class WandbMetricHandler(MetricHandlerBase):
def __init__(self, *args, **kwargs):
self.run = None
super(WandbMetricHandler, self).__init__("wandb", *args, **kwargs)
def collect(self, collection, time, mode='train'):
if self.run is None:
import wandb
self.run = wandb.init(project='deep-rl-pytorch')
self.run.log(dict(collection), step=time)
pass
if __name__ == '__main__':
configure(
logging=dict(handlers=["file", "matplotlib", WandbMetricHandler]), )
# Set mp method to spawn
# Fork does not play well with pytorch
mp.set_start_method('spawn')
parser = argparse.ArgumentParser()
parser.add_argument('name', type=str, help='Experiment name')
args = parser.parse_args()
name = args.name
package_name = 'experiments.%s' % name.replace('-', '_')
package = __import__(package_name, fromlist=[''])
default_args = package.default_args
trainer = make_trainer(name, **default_args())
import argparse
from deep_rl import make_trainer
import deep_rl
import torch.multiprocessing as mp
from configuration import configuration
from deep_rl.common.torchsummary import get_shape
if __name__ == '__main__':
# Set mp method to spawn
# Fork does not play well with pytorch
mp.set_start_method('spawn')
deep_rl.configure(**configuration)
parser = argparse.ArgumentParser()
parser.add_argument('name', type=str, help='Experiment name')
args = parser.parse_args()
name = args.name
package_name = 'experiments.%s' % name.replace('-', '_')
package = __import__(package_name, fromlist=[''])
default_args = package.default_args
trainer = make_trainer(name, **default_args())
trainer.test()
import argparse
from deep_rl import make_trainer, configure
import torch.multiprocessing as mp
if __name__ == '__main__':
configure(visdom=dict(server='http://localhost', port=8097))
# Set mp method to spawn
# Fork does not play well with pytorch
mp.set_start_method('spawn')
parser = argparse.ArgumentParser()
parser.add_argument('name', type=str, help='Experiment name')
args = parser.parse_args()
name = args.name
package_name = 'experiments.%s' % name.replace('-', '_')
package = __import__(package_name, fromlist=[''])
default_args = package.default_args
trainer = make_trainer(name, **default_args())
trainer.run()