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Implement repr, hash, and richcompare for ObjectIDs. (#33)

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* Implement repr, hash, and richcompare for ObjectIDs.

* Addressing comments.

* Partially fix example applications.
This commit is contained in:
Robert Nishihara
2016-11-11 09:18:36 -08:00
committed by Philipp Moritz
parent 9d1e750e8f
commit 336a904404
8 changed files with 127 additions and 87 deletions
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examples/hyperopt/driver.py
+1 -9
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@@ -10,21 +10,13 @@ from tensorflow.examples.tutorials.mnist import input_data
import hyperopt
parser = argparse.ArgumentParser(description="Run the hyperparameter optimization example.")
parser.add_argument("--node-ip-address", default=None, type=str, help="The IP address of this node.")
parser.add_argument("--scheduler-address", default=None, type=str, help="The address of the scheduler.")
parser.add_argument("--trials", default=2, type=int, help="The number of random trials to do.")
parser.add_argument("--steps", default=10, type=int, help="The number of steps of training to do per network.")
if __name__ == "__main__":
args = parser.parse_args()
# If node_ip_address and scheduler_address are provided, then this command
# will connect the driver to the existing scheduler. If not, it will start
# a local scheduler and connect to it.
ray.init(start_ray_local=(args.node_ip_address is None),
node_ip_address=args.node_ip_address,
scheduler_address=args.scheduler_address,
num_workers=(10 if args.node_ip_address is None else None))
ray.init(start_ray_local=True, num_workers=10)
# The number of sets of random hyperparameters to try.
trials = args.trials