def displayOutput(self, display):
display.fill((34, 177, 76))
display.blit(data.getResource("credits_player.png"), (data.config.WIDTH * 0.4 - 380, data.config.HEIGHT * 0.55 - 264))
display.blit(data.getResource("credits_dog.png"), (data.config.WIDTH * 0.7 - 200, data.config.HEIGHT * 0.6))
graphics.drawText(display, data.translate("credits"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.1, size=50, formatting="center")
graphics.drawText(display, data.translate("students"), data.config.WIDTH * 0.7 - 400, data.config.HEIGHT * 0.25, size=30)
graphics.drawText(display, "Victor Andrade", data.config.WIDTH * 0.7 - 100, data.config.HEIGHT * 0.25, size=20)
graphics.drawText(display, "Marianne Linhares", data.config.WIDTH * 0.7 - 100, data.config.HEIGHT * 0.29, size=20)
graphics.drawText(display, data.translate("professors"), data.config.WIDTH * 0.7 - 400, data.config.HEIGHT * 0.36 + 20, size=30)
graphics.drawText(display, "Dalton Serey", data.config.WIDTH * 0.7 - 25, data.config.HEIGHT * 0.36 + 20, size=20)
graphics.drawText(display, "Jorge Figueiredo", data.config.WIDTH * 0.7 - 25, data.config.HEIGHT * 0.40 + 20, size=20)
graphics.drawText(display, data.translate("monitor"), data.config.WIDTH * 0.7 - 400 , data.config.HEIGHT * 0.47 + 40, size=30)
graphics.drawText(display, "Kl�udio Medeiros".decode("cp437"), data.config.WIDTH * 0.7 - 120, data.config.HEIGHT * 0.47 + 40, size=20)
self.credits_list.draw(display)
if self.fadin > 0:
blackness = pygame.Surface((data.config.WIDTH, data.config.HEIGHT))
blackness.set_alpha(self.fadin, pygame.RLEACCEL)
display.blit(blackness, (0, 0))
self.fadin -= 4
def test_translate_np():
# Simulate a piece matrix of length 100 timesteps and test if translate
# shifts the matrix down and up correctly across the note axis
rand_matrix = np.random.rand(100 * 78 * 2).reshape(100, 78, 2)
translated_matrix = data.translate(rand_matrix, direction="up")
assert translated_matrix[0][1:] == rand_matrix[0][:-1]
translated_matrix_d = data.translate(rand_matrix, direction="down")
assert translated_matrix_d[0][:-1] == rand_matrix[0][1:]
def displayOutput(self, display):
display.blit(self.shadow, (0, 0))
self.menu_list.draw(display)
graphics.drawText(display, data.translate("return"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.3, size=20 , formatting="center")
graphics.drawText(display, data.translate("help"), data.config.WIDTH * 0.3, data.config.HEIGHT * 0.5, size=20 , formatting="center")
graphics.drawText(display, data.translate("configurations"), data.config.WIDTH * 0.7, data.config.HEIGHT * 0.5, size=20 , formatting="center")
graphics.drawText(display, data.translate("exit"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.7, size=20 , formatting="center")
graphics.drawText(display, data.translate("pause"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.5, size=40 , color=0xFFFFFF, formatting="center")
def displayOutput(self, display):
self.buff.fill((64 - self.transitionTimer / 2, 0, 0))
self.buff.set_alpha(self.transitionTimer * 2 + 1, pygame.RLEACCEL)
self.menu_list.draw(self.buff)
graphics.drawText(self.buff, "Game Over", data.config.WIDTH * 0.5, data.config.HEIGHT * 0.4, size=40 , color=0xFFFFFF, formatting="center")
graphics.drawText(self.buff, data.translate("menu"), data.config.WIDTH * 0.3, data.config.HEIGHT * 0.7, size=20 , formatting="center")
graphics.drawText(self.buff, data.translate("submit"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.7 - 15, size=20, formatting="center")
graphics.drawText(self.buff, data.translate("score"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.7 + 15, size=20, formatting="center")
graphics.drawText(self.buff, data.translate("restart"), data.config.WIDTH * 0.7, data.config.HEIGHT * 0.7, size=20 , formatting="center")
display.blit(self.buff, (0, 0))
self.transitionTimer = min(self.transitionTimer + 1, 128)
def write_predictions(netG,
inv_charmap,
batches_per_file,
num_files,
batch_size=100000):
print(
f"Generating {batch_size * batches_per_file * num_files} passwords...")
