"--task",
type=str,
default="twotargets",
- help="byheart, learnop, guessop, twotargets, addition, picoclvr, mnist, maze, snake, stack, expr, rpl, grid",
+ help="byheart, learnop, guessop, twocuts, twotargets, addition, picoclvr, mnist, maze, snake, stack, expr, rpl, grid, qmlp",
)
parser.add_argument("--log_filename", type=str, default="train.log", help=" ")
parser.add_argument("--expr_input_file", type=str, default=None)
+##############################
+# Misc
+
+parser.add_argument("--twocuts_no_global", action="store_true", default=False)
+
######################################################################
args = parser.parse_args()
"nb_train_samples": 250000,
"nb_test_samples": 10000,
},
+ "qmlp": {
+ "model": "37M",
+ "batch_size": 10,
+ "nb_train_samples": 100000,
+ "nb_test_samples": 1000,
+ },
"guessop": {
"model": "352M",
"batch_size": 25,
"nb_train_samples": 50000,
"nb_test_samples": 10000,
},
+ "twocuts": {
+ "model": "37M",
+ "batch_size": 25,
+ "nb_train_samples": 100000,
+ "nb_test_samples": 10000,
+ },
"mnist": {
"model": "37M",
"batch_size": 10,
device=device,
)
+elif args.task == "twocuts":
+ task = tasks.SandBox(
+ problem=problems.ProblemTwoCuts(global_constraint = not args.twocuts_no_global),
+ nb_train_samples=args.nb_train_samples,
+ nb_test_samples=args.nb_test_samples,
+ batch_size=args.batch_size,
+ logger=log_string,
+ device=device,
+ )
+
elif args.task == "addition":
task = tasks.SandBox(
problem=problems.ProblemAddition(),
device=device,
)
+elif args.task == "qmlp":
+ task = tasks.QMLP(
+ nb_train_samples=args.nb_train_samples,
+ nb_test_samples=args.nb_test_samples,
+ batch_size=args.batch_size,
+ result_dir=args.result_dir,
+ logger=log_string,
+ device=device,
+ )
+
else:
raise ValueError(f"Unknown task {args.task}")