Deep Learning Frameworks – Keras 応用 & PyTorch, MXNet, Caffe2 ドã‚ュメント – クラスã‚ャット
PyTorch : PyTorch 0.1.12 リリースノート PyTorch 0.1.12 ãŒãƒªãƒªãƒ¼ã‚¹ã•ã‚Œã¾ã—ãŸã®ã§ã€ãƒªãƒªãƒ¼ã‚¹ãƒŽãƒ¼ãƒˆã‚’翻訳ã—ã¦ãŠãã¾ã—ãŸã€‚ [ 詳細 ] (05/05/2017) PyTorch : Tutorial åˆç´š : 分類器を訓練ã™ã‚‹ – CIFAR-10 一般ã«ç”»åƒãƒ»ãƒ†ã‚スト・音声ã‚ã‚‹ã„ã¯ãƒ“デオデータを扱ã‚ãªã‘ã‚Œã°ãªã‚‰ãªã„時ã€ãƒ‡ãƒ¼ã‚¿ã‚’ numpy é…列ã«ãƒãƒ¼ãƒ‰ã™ã‚‹æ¨™æº– python パッケージãŒä½¿ç”¨ã§ãã¾ã™ã€‚ãã‚Œã‹ã‚‰ã“ã®é…列を torch.*Tensor ã«å¤‰æ›ã§ãã¾ã™ã€‚ ç”»åƒã«ã¤ã„ã¦ã¯ã€Pillow, OpenCV ã®ã‚ˆã†ãªãƒ‘ッケージãŒæœ‰ç”¨ã§ã™ã€‚ 音声ã«ã¤ã„ã¦ã¯ã€scipy 㨠librosa。 テã‚ストã«ã¤ã„ã¦ã¯ã€ç”Ÿã® Python ã‚ã‚‹ã„㯠Cython ベースã®ãƒãƒ¼ãƒ‰ã€ã‚ã‚‹ã„㯠NLTK 㨠SpaCy ãŒæœ‰ç”¨ã§ã™ã€‚ ビジョンã«ã¤ã„ã¦ã¯ã€torchv
Why AI and machine learning researchers are beginning to embrace PyTorch
Data Show, I spoke with Soumith Chintala, AI research engineer at Facebook. Among his many research projects, Chintala was part of the team behind DCGAN (Deep Convolutional Generative Adversarial Networks), a widely cited paper that introduced a set of neural network architectures for unsupervised learning. Our conversation centered around PyTorch, the successor to the popular Torch scientific com
シンプルãªGANã®å®Ÿè£… - akmtn記録
GANã®è«–文をèªã‚“ã ã¤ã„ã§ã«MNIST用ã«å®Ÿè£…ã—ã¾ã—ãŸï¼Ž ãƒãƒƒãƒˆãƒ¯ãƒ¼ã‚¯ã«ã¯ï¼ŒConvolutionを使ã‚ãšï¼Œå¤šå±¤ãƒ‹ãƒ¥ãƒ¼ãƒ©ãƒ«ãƒãƒƒãƒˆã§ã™ï¼Žå±¤ã®æ•°ï¼Œæ´»æ€§åŒ–関数やãƒãƒƒãƒæ£è¦åŒ–ãªã©ã®è¨å®šã¯ã¦ãã¨ã†ã§ã™ï¼Žãªã®ã§GANã‚‚ã©ãã§ã™ï¼Ž ãŒã‚“ã‚‚ã©ã pytorchã§å®Ÿè£…ã—ãŸã‹ã£ãŸã®ã§ï¼Œæœ¬å®¶ã®DCGANã®ã‚³ãƒ¼ãƒ‰ã‚’å‚考ã«ã—ãªãŒã‚‰æ›¸ãã¾ã—ãŸï¼Ž github.com ã¾ãŸï¼Œã“ã¡ã‚‰ã®æ–¹ã®å®Ÿè£…ã‚‚å‚考ã«ã—ã¾ã—ãŸï¼Ž(keras) yusuke-ujitoko.hatenablog.com çµæžœã¨ã—ã¦ï¼Œä»¥ä¸‹ã®ã‚ˆã†ãªå‡ºåŠ›ã‚’å¾—ã¾ã—ãŸï¼Ž ãã‚Œãªã‚Šã«æ•°å—ã«ã¯è¦‹ãˆã¾ã™ãŒï¼Œï¼‘ãŒå¤šã„一方，２ãŒå°‘ãªã„ã¨ã„ã†åã‚ŠãŒã‚ã‚Šã¾ã—ãŸï¼Ž 一応，コードã¯ã“ã“ã«ã‚ã‚Šã¾ã™ï¼Ž
