import doodad as dd
import doodad.ec2 as ec2
import doodad.ssh as ssh
import doodad.mount as mount
from doodad.utils import EXAMPLES_DIR, REPO_DIR
# Local docker
mode_docker = dd.mode.LocalDocker(
image='python:3.5',
)
# or this! Run experiment via docker on another machine through SSH
mode_ssh = dd.mode.SSHDocker(
image='python:3.5',
credentials=ssh.SSHCredentials(hostname='my.machine.name', username='******', identity_file='~/.ssh/id_rsa'),
)
# or use this!
mode_ec2=None
#mode_ec2 = dd.mode.EC2AutoconfigDocker(
# image='python:3.5',
# region='us-west-1',
# instance_type='m3.medium',
# spot_price=0.02,
#)
MY_RUN_MODE = mode_docker # CHANGE THIS
# Set up code and output directories
OUTPUT_DIR = '/example/outputs' # this is the directory visible to the target
import doodad.mount as mount
import doodad.ssh as ssh
from doodad.utils import EXAMPLES_DIR, REPO_DIR
# Local run
mode_local = dd.mode.Local()
# Local docker
mode_docker = dd.mode.LocalDocker(image="python:3.5", )
# or this! Run experiment via docker on another machine through SSH
mode_ssh = dd.mode.SSHDocker(
image="python:3.5",
credentials=ssh.SSHCredentials(
hostname="my.machine.name",
username="******",
identity_file="~/.ssh/id_rsa",
),
)
MY_RUN_MODE = mode_docker # CHANGE THIS
# Set up code and output directories
mounts = [
mount.MountLocal(local_dir=REPO_DIR, pythonpath=True), # Code
]
THIS_FILE_DIR = os.path.realpath(os.path.dirname(__file__))
dd.launch_python(
target=os.path.join(
THIS_FILE_DIR, "app_main.py"
"""
import doodad as dd
import doodad.ssh as ssh
import doodad.mount as mount
MY_USERNAME = '******'
# Use local mode to test code
mode_local = dd.mode.LocalDocker(image='justinfu/rl_base:0.1')
# Use docker mode to launch jobs on newton machine
mode_ssh = dd.mode.SSHDocker(
image='justinfu/rl_base:0.1',
credentials=ssh.SSHCredentials(hostname='newton2.banatao.berkeley.edu',
username='******',
identity_file='path/to/identity'),
)
# Set up code and output directories
OUTPUT_DIR = '/mount/outputs' # this is the directory visible to the target script inside docker
mounts = [
mount.MountLocal(local_dir='~/install/rllab',
pythonpath=True), # point to your rllab
mount.MountLocal(local_dir='~/install/gym/.mujoco',
mount_point='/root/.mujoco'), # point to your mujoco
# this output directory will be visible on the remote machine
# TODO: this directory will have root permissions. For now you need to scp your data inside your script.
mount.MountLocal(local_dir='~/data/%s' % MY_USERNAME,
mount_point=OUTPUT_DIR,
import os
import doodad as pd
import doodad.ssh as ssh
import doodad.mount as mount
from doodad.ec2.credentials import AWSCredentials
THIS_FILE_DIR = os.path.dirname(os.path.realpath(__file__))
REPO_DIR = os.path.dirname(THIS_FILE_DIR)
# or this! Run experiment via docker on another machine through SSH
mode_ssh = pd.mode.SSHDocker(
image='vitchyr/rllab-vitchyr:latest',
credentials=ssh.SSHCredentials(hostname='newton4.banatao.berkeley.edu',
username='******',
identity_file='~/.ssh/rail_lab_0617'),
)
mode_local = pd.mode.LocalDocker(image='vitchyr/rllab-vitchyr:latest', )
credentials = AWSCredentials(from_env=True)
mode_ec2 = pd.mode.EC2SpotDocker(
credentials,
image='vitchyr/rllab-vitchyr:latest',
region='us-west-1',
instance_type='c4.large',
spot_price=0.03,
s3_bucket="2-12-2017.railrl.vitchyr.rail.bucket",
terminate=True,
image_id="ami-ad81c8cd",
aws_key_name="rllab-vitchyr-us-west-1",
BASE_DIR_MOUNT = './'
DOODAD_DIR = '~/install/doodad'
DATA_DIR_MOUNT = './data'
DATA_DIR_LOCAL = './data'
THIS_FILE_DIR = os.path.realpath(os.path.dirname(__file__))
CELEBA_DIR = './data/celeba'
GPU_ID = args.gpu_id
# Local docker
mode_docker = dd.mode.LocalDocker(image=IMAGE, gpu=True, gpu_id=GPU_ID)
# Run experiment via docker on another machine through SSH
mode_ssh = dd.mode.SSHDocker(image=IMAGE,
credentials=ssh.SSHCredentials(
hostname='kelvinxx',
username='******',
identity_file='~/.ssh/id_rsa'))