t_total = datetime.datetime.now()
for i in range(1, num_files + 1):
t = datetime.datetime.now()
print(f"File {i}")
print("\tGenerating output...")
preds = []
for _ in range(batches_per_file):
preds.append(
netG(torch.randn(batch_size, 128).to(device=device)).argmax(
dim=2)) #max 100k fits in memory
list_of_preds = torch.stack(preds).reshape((-1, 10)).cpu().tolist()
del preds
print("\tTranslating output...")
translated_preds = translate(list_of_preds, inv_charmap)
del list_of_preds
print("\tWriting output...")
with open(
f"Predictions/predfile_{i}_{batch_size*batches_per_file}.txt",
'w+') as f:
for pred in translated_preds:
f.write(pred + "\n")
print(f"\t{datetime.datetime.now() - t}")
del translated_preds
print(f"\tTotal: {datetime.datetime.now() - t_total}")
def displayOutput(self, display):
textColor = 0xF0F0F0
buf = pygame.Surface((data.config.WIDTH, data.config.HEIGHT))
if self.transitionTimer < 1080:
buf.set_alpha(5 * abs((self.transitionTimer + 180) % 360 - 180), pygame.RLEACCEL)
if self.transitionTimer < 360:
buf.blit(data.getResource("bob.png")[28], (data.config.WIDTH * 0.4 - 48, data.config.HEIGHT * 0.6 - 48))
buf.blit(data.getResource("dog.png")[3], (data.config.WIDTH * 0.6 - 26, data.config.HEIGHT * 0.6 - 24))
graphics.drawText(buf, data.translate("intro1"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.4, color=textColor, size=20, formatting="center")
graphics.drawText(buf, data.translate("intro2"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.4 + 50, color=textColor, size=20, formatting="center")
elif self.transitionTimer < 720:
buf.blit(data.getResource("bob.png")[24], (data.config.WIDTH * 0.4 - 48, data.config.HEIGHT * 0.7 - 48))
buf.blit(data.getResource("cage.png")[0], (data.config.WIDTH * 0.6 + 37, data.config.HEIGHT * 0.7 - 6))
buf.blit(data.getResource("neighbour.png")[1], (data.config.WIDTH * 0.6 - 40, data.config.HEIGHT * 0.7 - 92))
graphics.drawText(buf, data.translate("intro3"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.4, color=textColor, size=20, formatting="center")
graphics.drawText(buf, data.translate("intro4"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.4 + 50, color=textColor, size=20, formatting="center")
graphics.drawText(buf, data.translate("intro5"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.4 + 100, color=textColor, size=20, formatting="center")
elif self.transitionTimer < 1080:
buf.blit(data.getResource("bob.png")[0], (data.config.WIDTH * 0.5 - 48, data.config.HEIGHT * 0.45 - 48))
graphics.drawText(buf, data.translate("intro6"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.6, color=textColor, size=20, formatting="center")
elif ((self.transitionTimer - 1002) / 16) % 4:
graphics.drawText(buf, data.translate("press"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.5, color=textColor, size=20, formatting="center")
display.blit(buf, (0, 0))
def displayOutput(self, display, offset=(0, 0)):
if self.transitionTimer < 128:
buf = pygame.Surface((200 + data.config.WIDTH * 0.3, 100), pygame.SRCALPHA)
self.winButtons.draw(buf, (data.config.WIDTH * 0.35 - 100, data.config.HEIGHT * 0.4 - 50))
graphics.drawText(buf, data.translate("submit"), 100, 50 - 15, size=20, formatting="center")
graphics.drawText(buf, data.translate("score"), 100, 50 + 15, size=20, formatting="center")
graphics.drawText(buf, data.translate("exit"), 100 + data.config.WIDTH * 0.3, 50, size=20, formatting="center")
buf.fill((255, 255, 255, 255 - self.transitionTimer * 2), special_flags=pygame.BLEND_RGBA_MULT)
display.blit(buf, (data.config.WIDTH * 0.35 - 100, data.config.HEIGHT * 0.4 - 50))
