from torch import nn
from torch.nn import functional as F
+import ffutils
import mygpt, tasks
######################################################################
parser.add_argument(
"--task",
type=str,
- default="picoclvr",
- help="picoclvr, mnist, maze, snake, stack, expr, world",
+ default="sandbox",
+ help="sandbox, picoclvr, mnist, maze, snake, stack, expr, world",
)
parser.add_argument("--log_filename", type=str, default="train.log", help=" ")
parser.add_argument("--expr_input_file", type=str, default=None)
+##############################
+# World options
+
+parser.add_argument("--world_vqae_nb_epochs", type=int, default=25)
+
######################################################################
args = parser.parse_args()
######################################################################
default_args = {
+ "sandbox": {
+ "nb_epochs": 10,
+ "batch_size": 25,
+ "nb_train_samples": 25000,
+ "nb_test_samples": 10000,
+ },
"picoclvr": {
"nb_epochs": 25,
"batch_size": 25,
"nb_test_samples": 10000,
},
"world": {
- "nb_epochs": 5,
+ "nb_epochs": 10,
"batch_size": 25,
- "nb_train_samples": 10000,
+ "nb_train_samples": 25000,
"nb_test_samples": 1000,
},
}
######################################################################
-if args.task == "picoclvr":
+if args.task == "sandbox":
+ task = tasks.SandBox(
+ 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 == "picoclvr":
task = tasks.PicoCLVR(
nb_train_samples=args.nb_train_samples,
nb_test_samples=args.nb_test_samples,
nb_train_samples=args.nb_train_samples,
nb_test_samples=args.nb_test_samples,
batch_size=args.batch_size,
+ vqae_nb_epochs=args.world_vqae_nb_epochs,
+ logger=log_string,
device=device,
)