"--task",
type=str,
default="twotargets",
- help="byheart, learnop, guessop, mixing, twotargets, addition, picoclvr, mnist, maze, snake, stack, expr, rpl, grid, qmlp",
+ help="byheart, learnop, guessop, mixing, memory, twotargets, addition, picoclvr, mnist, maze, snake, stack, expr, rpl, grid, qmlp",
)
parser.add_argument("--log_filename", type=str, default="train.log", help=" ")
"nb_train_samples": 50000,
"nb_test_samples": 10000,
},
+ "memory": {
+ "model": "4M",
+ "batch_size": 100,
+ "nb_train_samples": 5000,
+ "nb_test_samples": 1000,
+ },
"mixing": {
"model": "37M",
"batch_size": 25,
"nb_heads": 2,
"nb_blocks": 2,
},
+ "4M": {
+ "dim_model": 256,
+ "dim_keys": 32,
+ "dim_hidden": 1024,
+ "nb_heads": 4,
+ "nb_blocks": 6,
+ },
"37M": {
"dim_model": 512,
"dim_keys": 64,
sys.stdout.flush()
+log_string(f"argv {' '.join(sys.argv)}")
+
for n in vars(args):
log_string(f"args.{n} {getattr(args, n)}")
device=device,
)
+elif args.task == "memory":
+ task = tasks.SandBox(
+ problem=problems.ProblemMemory(),
+ 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 == "mixing":
task = tasks.SandBox(
problem=problems.ProblemMixing(