ãŒã€torchãŒå«Œã„ãªã‚ã‘ã§ã¯ã‚ã‚Šã¾ã›ã‚“。torchã¯ã‚µã‚¤ã‚³ãƒ¼ã§ã™ã€‚ リリースやãƒãƒ¼ã‚¸ãƒ§ãƒ³ã«ã¤ã„㦠ezinstallã¯gitã®ãƒªãƒã‚¸ãƒˆãƒªã‚’cloneã—ã¦ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã—ã¾ã™ã€‚torchã¯ä»Šã®ã¨ã“ã‚リリースã®ç®¡ç†ãªã©ã—ã¦ã„ãªãã¦ã€æ—¥ã€…æ›´æ–°ã•ã‚Œã‚‹é–‹ç™ºãƒªãƒã‚¸ãƒˆãƒªãŒã‚ã‚‹ã ã‘ãªã®ã§ã€ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã—ãŸæ—¥ã«ã‚ˆã£ã¦ç•°ãªã‚‹ãƒãƒ¼ã‚¸ãƒ§ãƒ³ãŒã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã•ã‚Œã¾ã™ã€‚ ãŸã¾ã«ä»¥ä¸‹ã®ã‚ˆã†ãªã‚³ãƒžãƒ³ãƒ‰ã‚’実行ã—ã¦æ›´æ–°ã—ãŸã»ã†ãŒã„ã„ã§ã™ã€‚ #!/bin/sh sudo luarocks install cwrap sudo luarocks install torch su
Torch7 ã®ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ« - ã®ã‚“ã³ã‚Šã—ã¦ã„るエンジニアã®æ—¥è¨˜
皆ã•ã‚“ã“ã‚“ã«ã¡ã¯ ãŠå…ƒæ°—ã§ã™ã‹ã€‚ç§ã¯å…ƒæ°—ã§ã™ã€‚ FacebookãŒä¸€éƒ¨ã‚’オープンソースã«ã—ãŸã¨ã‹ã§ã€æœ€è¿‘話題ã®Torch7ã«ã¤ã„ã¦è¨˜è¼‰ã—ã¦ã¿ãŸã€‚ Torch7ã¨ã¯ï¼Ÿ http://torch.ch/:enable 科å¦æŠ€è¡“計算ã®ç‚ºã®ã€æ©Ÿæ¢°å¦ç¿’ライブラリã§ã€LuaJITã§å‹•ä½œã—ã¾ã™ã€‚ CUDAãªã©ã®GPUã«ã¤ã„ã¦ã‚‚実装ã•ã‚Œã¦ã„ã¾ã™ã€‚ Install å…¬å¼ãƒ›ãƒ¼ãƒ ページ通りã§åŸºæœ¬ã¯å•é¡Œã‚ã‚Šã¾ã›ã‚“ãŒä¸€ç®‡æ‰€ã ã‘変更ã—ã¦ãŠã„ãŸã»ã†ãŒè‰¯ã„箇所ãŒã‚ã‚Šã¾ã™ã€‚ curl -sk https://raw.githubusercontent.com/torch/ezinstall/master/install-deps | bash git clone https://github.com/torch/distro.git ~/torch --recursive cd ~/torch; ./install.sh
GitHub - torch/torch7: http://torch.ch
Torch is not in active developement. The functionality provided by the C backend of Torch, which are the TH, THNN, THC, THCUNN libraries is actively extended and re-written in the ATen C++11 library (source, mirror). ATen exposes all operators you would expect from torch7, nn, cutorch, and cunn directly in C++11 and includes additional support for sparse tensors and distributed operations. It is t
Torch vs Theano - FastML
Recently we took a look at Torch 7 and found its data ingestion facilities less than impressive. Torch’s biggest competitor seems to be Theano, a popular deep-learning framework for Python. These two have been having “who is faster†competition going for a few years now. It’s been documented in the following papers: J. Bergstra, O. Breuleux, F. Bastien, P. Lamblin, R. Pascanu, G. Desjardins, J. Tu
[MLAC 2013 7日目] Torch7ã§ãŠæ‰‹è»½ãƒ‹ãƒ¥ãƒ¼ãƒ©ãƒ«ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ - a lonely miner
ã¯ã˜ã‚ã« ã“ã®è¨˜äº‹ã¯ Machine Learning Advent Calendar 2013 ã® 7日目ã®è¨˜äº‹ã§ã™ï¼Ž 2013年，Deep Learning もアカデミックレベルã§ã¯ã•ã¾ã–ã¾ãªåˆ†é‡Žã¸ã®æµ¸é€ãŒé€²ã¿ï¼Œãƒã‚ºãƒ¯ãƒ¼ãƒ‰ã®åŸŸã‚’脱ã—ãŸã‚ˆã†ã«æ€ãˆã¾ã™ï¼Ž ã“ã‚Œã¾ã§ã¯ï¼Œæ©Ÿæ¢°å¦ç¿’ã¨ã„ã†ã¨ï¼Œå¿œç”¨åˆ†é‡Žã«ãŠã„ã¦ã¯(分類/回帰ã¨ã„ã£ãŸ)タスクを決ã‚ã¦ã—ã¾ã£ãŸä¸Šã§ãƒ–ラックボックスã¨ã—㦠扱ã†ã‚‚ã®ï¼Œã¨ã„ã†ç©ºæ°—ãŒã‚ã‚Šã¾ã—ãŸãŒï¼Œ Deep Learning ã«ä»£è¡¨ã•ã‚Œã‚‹æŸ”軟ãªï¼Œã„ã‹ã‚ˆã†ã«ã‚‚組ã¿ä¸Šã’られるモデルã¯ï¼Œå•é¡Œã®æ€§è³ªã‚’ç©æ¥µçš„ã«(特徴é‡ã¨ã—ã¦ã§ã¯ãªã，モデル自体ã«)組ã¿è¾¼ã‚€ã“ã¨ã‚’容易ã«ã™ã‚‹ï¼Œå¤§ããªæ¦å™¨ã«ãªã‚‹ã®ã§ã¯ãªã„ã‹ã¨æ„Ÿã˜ã¦ã„ã¾ã™ï¼Ž ç´ æ€§ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ãƒªãƒ³ã‚° vs モデルパラメータエンジニアリング ã®ä¸æ¯›ãªæˆ¦ã„ãŒå¹•ã‚’上ã’ãŸï¼Œã¨ã„ã†è¦‹æ–¹ã‚‚ã§ãã¡ã‚ƒã„ãã†ã§ã™ãŒãƒ»ãƒ»ãƒ»ï¼Žï¼Ž ã•ã¦ä»Šå›žã¯ï¼Œ Torch7 ã¨ã„ã†ï¼ŒNe
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http://learning.cs.toronto.edu/wp-content/uploads/2015/02/torch_tutorial.pdf
GitHub - facebookarchive/iTorch: IPython kernel for Torch with visualization and plotting
http://code.cogbits.com/wiki/doku.php?id=start
Meta Research News | Meta Research
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