start new:
tmux
start new with session name:
tmux new -s myname
""" | |
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
BSD License | |
""" | |
import numpy as np | |
# data I/O | |
data = open('input.txt', 'r').read() # should be simple plain text file | |
chars = list(set(data)) | |
data_size, vocab_size = len(data), len(chars) |
Picking the right architecture = Picking the right battles + Managing trade-offs
/* | |
* Note: This template uses some c++11 functions , so you have to compile it with c++11 flag. | |
* Example:- $ g++ -std=c++11 c++Template.cpp | |
* | |
* Author : Akshay Pratap Singh | |
* Handle: code_crack_01 | |
* | |
*/ | |
/******** All Required Header Files ********/ |
In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.
""" | |
Create train, valid, test iterators for CIFAR-10 [1]. | |
Easily extended to MNIST, CIFAR-100 and Imagenet. | |
[1]: https://discuss.pytorch.org/t/feedback-on-pytorch-for-kaggle-competitions/2252/4 | |
""" | |
import torch | |
import numpy as np |
import argparse | |
import torch | |
import torch.nn as nn | |
from torch.autograd import Variable | |
from torch.utils.data import DataLoader | |
import torchvision | |
import torchvision.transforms as T | |
from torchvision.datasets import ImageFolder |
set nocompatible " be iMproved, required | |
filetype off " required | |
" set the runtime path to include Vundle and initialize | |
set rtp+=~/.vim/bundle/Vundle.vim | |
call vundle#begin() | |
" alternatively, pass a path where Vundle should install plugins | |
"call vundle#begin('~/some/path/here') | |
" let Vundle manage Vundle, required |
import torch | |
import torch.nn as nn | |
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence | |
seqs = ['gigantic_string','tiny_str','medium_str'] | |
# make <pad> idx 0 | |
vocab = ['<pad>'] + sorted(set(''.join(seqs))) | |
# make model |
# Instructions for 4.14 and cuda 9.1 | |
# If upgrading from 4.13 and cuda 9.0 | |
$ sudo apt-get purge --auto-remove libcud* | |
$ sudo apt-get purge --auto-remove cuda* | |
$ sudo apt-get purge --auto-remove nvidia* | |
# also remove the container directory direcotory at /usr/local/cuda-9.0/ | |
# Important libs required with 4.14.x with Cuda 9.X | |
$ sudo apt install libelf1 libelf-dev |