Generative Adversarial Networks (GANs) in 50 lines of code (PyTorch)
In 2014, Ian Goodfellow and his colleagues at the University of Montreal published a stunning paper introducing the world to GANs, or generative adversarial networks. Through an innovative combination of computational graphs and game theory they showed that, given enough modeling power, two models fighting against each other would be able to co-train through plain old backpropagation. The models p
Deep Learningã‚’ã‚„ã‚‹ãªã‚‰TensorflowよりもPyTorch! | ITANDI Blog
ã“ã‚“ã«ã¡ã¯ã€ã‚¨ãƒ³ã‚¸ãƒ‹ã‚¢ã®å»ºä¸‰ã§ã™ã€‚ Deep Learningã®ãƒ©ã‚¤ãƒ–ラリã¨è¨€ãˆã°TensorflowãŒæœ‰åã§ã™ã‚ˆã。１年åŠå‰ã«ãƒªãƒªãƒ¼ã‚¹ã•ã‚Œã¦ä»¥æ¥ã€ä¸€çž¬ã«ã—ã¦çŸ¥å度を手ã«ã—ã¾ã—ãŸã€‚僕ã¯ãã®é ƒDeep Learningを勉強ã—ã¦ã„ãŸã®ã§ã€Hacker Newsã§TensorflowãŒãƒã‚ºã£ã¦ã‚‹ã®ã‚’見ã¦ä½•ã¨ãªã僕も興奮ã—ã¦ã„ãŸã®ã‚’覚ãˆã¦ã„ã¾ã™ã€‚ã—ã‹ã—早速使ã£ã¦ã¿ã‚ˆã†ã¨æ€ã„ãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ«ã‚’進ã‚ãŸã‚‚ã®ã®ã€LSTMã‚„CNNã®ä½œã‚Šæ–¹ãŒåˆ†ã‹ã‚‰ãšæ–念ã—ã¾ã—ãŸã€‚ 僕㯠Stanfordã®ã‚³ãƒ¼ã‚¹ ã§Deep Learningを勉強ã—ãŸã‚“ã§ã™ãŒï¼ˆç„¡æ–™ã§ã‚¯ã‚ªãƒªãƒ†ã‚£è¶…高ã„ã§ã™ï¼‰ã‚¤ãƒ³ã‚¹ãƒˆãƒ©ã‚¯ã‚¿ãƒ¼ã®Andrej Karpathyã¯TensorflowよりもTorchを勧ã‚ã¦ã„ã¾ã—ãŸã€‚ホームワークã¯numpyを使ã†ã‚“ã§ã™ãŒã€ã‚¢ãƒ¼ã‚テクãƒãƒ£ãŒæ£ã«Torchã®Python版ã¨ã„ã†æ„Ÿã˜ã§ã€ã™ã”ãã—ã£ãã‚Šãã‚‹ã‚“ã§ã™ã‚ˆã。ãã‚Œã¾ã§
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Easy way to switch between CPU and cuda · Issue #1668 · pytorch/pytorch
GitHub - pytorch/examples: A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
GitHub - yunjey/pytorch-tutorial: PyTorch Tutorial for Deep Learning Researchers
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