start new:
tmux
start new with session name:
tmux new -s myname
Gabriele Angeletti gabrieleangeletti
📖
farrajota
/ multiple_learning_rates.lua
Last active
April 10, 2018 16:47
Example code for how to set different learning rates per layer. Note that when calling :parameters(), the weights and bias of a given layer are separate, consecutive tensors. Therefore, when calling :parameters(), a network with N layers will output a table with N*2 tensors, where the i'th and i'th+1 tensors belong to the same layer.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| -- 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)) |
MohamedAlaa
/ tmux-cheatsheet.markdown
Last active
November 15, 2024 09:51
tmux shortcuts & cheatsheet