self.transitionTimer += 2
elif self.transitionTimer < 256:
buf = display.copy()
self.menu_list.draw(buf)
graphics.drawText(buf, data.translate("name"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.4, size=40, color=self.color, formatting="center")
graphics.drawText(buf, data.translate("submit"), data.config.WIDTH * 0.5 + 225, data.config.HEIGHT * 0.55, size=20 , formatting="center")
buf.set_alpha(2 * self.transitionTimer - 256, pygame.RLEACCEL)
display.blit(buf, (0, 0))
self.transitionTimer += 2
else:
self.menu_list.draw(display)
graphics.drawText(display, data.translate("name"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.4, size=40, color=self.color, formatting="center")
graphics.drawText(display, data.translate("submit"), data.config.WIDTH * 0.5 + 225, data.config.HEIGHT * 0.55, size=20 , formatting="center")
def displayOutput(self, display):
display.fill(0x101010)
display.blit(data.getResource("ranking.png"), (data.config.WIDTH * 0.5 - 350 - 8, data.config.HEIGHT * 0.55 - 272))
self.ranking_list.draw(display)
purple = 0x7018cb
buff = display.copy()
if len(self.list) == 0:
graphics.drawText(buff, data.translate("empty"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.55, size=30, color=0x303030, formatting="center")
for i in range(0, len(self.list)):
y = data.config.HEIGHT * 0.55 - 218 + i * 110 - self.ranking_list.getSliderValue(1) * max(0, len(self.list) - 5) * 110 / 1000
buff.blit(data.getResource("ranking_pos.png"), (data.config.WIDTH * 0.5 - 350, y - 46))
buff.blit(data.getResource("ranking_slot.png"), (data.config.WIDTH * 0.5 - 240, y - 46))
buff.blit(data.getResource("ranking_score.png"), (data.config.WIDTH * 0.5 + 160, y - 46))
if data.config.HEIGHT * 0.55 - 276 < y < data.config.HEIGHT * 0.55 + 272 + 15:
graphics.drawText(buff, str(i + 1), data.config.WIDTH * 0.5 - 300, y, size=30, color=purple, formatting="center")
graphics.drawText(buff, self.list[i][0], data.config.WIDTH * 0.5 - 228, y, size=20, color=purple)
graphics.drawText(buff, "%4d" % self.list[i][1], data.config.WIDTH * 0.5 + 160 + 100, y, size=20, color=purple, formatting="center")
display.blit(buff, (data.config.WIDTH * 0.5 - 350, data.config.HEIGHT * 0.55 - 268), ((data.config.WIDTH * 0.5 - 350, data.config.HEIGHT * 0.55 - 268), (710, 540)))
display.blit(data.getResource("separator.png"), (data.config.WIDTH * 0.5 - 350 - 8, data.config.HEIGHT * 0.55 - 276))
display.blit(data.getResource("separator.png"), (data.config.WIDTH * 0.5 - 350 - 8, data.config.HEIGHT * 0.55 + 272))
if self.fadin > 0:
blackness = pygame.Surface((data.config.WIDTH, data.config.HEIGHT))
blackness.set_alpha(self.fadin, pygame.RLEACCEL)
display.blit(blackness, (0, 0))
self.fadin -= 4
graphics.drawText(display, data.translate("ranking"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.1, size=40, color=0xffffff, formatting="center")
def displayOutput(self, display):
display.blit(data.getResource("backyard.png"), (data.config.WIDTH * 0.5 - 960, data.config.HEIGHT * 0.85 - 1080 + 162))
display.blit(data.getResource("logo.png"), (data.config.WIDTH * 0.5 - 461, data.config.HEIGHT * 0.05))
self.menu_list.draw(display)
graphics.drawText(display, data.translate("start"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.6, size=20 , formatting="center")
graphics.drawText(display, data.translate("help"), data.config.WIDTH * 0.1, data.config.HEIGHT * 0.9, size=20 , formatting="center")
graphics.drawText(display, data.translate("ranking"), data.config.WIDTH * 0.3, data.config.HEIGHT * 0.9, size=20 , formatting="center")
