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Update.
[culture.git]
/
main.py
diff --git
a/main.py
b/main.py
index
2afe61b
..
8033836
100755
(executable)
--- a/
main.py
+++ b/
main.py
@@
-73,7
+73,7
@@
parser.add_argument("--deterministic_synthesis", action="store_true", default=Fa
parser.add_argument("--nb_gpts", type=int, default=5)
parser.add_argument("--nb_gpts", type=int, default=5)
-parser.add_argument("--
check
", action="store_true", default=False)
+parser.add_argument("--
dirty_debug
", action="store_true", default=False)
######################################################################
######################################################################
@@
-182,7
+182,7
@@
for n in vars(args):
######################################################################
######################################################################
-if args.
check
:
+if args.
dirty_debug
:
args.nb_train_samples = 2500
args.nb_test_samples = 100
args.nb_train_samples = 2500
args.nb_test_samples = 100
@@
-338,10
+338,12
@@
def create_quizzes(
desired_average_logits=None,
):
kept = []
desired_average_logits=None,
):
kept = []
- nb_generated_tokens, sum_logits = 0, 0
+
+ sum_logits, sum_nb_quizzes = 0, 0
while sum([x.size(0) for x in kept]) < nb_for_train + nb_for_test:
nb_to_generate = 4 * (nb_for_train + nb_for_test)
while sum([x.size(0) for x in kept]) < nb_for_train + nb_for_test:
nb_to_generate = 4 * (nb_for_train + nb_for_test)
+
new_quizzes, nb_correct, average_logits = task.create_new_quizzes(
n_epoch=n_epoch,
result_dir=args.result_dir,
new_quizzes, nb_correct, average_logits = task.create_new_quizzes(
n_epoch=n_epoch,
result_dir=args.result_dir,
@@
-352,13
+354,18
@@
def create_quizzes(
desired_average_logits=desired_average_logits,
)
desired_average_logits=desired_average_logits,
)
- nb_generated_tokens += new_quizzes.numel()
- sum_
logits += average_logits * new_quizzes.numel(
)
+ sum_logits += new_quizzes.size(0) * average_logits
+ sum_
nb_quizzes += new_quizzes.size(0
)
to_keep = new_quizzes[nb_correct == len(other_models) - 1]
to_keep = new_quizzes[nb_correct == len(other_models) - 1]
+
+ if args.dirty_debug:
+ to_keep = new_quizzes
+
log_string(
f"keep {to_keep.size(0)}/{new_quizzes.size(0)} quizzes ({to_keep.size(0)*100/new_quizzes.size(0):.02f}%)"
)
log_string(
f"keep {to_keep.size(0)}/{new_quizzes.size(0)} quizzes ({to_keep.size(0)*100/new_quizzes.size(0):.02f}%)"
)
+
kept.append(to_keep)
new_quizzes = torch.cat(kept, dim=0)[: nb_for_train + nb_for_test]
kept.append(to_keep)
new_quizzes = torch.cat(kept, dim=0)[: nb_for_train + nb_for_test]
@@
-373,7
+380,7
@@
def create_quizzes(
log_string,
)
log_string,
)
- return sum_logits /
nb_generated_token
s
+ return sum_logits /
sum_nb_quizze
s
######################################################################
######################################################################
@@
-407,9
+414,9
@@
accuracy_to_make_quizzes = 0.975
nb_new_quizzes_for_train = 1000
nb_new_quizzes_for_test = 100
nb_new_quizzes_for_train = 1000
nb_new_quizzes_for_test = 100
-if args.
check
:
+if args.
dirty_debug
:
accuracy_to_make_quizzes = 0.0
accuracy_to_make_quizzes = 0.0
- nb_new_quizzes_for_train = 10
+ nb_new_quizzes_for_train = 10
0
nb_new_quizzes_for_test = 10
desired_average_logits = None
nb_new_quizzes_for_test = 10
desired_average_logits = None