only save 1 image per embedding
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9e846083b7
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@ -242,6 +242,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
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last_saved_file = "<none>"
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last_saved_image = "<none>"
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embedding_yet_to_be_embedded = False
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ititial_step = embedding.step or 0
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if ititial_step > steps:
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@ -281,6 +282,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
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if embedding.step > 0 and embedding_dir is not None and embedding.step % save_embedding_every == 0:
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last_saved_file = os.path.join(embedding_dir, f'{embedding_name}-{embedding.step}.pt')
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embedding.save(last_saved_file)
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embedding_yet_to_be_embedded = True
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write_loss(log_directory, "textual_inversion_loss.csv", embedding.step, len(ds), {
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"loss": f"{losses.mean():.7f}",
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@ -318,7 +320,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
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shared.state.current_image = image
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if save_image_with_stored_embedding and os.path.exists(last_saved_file):
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if save_image_with_stored_embedding and os.path.exists(last_saved_file) and embedding_yet_to_be_embedded:
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last_saved_image_chunks = os.path.join(images_embeds_dir, f'{embedding_name}-{embedding.step}.png')
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@ -342,6 +344,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
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captioned_image = insert_image_data_embed(captioned_image, data)
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captioned_image.save(last_saved_image_chunks, "PNG", pnginfo=info)
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embedding_yet_to_be_embedded = False
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image.save(last_saved_image)
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