ArnyminerZ

import androidx.compose.runtime.Composable
import androidx.compose.runtime.DisposableEffect
import androidx.compose.runtime.remember
import androidx.compose.ui.platform.LocalContext
import androidx.compose.ui.platform.LocalLifecycleOwner
import androidx.lifecycle.Lifecycle
import androidx.lifecycle.LifecycleEventObserver
import org.osmdroid.views.MapView

@Composable

hereismari

Setting up a MSI laptop with GPU (gtx1060)

Installing Ubuntu 18.04, CUDA, CDNN, Pytorch and TensorFlow

Installing Ubuntu 18.04

Get Image

https://tutorials.ubuntu.com/tutorial/tutorial-create-a-usb-stick-on-ubuntu#0

Install (solving issues)

MFreidank

from torch.utils.data import DataLoader


class InfiniteDataLoader(DataLoader):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        # Initialize an iterator over the dataset.
        self.dataset_iterator = super().__iter__()

    def __iter__(self):

wangruohui

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.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install NVIDIA Graphics Driver via runfile
  • Remove Previous Installations (Important)
  • Download the Driver
  • Install Dependencies
  • Creat Blacklist for Nouveau Driver

• Stop lightdm/gdm/kdm