Ejemplos de a2c en Python

Ejemplo n.º 1

Archivo: slurm_experiment.py Proyecto: vwxyzjn/autonomous-learning-library

def main():
    device = 'cuda'
    envs = [
        AtariEnvironment(env, device)
        for env in ['Pong', 'Breakout', 'SpaceInvaders']
    ]
    SlurmExperiment(a2c(device=device),
                    envs,
                    1e6,
                    sbatch_args={'partition': '1080ti-short'})

Ejemplo n.º 2

Archivo: atari40.py Proyecto: vwxyzjn/autonomous-learning-library

def main():
    agents = [
        atari.a2c(),
        atari.c51(),
        atari.dqn(),
        atari.ddqn(),
        atari.ppo(),
        atari.rainbow(),
    ]
    envs = [
        AtariEnvironment(env, device='cuda')
        for env in ['BeamRider', 'Breakout', 'Pong', 'Qbert', 'SpaceInvaders']
    ]
    SlurmExperiment(agents,
                    envs,
                    10e6,
                    sbatch_args={'partition': '1080ti-long'})

Ejemplo n.º 3

 def test_a2c_cuda(self):
     validate_agent(a2c(device=CUDA),
                    AtariEnvironment("Breakout", device=CUDA))

Ejemplo n.º 4

 def test_a2c(self):
     validate_agent(a2c(device=CPU), AtariEnvironment("Breakout",
                                                      device=CPU))

Ejemplo n.º 5

'''
Run the rull atari suite on swarm with a2c.
You should modify this script to suit your needs.
'''
from gym import envs
from all.experiments import SlurmExperiment
from all.presets.atari import a2c
from all.environments import GymEnvironment

# Use the first available GPU
device = 'cuda'

# Get all atari envs.
# Note that this actually returns some games that aren't compatible.
# Those slurm tasks will simply fail.
envs = [
    GymEnvironment(env, device) for env in envs.registry.env_specs.keys()
    if 'NoFrameskip-v4' in env and not '-ram' in env
]

SlurmExperiment(
    a2c(device=device),
    envs,
    1e9,
    sbatch_args={
        'partition': '1080ti-long'  # long queue: run for a week
    })

Ejemplo n.º 6

Archivo: slurm_atari.py Proyecto: eco-energy/autonomous-learning-library

'''
Quick demo of a2c running on slurm.
Note that it only runs for 1 million frames.
For real experiments, you will surely need a modified version of this script.
'''
from gym import envs
from all.experiments import SlurmExperiment
from all.presets.atari import a2c
from all.environments import AtariEnvironment

device = 'cuda'
envs = [
    AtariEnvironment(env, device)
    for env in ['Pong', 'Breakout', 'SpaceInvaders']
]
SlurmExperiment(a2c(device=device),
                envs,
                1e6,
                sbatch_args={'partition': '1080ti-short'})

Ejemplo n.º 7

'''
Quick demo of a2c running on slurm, a distributed cluster.
Note that it only runs for 1 million frames.
For real experiments, you will surely need a modified version of this script.
'''
from gym import envs
from all.experiments import SlurmExperiment
from all.presets.atari import a2c
from all.environments import AtariEnvironment

device = 'cuda'
envs = [AtariEnvironment(env, device) for env in ['Pong', 'Breakout', 'SpaceInvaders']]
SlurmExperiment(a2c(device=device), envs, 1e6, sbatch_args={
    'partition': '1080ti-short'
})