help="Specifies Determined Experiment configuration.",
default="{}",
)
parser.add_argument("--mode",
dest="mode",
help="Specifies local mode or cluster mode.",
default="cluster")
args = parser.parse_args()
config = {
"data": {
"url":
"https://s3-us-west-2.amazonaws.com/determined-ai-test-data/pytorch_mnist.tar.gz"
},
"hyperparameters": {
"learning_rate": det.Log(minval=-3.0, maxval=-1.0, base=10),
"dropout": det.Double(minval=0.2, maxval=0.8),
"global_batch_size": det.Constant(value=64),
"n_filters1": det.Constant(value=32),
"n_filters2": det.Constant(value=32),
},
"searcher": {
"name": "single",
"metric": "validation_error",
"max_steps": 20,
"smaller_is_better": True,
},
}
config.update(json.loads(args.config))
experimental.create(
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"--config",
dest="config",
help="Specifies Determined Experiment configuration.",
default="{}",
)
parser.add_argument(
"--mode", dest="mode", help="Specifies local mode or cluster mode.", default="cluster"
)
args = parser.parse_args()
config = {
"hyperparameters": {
"learning_rate": det.Log(-4.0, -2.0, 10),
"global_batch_size": det.Constant(64),
"hidden_layer_1": det.Constant(250),
"hidden_layer_2": det.Constant(250),
"hidden_layer_3": det.Constant(250),
"dropout": det.Double(0.0, 0.5),
},
"searcher": {
"name": "single",
"metric": "accuracy",
"max_steps": 10,
"smaller_is_better": False,
},
}
config.update(json.loads(args.config))