graphics.drawText(display, data.translate("configurations"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.9, size=20 , formatting="center")
graphics.drawText(display, data.translate("credits"), data.config.WIDTH * 0.7, data.config.HEIGHT * 0.9, size=20 , formatting="center")
graphics.drawText(display, data.translate("exit"), data.config.WIDTH * 0.9, data.config.HEIGHT * 0.9, size=20 , formatting="center")
if self.fadin > 0:
blackness = pygame.Surface((data.config.WIDTH, data.config.HEIGHT))
blackness.set_alpha(self.fadin, pygame.RLEACCEL)
display.blit(blackness, (0, 0))
self.fadin -= 4
def displayOutput(self, display):
if self.transitionTimer >= 128:
self.buttons.draw(display)
graphics.drawText(display, data.translate("submit"), data.config.WIDTH * 0.35, data.config.HEIGHT * 0.4 - 15, size=20, formatting="center")
graphics.drawText(display, data.translate("score"), data.config.WIDTH * 0.35, data.config.HEIGHT * 0.4 + 15, size=20, formatting="center")
graphics.drawText(display, data.translate("exit"), data.config.WIDTH * 0.65, data.config.HEIGHT * 0.4, size=20, formatting="center")
else:
buf = pygame.Surface((200 + data.config.WIDTH * 0.3, 100), pygame.SRCALPHA)
self.buttons.draw(buf, (data.config.WIDTH * 0.35 - 100, data.config.HEIGHT * 0.4 - 50))
graphics.drawText(buf, data.translate("submit"), 100, 50 - 15, size=20, formatting="center")
graphics.drawText(buf, data.translate("score"), 100, 50 + 15, size=20, formatting="center")
graphics.drawText(buf, data.translate("exit"), 100 + data.config.WIDTH * 0.3, 50, size=20, formatting="center")
buf.fill((255, 255, 255, self.transitionTimer * 2), special_flags=pygame.BLEND_RGBA_MULT)
display.blit(buf, (data.config.WIDTH * 0.35 - 100, data.config.HEIGHT * 0.4 - 50))
self.transitionTimer += 2
import pygame
import screen
import keyboard
import graphics
import data
pygame.mixer.pre_init(buffer=1024)
pygame.init()
pygame.mixer.set_num_channels(16)
data.loadConfig()
data.loadLanguage()
pygame.display.set_icon(pygame.image.load("icon.png"))
pygame.display.set_caption(data.translate("caption"))
resolution = data.config.WIDTH, data.config.HEIGHT
if data.config.FULLSCREEN:
display = pygame.display.set_mode(resolution, pygame.FULLSCREEN)
else: display = pygame.display.set_mode(resolution)
data.loadResources()
graphics.userInterface.cursor.init()
clock = pygame.time.Clock()
screen = screen.Introduction()
def repaint():
display.fill(0x000000)
screen.displayOutput(display)
def eval_dataset(config, valid_data, vocab, model, sess):
model_preds = []
ground_truths = []
memories = []
questions = []
commonsense = []
total_eval_loss = []
batch_obj = enumerate(valid_data.get_batches(config.batch_size,
shuffle=False, pad_to_full_batch=True))
if config.show_eval_progress:
batch_obj = tqdm(batch_obj)
for i,eval_batches in batch_obj:
is_training = False
if config.sample != -1 and i > config.sample:
break
ground_truths.extend(map(
lambda item: [item['answer1'], item['answer2']],
eval_batches))
memories.extend(map(lambda item: item['summary'],
eval_batches))
questions.extend(map(lambda item: item['ques'],
eval_batches))
if config.load_commonsense:
commonsense.extend(map(lambda item: item['commonsense'],
eval_batches))
fd = model.encode(eval_batches, is_training)
oovs = model.get_batch_oov()
eval_loss, preds = model.eval(sess, fd)
model_preds.extend(map(lambda p: translate(p, vocab, oovs),
preds))
total_eval_loss.append(eval_loss)
model_preds = model_preds[:valid_data.num_examples]
ground_truths = ground_truths[:valid_data.num_examples]
eval_loss = avg(total_eval_loss)
bleu1, bleu4, meteor, rouge, cider,\
bleu1_scores, bleu4_scores, meteor_scores, rouge_scores, cider_scores =\
