log ed batch name on creation
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@ -63,7 +63,7 @@ class EveryDreamBatch(Dataset):
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self.name = name
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num_images = len(self.image_train_items)
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logging.info(f" ** Trainer Set: {num_images / self.batch_size:.0f}, num_images: {num_images}, batch_size: {self.batch_size}")
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logging.info(f" ** Dataset '{name}': {num_images / self.batch_size:.0f} batches, num_images: {num_images}, batch_size: {self.batch_size}")
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def get_random_split(self, split_proportion: float, remove_from_dataset: bool=False) -> list[ImageTrainItem]:
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items = self.data_loader.get_random_split(split_proportion, remove_from_dataset)
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