dev_iter = build_iterator(dev_data, config)
for i in dev_iter:
    if i:
        print(i)
        break

$ git clone https://github.com/NVIDIA/apex
$ cd apex
$ pip3 install -v --no-cache-dir --global-option="--cpp_ext" --global-option="--cuda_ext" ./

hexo n "hexo标题 有空格 怎么办"

docker-compose     Define and run multi-container applications with Docker.
up                 Create and start containers

version: '2'

volumes:
  nextcloud:
  db:

services:
  db:
    image: mariadb
    command: --transaction-isolation=READ-COMMITTED --binlog-format=ROW
    restart: always
    volumes:
      - db:/var/lib/mysql
    environment:
      - MYSQL_ROOT_PASSWORD=123456
      - MYSQL_PASSWORD=123456
      - MYSQL_DATABASE=nextcloud
      - MYSQL_USER=nextcloud

  app:
    image: nextcloud
    ports:
      - 8080:80
    links:
      - db
    volumes:
      - nextcloud:/var/www/html
    restart: always

# Add the package repositories
$ distribution=$(. /etc/os-release;echo $ID$VERSION_ID)
$ curl -s -L https://nvidia.github.io/nvidia-docker/gpgkey | sudo apt-key add -
$ curl -s -L https://nvidia.github.io/nvidia-docker/$distribution/nvidia-docker.list | sudo tee /etc/apt/sources.list.d/nvidia-docker.list

$ sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
$ sudo systemctl restart docker


# On debian based distributions: Ubuntu / Debian
$ sudo apt-get update
$ sudo apt-get --only-upgrade install docker-ce nvidia-docker2
$ sudo systemctl restart docker

# All of the following options will continue working
#$ docker run --gpus all nvidia/cuda:9.0-base nvidia-smi
$ docker run --runtime nvidia nvidia/cuda:9.0-base nvidia-smi

import keras.backend.tensorflow_backend as KTF
import tensorflow as tf
config = tf.ConfigProto()
config.gpu_options.allow_growth=True  
sess = tf.Session(config=config)
KTF.set_session(sess)