eval_set(model_preds, ground_truths)
if config.to_print_nums == -1:
to_print_indices = range(len(model_preds))
else:
to_print_indices = random.sample(range(len(model_preds)),
config.to_print_nums)
for idx in to_print_indices:
print("Data %d" % idx)
print("Summary: ", " ".join(memories[idx]))
if config.load_commonsense:
print("Commonsense: ")
for path in commonsense[idx]:
for concept in path:
print (concept, "->", )
print ("")
print("Question: ", " ".join(questions[idx]))
print("Answer1: ", " ".join(ground_truths[idx][0]))
print("Answer2: ", " ".join(ground_truths[idx][1]))
print("Predicted: ", " ".join(model_preds[idx]))
print("Bleu1: %.3f, Bleu4: %.3f, Rouge-L: %.3f, Meteor: %.3f, CIDEr: %.3f" %
(bleu1_scores[idx], bleu4_scores[idx], rouge_scores[idx],
meteor_scores[idx], cider_scores[idx]))
print ("")
print("=" * 80)
print ("")
return bleu1, bleu4, meteor, rouge, cider, eval_loss, model_preds
def displayOutput(self, display):
textColor = 0x161616
menuNum = 3
if self.origin is not screen.Menu:
display.blit(self.shadow, (0, 0))
textColor = 0xE0E0E0
menuNum = 2
else: display.fill((0, 90, 150))
if self.image % menuNum == 0:
display.blit(data.getResource("help_esc.png"), (data.config.WIDTH * 0.4 - 200, data.config.HEIGHT * 0.25))
display.blit(data.getResource("help_Z.png"), (data.config.WIDTH * 0.4 - 200, data.config.HEIGHT * 0.25 + 80))
display.blit(data.getResource("help_X.png"), (data.config.WIDTH * 0.4 - 200, data.config.HEIGHT * 0.25 + 80 * 2))
display.blit(data.getResource("help_C.png"), (data.config.WIDTH * 0.4 - 200, data.config.HEIGHT * 0.25 + 80 * 3))
display.blit(data.getResource("help_up.png"), (data.config.WIDTH * 0.6 - 100, data.config.HEIGHT * 0.25))
display.blit(data.getResource("help_down.png"), (data.config.WIDTH * 0.6 - 100, data.config.HEIGHT * 0.25 + 80))
display.blit(data.getResource("help_left.png"), (data.config.WIDTH * 0.6 - 100, data.config.HEIGHT * 0.25 + 80 * 2))
display.blit(data.getResource("help_right.png"), (data.config.WIDTH * 0.6 - 20, data.config.HEIGHT * 0.25 + 80 * 2))
graphics.drawText(display, data.translate("controls"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.1, color=textColor, size=40, formatting="center")
graphics.drawText(display, data.translate("pause"), data.config.WIDTH * 0.4 - 120, data.config.HEIGHT * 0.25 + 20, color=textColor, size=20)
graphics.drawText(display, data.translate("jump"), data.config.WIDTH * 0.4 - 120, data.config.HEIGHT * 0.25 + 80 + 25, color=textColor, size=20)
graphics.drawText(display, data.translate("attack"), data.config.WIDTH * 0.4 - 120, data.config.HEIGHT * 0.25 + 80 * 2 + 25, color=textColor, size=20)
graphics.drawText(display, data.translate("use item"), data.config.WIDTH * 0.4 - 120, data.config.HEIGHT * 0.25 + 80 * 3 + 25, color=textColor, size=20)
graphics.drawText(display, data.translate("open"), data.config.WIDTH * 0.6 - 20, data.config.HEIGHT * 0.25 + 25, color=textColor, size=20)
graphics.drawText(display, data.translate("crouch"), data.config.WIDTH * 0.6 - 20, data.config.HEIGHT * 0.25 + 80 + 25, color=textColor, size=20)
graphics.drawText(display, data.translate("move"), data.config.WIDTH * 0.6 + 60, data.config.HEIGHT * 0.25 + 80 * 2 + 25, color=textColor, size=20)
graphics.drawText(display, data.translate("jump higher"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.65 + 60, color=textColor, size=18, formatting="center")
elif self.image % menuNum == 1:
display.blit(data.getResource("items.png")[0], (data.config.WIDTH * 0.6 + 150, data.config.HEIGHT * 0.25))
display.blit(data.getResource("items.png")[1], (data.config.WIDTH * 0.6 + 150 - 48, data.config.HEIGHT * 0.25))
