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.
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import torch | |
import torch.nn as nn | |
from torch.autograd import Variable | |
from torch.nn.utils.rnn import pad_packed_sequence, pack_padded_sequence | |
x = Variable(torch.randn(10, 20, 30)).cuda() | |
lens = range(10) | |
x = pack_padded_sequence(x, lens[::-1], batch_first=True) |
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#!/usr/bin/env python | |
"""Hidden Markov Models | |
Abstract base class for HMMs and an implementation of an HMM | |
with discrete states and gaussian emissions. | |
""" | |
import tensorflow as tf | |
import edward as ed | |
from edward.models import Bernoulli, Categorical, Normal |
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import fire | |
import fastai | |
from fastai.vision import * | |
from torch import nn | |
from fastai.metrics import top_k_accuracy | |
path = untar_data(URLs.CIFAR) | |
data = ImageDataBunch.from_folder(path, valid='test') | |
class block(nn.Module): |
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#include <iostream> | |
#include <string> | |
#include <vector> | |
#include <queue> | |
#include <stack> | |
#include <algorithm> | |
using namespace std; | |
class Node{ |
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import numpy as np | |
import pymc | |
import pdb | |
def unconditionalProbability(Ptrans): | |
"""Compute the unconditional probability for the states of a | |
Markov chain.""" | |
m = Ptrans.shape[0] |
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# 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 |
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