From: François Fleuret Date: Tue, 2 Jul 2024 14:01:38 +0000 (+0300) Subject: Update. X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=d283cd3d46a6323fec4c6a0970ac71e553e4a486;p=culture.git Update. --- diff --git a/main.py b/main.py index d194a8d..d63398c 100755 --- 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("--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") @@ -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, - reverse_cleanup=args.reverse_cleanup, ) 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: @@ -429,7 +426,7 @@ def create_c_quizzes( 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 @@ -487,20 +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} ----------------------------------------") + # 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}" ) - # 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}" ) - # test it run_tests(weakest_model, quizz_machine, deterministic_synthesis=False) log_string( @@ -510,9 +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}") - # 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) + # 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, @@ -521,7 +522,6 @@ for n_epoch in range(args.nb_epochs): nb_for_test=nb_new_c_quizzes_for_test, ) - # We update everyone for model in models: run_tests(model, quizz_machine, deterministic_synthesis=False) diff --git a/quizz_machine.py b/quizz_machine.py index 5807b66..0d6d8f5 100755 --- a/quizz_machine.py +++ b/quizz_machine.py @@ -333,7 +333,7 @@ class QuizzMachine: ) def compute_correctness( - self, c_quizzes, models_for_validation, both_directions=True + self, c_quizzes, models_for_validation, both_directions=False ): reversed_c_quizzes = self.reverse_time(c_quizzes) @@ -390,7 +390,7 @@ class QuizzMachine: ############################################################### - def generate_quizzes(self, nb, model_for_generation, reverse_cleanup=False): + def generate_quizzes(self, nb, model_for_generation): c_quizzes = torch.empty( nb, self.train_w_quizzes.size(1), device=self.device, dtype=torch.int64 ) @@ -403,10 +403,7 @@ class QuizzMachine: seq_logproba = torch.empty(ar_mask_first.size(0), device=self.device) - if reverse_cleanup: - temperature = 10.0 - else: - temperature = 1.0 + temperature = 10.0 # First, we generate the answer at high temperature @@ -433,7 +430,7 @@ class QuizzMachine: input=c_quizzes, ar_mask=ar_mask_second, seq_logproba=seq_logproba, - temperature=temperature, + temperature=1.0, deterministic_synthesis=True, device=self.device, ) diff --git a/sky.py b/sky.py index d2a4568..2183cf1 100755 --- a/sky.py +++ b/sky.py @@ -165,7 +165,7 @@ class Sky(problem.Problem): ###################################################################### def frame2img(self, x, scale=15): - x = x.reshape(-1, self.height, self.width) + x = x.reshape(x.size(0), self.height, -1) m = torch.logical_and( x >= 0, x < self.first_bird_token + self.nb_bird_tokens ).long() @@ -274,7 +274,7 @@ class Sky(problem.Problem): if __name__ == "__main__": import time - sky = Sky(height=6, width=8, speed=4, nb_iterations=2) + sky = Sky(height=6, width=8, speed=1, nb_iterations=4) prompts, answers = sky.generate_prompts_and_answers(4)