| # WARNING: These steps seem to not work anymore! | |
| #!/bin/bash | |
| # Purge existign CUDA first | |
| sudo apt --purge remove "cublas*" "cuda*" | |
| sudo apt --purge remove "nvidia*" | |
| # Install CUDA Toolkit 10 | |
| wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.0.130-1_amd64.deb |
| import tensorflow as tf | |
| from tensorflow.contrib.rnn import RNNCell | |
| from tensorflow.contrib.rnn import LSTMStateTuple | |
| from tensorflow.python.ops import variable_scope | |
| from tensorflow.python.ops import array_ops | |
| from tensorflow.python.ops.rnn_cell_impl import _linear | |
| from tensorflow.python.ops import math_ops | |
| from tensorflow.python.ops import nn_ops | |
| from random import random, choice | |
| def noise_generator(string, noise_level, chars): | |
| noised = "" | |
| for c in string: | |
| if random() > noise_level: | |
| noised += c | |
| if random() < noise_level: | |
| noised += choice(chars) | |
| return noised |
Starting from version 1.5, OpenFst has offered a native Python module, making the use of external wrappers like PyFst unnecessary. This has been greatly helpful since PyFst doesn't support Python 3.
$ tar xzvf openfst-1.5.4.tar.gz$ ./configure --enable-python --enable-far
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.
| #!/bin/bash | |
| # | |
| # ssh into a machine and automatically set the background | |
| # color of Mac OS X Terminal depending on the hostname. | |
| # | |
| # Installation: | |
| # 1. Save this script to /usr/local/bin/ssh-host-color | |
| # 2. chmod 755 /usr/local/bin/ssh-host-color | |
| # 3. alias ssh=/usr/local/bin/ssh-host-color | |
| # 4. export PRODUCTION_HOST="<hostname_production_server>" |