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Fix memory leak in latent caching. bmp failed to cache

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Kohya S
2024-11-01 21:43:21 +09:00
parent 830df4abcc
commit 9aa6f52ac3
1 changed files with 15 additions and 1 deletions
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16
library/train_util.py
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@@ -1082,6 +1082,10 @@ class BaseDataset(torch.utils.data.Dataset):
info.image = info.image.result() # future to image info.image = info.image.result() # future to image
caching_strategy.cache_batch_latents(model, batch, cond.flip_aug, cond.alpha_mask, cond.random_crop) caching_strategy.cache_batch_latents(model, batch, cond.flip_aug, cond.alpha_mask, cond.random_crop)
# remove image from memory
for info in batch:
info.image = None
# define ThreadPoolExecutor to load images in parallel # define ThreadPoolExecutor to load images in parallel
max_workers = min(os.cpu_count(), len(image_infos)) max_workers = min(os.cpu_count(), len(image_infos))
max_workers = max(1, max_workers // num_processes) # consider multi-gpu max_workers = max(1, max_workers // num_processes) # consider multi-gpu
@@ -1397,7 +1401,17 @@ class BaseDataset(torch.utils.data.Dataset):
) )
def get_image_size(self, image_path): def get_image_size(self, image_path):
return imagesize.get(image_path) # return imagesize.get(image_path)
image_size = imagesize.get(image_path)
if image_size[0] <= 0:
# imagesize doesn't work for some images, so use cv2
img = cv2.imread(image_path)
if img is not None:
image_size = (img.shape[1], img.shape[0])
else:
logger.warning(f"failed to get image size: {image_path}")
image_size = (0, 0)
return image_size
def load_image_with_face_info(self, subset: BaseSubset, image_path: str, alpha_mask=False): def load_image_with_face_info(self, subset: BaseSubset, image_path: str, alpha_mask=False):
img = load_image(image_path, alpha_mask) img = load_image(image_path, alpha_mask)