| import scipy.misc as misc | |
| import numpy as np | |
| len_target = 20 | |
| v = 60 # Vocabulary size | |
| T = .9 # Temperature | |
| max_edits = len_target | |
| x = np.zeros(max_edits) | |
| for n_edits in range(max_edits): |
| sudo apt-get remove --purge vim vim-runtime vim-gnome vim-tiny vim-gui-common | |
| sudo apt-get install liblua5.1-dev luajit libluajit-5.1 python-dev ruby-dev libperl-dev libncurses5-dev libatk1.0-dev libx11-dev libxpm-dev libxt-dev | |
| #Optional: so vim can be uninstalled again via `dpkg -r vim` | |
| sudo apt-get install checkinstall | |
| sudo rm -rf /usr/local/share/vim /usr/bin/vim | |
| cd ~ |
Trained by me using https://github.com/soumith/imagenet-multiGPU.torch, achieves 62.6% top1 center crop accuracy on ImageNet validation set. Tested here: https://github.com/szagoruyko/imagenet-validation.torch
Download links:
| --[[ | |
| This layer expects an [n x d] Tensor and normalizes each | |
| row to have unit L2 norm. | |
| ]]-- | |
| local L2Normalize, parent = torch.class('nn.L2Normalize', 'nn.Module') | |
| function L2Normalize:__init() | |
| parent.__init(self) | |
| end | |
| function L2Normalize:updateOutput(input) |
| -- multiple learning rates per network. Optimizes two copies of a model network and checks if the optimization steps (2) and (3) produce the same weights/parameters. | |
| require 'torch' | |
| require 'nn' | |
| require 'optim' | |
| torch.setdefaulttensortype('torch.FloatTensor') | |
| -- (1) Define a model for this example. | |
| local model = nn.Sequential() | |
| model:add(nn.Linear(10,20)) |
| -- multiple learning rates per network. Optimizes two copies of a model network and checks if the optimization steps (2) and (3) produce the same weights/parameters. | |
| require 'torch' | |
| require 'nn' | |
| require 'optim' | |
| torch.setdefaulttensortype('torch.FloatTensor') | |
| -- (1) Define a model for this example. | |
| local model = nn.Sequential() | |
| model:add(nn.Linear(10,20)) |
| # Latex files | |
| *.aux | |
| *.glo | |
| *.idx | |
| *.log | |
| *.toc | |
| *.ist | |
| *.acn | |
| *.acr |