naviocean

#!/bin/bash

# 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
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub && sudo apt update
sudo dpkg -i cuda-repo-ubuntu1804_10.0.130-1_amd64.deb

sudo apt update
sudo apt install -y cuda

naviocean

1. Install NVIDIA Driver Version 390 via apt-get

sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt-get update
sudo apt-get install nvidia-390 nvidia-modprobe

To verify installation, restart your machine with reboot and type nvidia-smi.

2. Install Cuda 9.0

naviocean

First of all your /dev/sdb isn't partitioned. I am assuming this is the disk you want to mount. Run 

sudo fdisk /dev/sdb

1. Press O and press Enter (creates a new table)

2. Press N and press Enter (creates a new partition)

3. Press P and press Enter (makes a primary partition)

4. Then press 1 and press Enter (creates it as the 1st partition)

5. Finally, press W (this will write any changes to disk)


naviocean

#https://github.com/RuiminChen/Caffe-MobileNetV2-ReLU6
FROM nvidia/cuda:9.0-devel-ubuntu16.04
MAINTAINER    NaviOcean <navi.ocean@outlook.com>
#install Cuda & Cudnn
ENV CUDNN_VERSION 7.2.1.38

LABEL com.nvidia.cudnn.version="${CUDNN_VERSION}"

RUN apt-get update && apt-get install -y --no-install-recommends apt-utils \
	libcudnn7=$CUDNN_VERSION-1+cuda9.0 \

naviocean

FROM nvidia/cuda:9.0-devel-ubuntu16.04
MAINTAINER    NaviOcean <navi.ocean@outlook.com>
#install Cuda & Cudnn
ENV CUDNN_VERSION 7.2.1.38

LABEL com.nvidia.cudnn.version="${CUDNN_VERSION}"

RUN apt-get update && apt-get install -y --no-install-recommends apt-utils \
        libcudnn7=$CUDNN_VERSION-1+cuda9.0 \
        libcudnn7-dev=$CUDNN_VERSION-1+cuda9.0 && \

naviocean

# $ nvida-docker run -it naviocean/convert

# Download base image
FROM ubuntu:16.04

# Set environment variables
ENV PATH "/usr/local/cuda-8.0/bin:$PATH"
ENV LD_LIBRARY_PATH "/usr/local/cuda-8.0/lib:$LD_LIBRARY_PATH"

# Set keyboard configuration in advance of installing CUDA

naviocean

First, git clone the MMdnn

git clone https://github.com/Microsoft/MMdnn Commit pytorch_parser.py from Line 67 to Line 76, and add model = model_file_name at Line 77.

It might look like this.

    def __init__(self, model_file_name, input_shape):
        super(PytorchParser, self).__init__()
        # if not os.path.exists(model_file_name):

naviocean

#!/bin/bash

#Update repositories list
sudo apt-get update

#Completely remove boost
sudo apt-get -y --purge remove libboost-all-dev libboost-doc libboost-dev
sudo rm -f /usr/lib/libboost_*

#Install required packages

naviocean

'''This script goes along the blog post
"Building powerful image classification models using very little data"
from blog.keras.io.
It uses data that can be downloaded at:
https://www.kaggle.com/c/dogs-vs-cats/data
In our setup, we:
- created a data/ folder
- created train/ and validation/ subfolders inside data/
- created cats/ and dogs/ subfolders inside train/ and validation/
- put the cat pictures index 0-999 in data/train/cats

naviocean

// configureStore.js
import { createStore, applyMiddleware, compose } from 'redux';
import { autoRehydrate, persistStore } from 'redux-persist';
import { localStorage } from 'redux-persist/storages';
import { rootReducer } from '../reducers';

export default function configureStore() {
  // use desired middlewares
  const middlewares = [];