display.blit(data.getResource("items.png")[2], (data.config.WIDTH * 0.6 + 150 - 48 * 2, data.config.HEIGHT * 0.25))
display.blit(data.getResource("items.png")[3], (data.config.WIDTH * 0.6 + 150 - 48 * 3, data.config.HEIGHT * 0.25))
display.blit(data.getResource("items.png")[4], (data.config.WIDTH * 0.6 + 150 - 48 * 4, data.config.HEIGHT * 0.25))
display.blit(data.getResource("items.png")[5], (data.config.WIDTH * 0.6 + 150 - 48 * 5, data.config.HEIGHT * 0.25))
display.blit(data.getResource("items.png")[6], (data.config.WIDTH * 0.6 + 150 - 48 * 6, data.config.HEIGHT * 0.25))
display.blit(data.getResource("items.png")[7], (data.config.WIDTH * 0.6 + 150 - 48 * 7, data.config.HEIGHT * 0.25))
display.blit(data.getResource("items.png")[8], (data.config.WIDTH * 0.6 + 150, data.config.HEIGHT * 0.25 + 80))
display.blit(data.getResource("items.png")[9], (data.config.WIDTH * 0.6 + 150 - 48, data.config.HEIGHT * 0.25 + 80))
display.blit(data.getResource("items.png")[16], (data.config.WIDTH * 0.6 + 150, data.config.HEIGHT * 0.25 + 80 * 2))
display.blit(data.getResource("items.png")[17], (data.config.WIDTH * 0.6 + 150 - 48, data.config.HEIGHT * 0.25 + 80 * 2))
display.blit(data.getResource("items.png")[18], (data.config.WIDTH * 0.6 + 150 - 48 * 2, data.config.HEIGHT * 0.25 + 80 * 2))
display.blit(data.getResource("items.png")[11], (data.config.WIDTH * 0.6 + 150, data.config.HEIGHT * 0.25 + 80 * 3))
display.blit(data.getResource("chest.png")[0], (data.config.WIDTH * 0.3 - 200, data.config.HEIGHT * 0.55 - 120))
graphics.drawText(display, data.translate("items"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.1, size=40, color=textColor, formatting="center")
graphics.drawText(display, data.translate("chest1"), data.config.WIDTH * 0.3 - 250, data.config.HEIGHT * 0.55, color=textColor, size=20)
graphics.drawText(display, data.translate("chest2"), data.config.WIDTH * 0.3 - 250, data.config.HEIGHT * 0.55 + 50, color=textColor, size=20)
graphics.drawText(display, data.translate("chest3"), data.config.WIDTH * 0.3 - 250, data.config.HEIGHT * 0.55 + 100, color=textColor, size=20)
graphics.drawText(display, data.translate("chest4"), data.config.WIDTH * 0.3 - 250, data.config.HEIGHT * 0.55 + 150, color=textColor, size=15)
graphics.drawText(display, data.translate("food"), data.config.WIDTH * 0.6 + 150 + 80, data.config.HEIGHT * 0.25 + 24, color=textColor, size=20)
graphics.drawText(display, data.translate("potions"), data.config.WIDTH * 0.6 + 150 + 80, data.config.HEIGHT * 0.25 + 80 + 24, color=textColor, size=20)
graphics.drawText(display, data.translate("weapons"), data.config.WIDTH * 0.6 + 150 + 80, data.config.HEIGHT * 0.25 + 80 * 2 + 24, color=textColor, size=20)
graphics.drawText(display, data.translate("bomb"), data.config.WIDTH * 0.6 + 150 + 80, data.config.HEIGHT * 0.25 + 80 * 3 + 24, color=textColor, size=20)
elif self.image % menuNum == 2:
graphics.drawText(display, data.translate("test"), data.config.WIDTH * 0.5, data.config.HEIGHT * 0.1, size=40, color=textColor, formatting="center")
graphics.drawText(display, data.translate("test1"), data.config.WIDTH * 0.5 - 320, data.config.HEIGHT * 0.62 - 75, color=textColor, size=20)
graphics.drawText(display, data.translate("test2"), data.config.WIDTH * 0.5 - 320, data.config.HEIGHT * 0.62 - 25, color=textColor, size=20)
graphics.drawText(display, data.translate("test3"), data.config.WIDTH * 0.5 - 320, data.config.HEIGHT * 0.62 + 25, color=textColor, size=20)
graphics.drawText(display, data.translate("test4"), data.config.WIDTH * 0.5 - 320, data.config.HEIGHT * 0.62 + 75, color=textColor, size=20)
