projects
/
culture.git
/ blobdiff
commit
grep
author
committer
pickaxe
?
search:
re
summary
|
shortlog
|
log
|
commit
|
commitdiff
|
tree
raw
|
inline
| side by side
Update.
[culture.git]
/
main.py
diff --git
a/main.py
b/main.py
index
d412e6c
..
d63398c
100755
(executable)
--- a/
main.py
+++ b/
main.py
@@
-79,9
+79,7
@@
parser.add_argument("--dropout", type=float, default=0.1)
parser.add_argument("--deterministic_synthesis", action="store_true", default=False)
parser.add_argument("--deterministic_synthesis", action="store_true", default=False)
-parser.add_argument("--reverse_cleanup", action="store_true", default=True)
-
-parser.add_argument("--validation_forward_only", action="store_true", default=False)
+parser.add_argument("--both_directions", action="store_true", default=False)
parser.add_argument("--problem", type=str, default="sky")
parser.add_argument("--problem", type=str, default="sky")
@@
-409,11
+407,10
@@
def create_c_quizzes(
c_quizzes, ave_seq_logproba = quizz_machine.generate_quizzes(
nb_to_create,
model_for_generation=model_for_generation,
c_quizzes, ave_seq_logproba = quizz_machine.generate_quizzes(
nb_to_create,
model_for_generation=model_for_generation,
- reverse_cleanup=args.reverse_cleanup,
)
nb_correct = quizz_machine.compute_correctness(
)
nb_correct = quizz_machine.compute_correctness(
- c_quizzes, models, both_directions=
not args.validation_forward_only
+ c_quizzes, models, both_directions=
args.both_directions
)
if args.dirty_debug:
)
if args.dirty_debug:
@@
-429,7
+426,7
@@
def create_c_quizzes(
nb_validated = valid_c_quizzes(recorded, standard_validity).size(0)
log_string(
nb_validated = valid_c_quizzes(recorded, standard_validity).size(0)
log_string(
- f"keep c_quizzes kept {nv} nb_accumulated {nb_validated} / {nb_to_create}"
+ f"keep c_quizzes
model {model_for_generation.id}
kept {nv} nb_accumulated {nb_validated} / {nb_to_create}"
)
# store the new c_quizzes which have been validated
)
# store the new c_quizzes which have been validated
@@
-452,10
+449,8
@@
def create_c_quizzes(
q = valid_c_quizzes(recorded, criteria=lambda nb_correct: nb_correct == n)[:72]
if q.size(0) > 0:
q = valid_c_quizzes(recorded, criteria=lambda nb_correct: nb_correct == n)[:72]
if q.size(0) > 0:
- quizz_machine.problem.save_quizzes(
- q,
- args.result_dir,
- f"culture_c_quiz_{n_epoch:04d}_N{n}{s}",
+ quizz_machine.save_quizzes(
+ args.result_dir, f"culture_c_quiz_{n_epoch:04d}_N{n}{s}", q
)
)
@@
-489,20
+484,20
@@
log_string(f"nb_parameters {nb_parameters} ({int(nb_parameters/1e6)}M)")
for n_epoch in range(args.nb_epochs):
log_string(f"--- epoch {n_epoch} ----------------------------------------")
for n_epoch in range(args.nb_epochs):
log_string(f"--- epoch {n_epoch} ----------------------------------------")
+ # Select, improve, and eval the worst model
+
weakest_model = min(models, key=lambda m: float(m.main_test_accuracy))
log_string(
f"training model {weakest_model.id} main_test_accuracy {weakest_model.main_test_accuracy}"
)
weakest_model = min(models, key=lambda m: float(m.main_test_accuracy))
log_string(
f"training model {weakest_model.id} main_test_accuracy {weakest_model.main_test_accuracy}"
)
- # improve it
one_epoch(weakest_model, quizz_machine)
log_string(
f"train_set_composition w_quizzes {quizz_machine.nb_batch_w_quizzes} c_quizzes {quizz_machine.nb_batch_c_quizzes}"
)
one_epoch(weakest_model, quizz_machine)
log_string(
f"train_set_composition w_quizzes {quizz_machine.nb_batch_w_quizzes} c_quizzes {quizz_machine.nb_batch_c_quizzes}"
)
- # test it
run_tests(weakest_model, quizz_machine, deterministic_synthesis=False)
log_string(
run_tests(weakest_model, quizz_machine, deterministic_synthesis=False)
log_string(
@@
-512,9
+507,13
@@
for n_epoch in range(args.nb_epochs):
cta = " ".join([f"{float(m.main_test_accuracy):.04f}" for m in models])
log_string(f"current_test_accuracies {cta}")
cta = " ".join([f"{float(m.main_test_accuracy):.04f}" for m in models])
log_string(f"current_test_accuracies {cta}")
- # replace a fraction of the w_quizzes with fresh ones
+ # Replace a fraction of the w_quizzes with fresh ones
+
quizz_machine.renew_w_quizzes(args.nb_train_samples // args.nb_gpts)
quizz_machine.renew_w_quizzes(args.nb_train_samples // args.nb_gpts)
+ # If all the models are good enough, generate new quizzes and
+ # re-compute the test errors
+
if min([m.main_test_accuracy for m in models]) >= args.accuracy_to_make_c_quizzes:
create_c_quizzes(
models,
if min([m.main_test_accuracy for m in models]) >= args.accuracy_to_make_c_quizzes:
create_c_quizzes(
models,
@@
-523,7
+522,6
@@
for n_epoch in range(args.nb_epochs):
nb_for_test=nb_new_c_quizzes_for_test,
)
nb_for_test=nb_new_c_quizzes_for_test,
)
- # We update everyone
for model in models:
run_tests(model, quizz_machine, deterministic_synthesis=False)
for model in models:
run_tests(model, quizz_machine, deterministic_synthesis=False)