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import os
import torch
from tqdm import tqdm
from configs import paths_config, hyperparameters, global_config
from training.coaches.base_coach import BaseCoach
from utils.log_utils import log_images_from_w
class SingleIDCoach(BaseCoach):
def __init__(self, data_loader, use_wandb):
super().__init__(data_loader, use_wandb)
def train(self):
w_path_dir = f'{paths_config.embedding_base_dir}/{paths_config.input_data_id}'
os.makedirs(w_path_dir, exist_ok=True)
os.makedirs(f'{w_path_dir}/{paths_config.pti_results_keyword}', exist_ok=True)
use_ball_holder = True
for fname, image in tqdm(self.data_loader):
image_name = fname[0]
self.restart_training()
if self.image_counter >= hyperparameters.max_images_to_invert:
break
embedding_dir = f'{w_path_dir}/{paths_config.pti_results_keyword}/{image_name}'
os.makedirs(embedding_dir, exist_ok=True)
w_pivot = None
if hyperparameters.use_last_w_pivots:
w_pivot = self.load_inversions(w_path_dir, image_name)
elif not hyperparameters.use_last_w_pivots or w_pivot is None:
w_pivot = self.calc_inversions(image, image_name)
# w_pivot = w_pivot.detach().clone().to(global_config.device)
w_pivot = w_pivot.to(global_config.device)
torch.save(w_pivot, f'{embedding_dir}/0.pt')
log_images_counter = 0
real_images_batch = image.to(global_config.device)
for i in tqdm(range(hyperparameters.max_pti_steps)):
generated_images = self.forward(w_pivot)
loss, l2_loss_val, loss_lpips = self.calc_loss(generated_images, real_images_batch, image_name,
self.G, use_ball_holder, w_pivot)
self.optimizer.zero_grad()
if loss_lpips <= hyperparameters.LPIPS_value_threshold:
break
loss.backward()
self.optimizer.step()
use_ball_holder = global_config.training_step % hyperparameters.locality_regularization_interval == 0
if self.use_wandb and log_images_counter % global_config.image_rec_result_log_snapshot == 0:
log_images_from_w([w_pivot], self.G, [image_name])
global_config.training_step += 1
log_images_counter += 1
self.image_counter += 1
torch.save(self.G,
f'{paths_config.checkpoints_dir}/model_{global_config.run_name}_{image_name}.pt')
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