self.help_list.draw(display)
def predict_many(netGs, inv_charmap, num_samples=5):
latent_noise = torch.randn(num_samples, 128).to(device=device)
return [
translate(netG(latent_noise).argmax(dim=2), inv_charmap)
for netG in netGs
]
def predict_one(netG, inv_charmap, num_samples):
latent_noise = torch.randn(num_samples, 128).to(device=device)
return translate(netG(latent_noise).argmax(dim=2), inv_charmap)
def training_loop(lines, charmap, inv_charmap, dataloader, args):
lambda_ = args['lambda_']
n_critic_iters_per_generator_iter = args[
'n_critic_iters_per_generator_iter']
batch_size = args['batch_size']
lr = args['lr']
adam_beta1 = args['adam_beta1']
adam_beta2 = args['adam_beta2']
iterations = args['iterations']
continue_training = args['continue_training']
netG_checkpoint = args['netG_checkpoint']
netD_checkpoint = args['netD_checkpoint']
netG = Generator(charmap).to(device=device)
netD = Discriminator(charmap).to(device=device)
train = dataloader(lines, batch_size)
if continue_training: #if continuing from checkpoint
netG.load_state_dict(torch.load(netG_checkpoint))
netD.load_state_dict(torch.load(netD_checkpoint))
start_iter = int(netG_checkpoint.split(":")[0].split("-")[-1][:-2])
for _ in range(start_iter):
next(train)
pass
print(f"Model loaded, starting at {start_iter}...")
else:
start_iter = 1
optimG = optim.Adam(netG.parameters(),
lr=lr,
betas=(adam_beta1, adam_beta2))
optimD = optim.Adam(netD.parameters(),
lr=lr,
betas=(adam_beta1, adam_beta2))
# start actual training loop
for iteration in range(start_iter, iterations + 1):
for p in netD.parameters():
p.requires_grad = True
for i in range(n_critic_iters_per_generator_iter
): #discrim trains 10 times for gen's 1
real_inputs_discrete = next(train)
real_data = F.one_hot(real_inputs_discrete,
num_classes=len(charmap)).float() #x
latent_variable = torch.randn(batch_size,
128).to(device=device) #z
alpha = torch.rand(batch_size, 1, 1).to(device=device) #epsilon
fake_data = netG(latent_variable) #x_tilde
interpolates = alpha * real_data + (
(1 - alpha) * fake_data) #x_hat
interpolates = interpolates.clone().detach().requires_grad_(
True) #x_hat
discrim_interpolates = netD(interpolates) #D_w(x_hat)
gradients = autograd.grad(
outputs=discrim_interpolates,
inputs=interpolates, #grad D_w(x_hat)
grad_outputs=torch.ones(
discrim_interpolates.size()).to(device=device),
create_graph=True,
retain_graph=True,
only_inputs=True)[0] #doesn't populate grad attributes
gradient_penalty = (
(gradients.norm(2, dim=1) - 1)**2).mean() * lambda_
disc_real = netD(real_data).mean() #D_w(x)
disc_fake = netD(fake_data).mean() #D_w(x_tilde)
loss = disc_fake - disc_real + gradient_penalty #L
loss.backward()
optimD.step()
netD.zero_grad()
for p in netD.parameters():
p.requires_grad = False # to avoid computation
netG.zero_grad()
latent_variable = torch.randn(batch_size, 128).to(device=device) #z
fake_data = netG(latent_variable)
G = -netD(fake_data).mean()
G.backward()
optimG.step()
if iteration % 1000 == 0 or iteration == 1:
print(f"iterations {iteration}")
real_translation = translate(
real_inputs_discrete[:10].cpu().numpy(), inv_charmap)
fake_translation = translate(
fake_data[:10].detach().cpu().numpy().argmax(axis=2),
inv_charmap)
print(f"\tFake: {fake_translation}\n\tReal: {real_translation}")
time = datetime.datetime.now(
tz=datetime.timezone(datetime.timedelta(
hours=-5))).strftime("%I:%M:%S%p_%m-%d-%y")
torch.save(
netG.state_dict(),
f"/home/nvijayakumar/gcp-gan/Checkpoints/netG-{iteration}{time}"
)
torch.save(
netD.state_dict(),
f"/home/nvijayakumar/gcp-gan/Checkpoints/netD-{iteration}{time}"
)