Torch | Generating Faces with Torch
November 13, 2015 by Anders Boesen Lindbo Larsen and Søren Kaae Sønderby In this blog post we’ll implement a generative image model that converts random noise into images of faces! Code available on Github. For this task, we employ a Generative Adversarial Network (GAN) [1]. A GAN consists of two components; a generator which converts random noise into images and a discriminator which tries to dis
Torch | Recurrent Model of Visual Attention
Basically, if you feed it an image, say the classic 3x512x512 Lenna image: And you run this code on it: require 'dpnn' require 'image' img = image.lena() loc = torch.Tensor{0,0} -- 0.0 is the center of the image sg = nn.SpatialGlimpse(64, 3, 2) output = sg:forward{img, loc} print(output:size()) -- 9 x 64 x 64 -- unroll the glimpse onto its different depths outputs = torch.chunk(output, 3) display
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
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