Update.

[picoclvr.git] / main.py

diff --git a/main.py b/main.py
index 305bd3c..63e6668 100755 (executable)
--- a/main.py
+++ b/main.py
@@ -14,6 +14,7 @@ import torch, torchvision
 from torch import nn
 from torch.nn import functional as F
 
+import ffutils
 import mygpt, tasks
 
 ######################################################################
@@ -34,8 +35,8 @@ parser = argparse.ArgumentParser(
 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, rpl, world",
 )
 
 parser.add_argument("--log_filename", type=str, default="train.log", help=" ")
@@ -58,15 +59,17 @@ parser.add_argument("--learning_rate", type=float, default=1e-4)
 
 parser.add_argument("--learning_rate_schedule", type=str, default="10: 2e-5,30: 4e-6")
 
-parser.add_argument("--dim_model", type=int, default=512)
+parser.add_argument("--model", type=str, default="37M")
 
-parser.add_argument("--dim_keys", type=int, default=64)
+parser.add_argument("--dim_model", type=int, default=None)
 
-parser.add_argument("--dim_hidden", type=int, default=2048)
+parser.add_argument("--dim_keys", type=int, default=None)
 
-parser.add_argument("--nb_heads", type=int, default=8)
+parser.add_argument("--dim_hidden", type=int, default=None)
 
-parser.add_argument("--nb_blocks", type=int, default=12)
+parser.add_argument("--nb_heads", type=int, default=None)
+
+parser.add_argument("--nb_blocks", type=int, default=None)
 
 parser.add_argument("--dropout", type=float, default=0.1)
 
@@ -81,6 +84,17 @@ parser.add_argument("--checkpoint_name", type=str, default="checkpoint.pth")
 ##############################
 # picoclvr options
 
+parser.add_argument("--sandbox_level", type=int, default=0)
+
+parser.add_argument("--sandbox_levels_nb_items", type=int, default=25)
+
+parser.add_argument("--sandbox_levels_len_source", type=int, default=6)
+
+parser.add_argument("--sandbox_levels_len_result", type=int, default=8)
+
+##############################
+# picoclvr options
+
 parser.add_argument("--picoclvr_nb_colors", type=int, default=5)
 
 parser.add_argument("--picoclvr_height", type=int, default=12)
@@ -149,7 +163,13 @@ if args.result_dir is None:
 
 ######################################################################
 
-default_args = {
+default_task_args = {
+    "sandbox": {
+        "nb_epochs": 50,
+        "batch_size": 25,
+        "nb_train_samples": 100000,
+        "nb_test_samples": 10000,
+    },
     "picoclvr": {
         "nb_epochs": 25,
         "batch_size": 25,
@@ -186,21 +206,67 @@ default_args = {
         "nb_train_samples": 1000000,
         "nb_test_samples": 10000,
     },
+    "rpl": {
+        "nb_epochs": 40,
+        "batch_size": 25,
+        "nb_train_samples": 1000000,
+        "nb_test_samples": 10000,
+    },
     "world": {
         "nb_epochs": 10,
         "batch_size": 25,
-        "nb_train_samples": 125000,
+        "nb_train_samples": 25000,
         "nb_test_samples": 1000,
     },
 }
 
-if args.task in default_args:
-    for k, v in default_args[args.task].items():
+if args.task in default_task_args:
+    for k, v in default_task_args[args.task].items():
         if getattr(args, k) is None:
             setattr(args, k, v)
 
 ######################################################################
 
+default_model_args = {
+    "17K": {
+        "dim_model": 32,
+        "dim_keys": 32,
+        "dim_hidden": 32,
+        "nb_heads": 2,
+        "nb_blocks": 2,
+    },
+    "37M": {
+        "dim_model": 512,
+        "dim_keys": 64,
+        "dim_hidden": 2048,
+        "nb_heads": 8,
+        "nb_blocks": 12,
+    },
+    "122M": {
+        "dim_model": 768,
+        "dim_keys": 64,
+        "dim_hidden": 2048,
+        "nb_heads": 8,
+        "nb_blocks": 24,
+    },
+    "352M": {
+        "dim_model": 1024,
+        "dim_keys": 64,
+        "dim_hidden": 2048,
+        "nb_heads": 8,
+        "nb_blocks": 48,
+    },
+}
+
+if args.model in default_model_args:
+    for k, v in default_model_args[args.model].items():
+        if getattr(args, k) is None:
+            setattr(args, k, v)
+else:
+    raise ValueError(f"Unknown model {args.model}")
+
+######################################################################
+
 try:
     os.mkdir(args.result_dir)
 except FileExistsError:
@@ -257,7 +323,38 @@ picoclvr_pruner_eval = (
 
 ######################################################################
 
-if args.task == "picoclvr":
+if args.task == "sandbox":
+    if args.sandbox_level == 0:
+        problem = tasks.ProblemLevel0(
+            nb_sentences=args.sandbox_levels_nb_items,
+            len_prompt=args.sandbox_levels_len_source,
+            len_result=args.sandbox_levels_len_result,
+        )
+    elif args.sandbox_level == 1:
+        problem = tasks.ProblemLevel1(
+            nb_operators=args.sandbox_levels_nb_items,
+            len_source=args.sandbox_levels_len_source,
+            len_result=args.sandbox_levels_len_result,
+        )
+    elif args.sandbox_level == 2:
+        problem = tasks.ProblemLevel2(
+            len_source=args.sandbox_levels_len_source,
+            len_result=args.sandbox_levels_len_result,
+        )
+    else:
+        raise ValueError(f"Unknown sandbox level {args.sandbox_level}")
+
+    task = tasks.SandBox(
+        problem,
+        # tasks.ProblemAddition(zero_padded=False, inverted_result=False),
+        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,
@@ -328,6 +425,14 @@ elif args.task == "expr":
         device=device,
     )
 
+elif args.task == "rpl":
+    task = tasks.RPL(
+        nb_train_samples=args.nb_train_samples,
+        nb_test_samples=args.nb_test_samples,
+        batch_size=args.batch_size,
+        device=device,
+    )
+
 elif args.task == "world":
     task = tasks.World(
         nb_train_samples=args.nb_train_samples,