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@ -6,6 +6,7 @@ import torch
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import tqdm
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import html
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import datetime
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import csv
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from PIL import Image, PngImagePlugin
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@ -256,6 +257,21 @@ def train_embedding(embedding_name, learn_rate, data_root, log_directory, traini
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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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if write_csv_every > 0 and log_directory is not None and embedding.step % write_csv_every == 0:
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write_csv_header = False if os.path.exists(os.path.join(log_directory, "textual_inversion_loss.csv")) else True
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with open(os.path.join(log_directory, "textual_inversion_loss.csv"), "a+") as fout:
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csv_writer = csv.DictWriter(fout, fieldnames=["epoch", "epoch_step", "loss", "learn_rate"])
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if write_csv_header:
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csv_writer.writeheader()
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csv_writer.writerow({"epoch": epoch_num + 1,
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"epoch_step": epoch_step - 1,
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"loss": f"{losses.mean():.7f}",
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"learn_rate": scheduler.learn_rate})
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if embedding.step > 0 and images_dir is not None and embedding.step % create_image_every == 0:
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last_saved_image = os.path.join(images_dir, f'{embedding_name}-{embedding.step}.png')
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