# change this based on desired mode!
MY_RUN_MODE = mode_docker
# add mounts as necessary, e.g. code from other directories
mounts = [
mount.MountLocal(local_dir=DOODAD_DIR, pythonpath=True), # add doodad
mount.MountLocal(local_dir=BASE_DIR_LOCAL, mount_point=BASE_DIR_MOUNT),
mount.MountLocal(local_dir=DATA_DIR_LOCAL, mount_point=DATA_DIR_MOUNT),
mount.MountLocal(local_dir=CELEBA_DIR, mount_point=CELEBA_DIR),
mount.MountLocal(local_dir=OUTPUT_DIR_LOCAL,
mount_point=OUTPUT_DIR_MOUNT,
output=True), # output mount
]
gcp_bucket_name='umrl',
instance_type='n1-standard-8',
image_name='gpu-docker',
image_project='umrl-228204',
disk_size='100',
terminate=True,
preemptible=False,
gcp_log_prefix='experiment',
gpu=True,
gpu_kwargs=dict(num_gpu=1, gpu_model='nvidia-tesla-k80'),
image='kylehsu/umrl:latest'
)
mode_ssh = dd.mode.SSHDocker(
image='kylehsu/umrl:latest',
credentials=ssh.SSHCredentials(hostname='alan.ist.berkeley.edu', username='******', identity_file='~/.ssh/id_rsa'),
)
mode = mode_gcp
mounts = [
mount.MountLocal(local_dir=os.path.dirname(os.path.realpath(__file__)),
filter_dir=('output',))
]
output_dir = '/home/docker/store/umrl/output'
if mode == mode_gcp:
output_mount = mount.MountGCP(gcp_path='output', gcp_bucket_name='umrl', mount_point=output_dir, output=True,
include_types=('*.txt', '*.csv', '*.json', '*.gz', '*.tar', '*.log', '*.pkl',
'*.png', '*.html', '*.mp4'))
import doodad as dd
import doodad.mount as mount
import doodad.ssh as ssh
MY_USERNAME = "******"
# Use local mode to test code
mode_local = dd.mode.LocalDocker(image="justinfu/rl_base:0.1")
# Use docker mode to launch jobs on newton machine
mode_ssh = dd.mode.SSHDocker(
image="justinfu/rl_base:0.1",
credentials=ssh.SSHCredentials(
hostname="newton2.banatao.berkeley.edu",
username="******",
identity_file="path/to/identity",
),
)
# Set up code and output directories
OUTPUT_DIR = (
"/mount/outputs" # this is the directory visible to the target script inside docker
)
mounts = [
mount.MountLocal(local_dir="~/install/rllab",
pythonpath=True), # point to your rllab
mount.MountLocal(local_dir="~/install/gym/.mujoco",
mount_point="/root/.mujoco"), # point to your mujoco
# this output directory will be visible on the remote machine
# TODO: this directory will have root permissions. For now you need to scp your data inside your script.