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@ -260,11 +260,11 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
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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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initial_step = embedding.step or 0
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if initial_step > steps:
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return embedding, filename
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scheduler = LearnRateScheduler(learn_rate, steps, ititial_step)
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scheduler = LearnRateScheduler(learn_rate, steps, initial_step)
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optimizer = torch.optim.AdamW([embedding.vec], lr=scheduler.learn_rate)
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if shared.opts.training_enable_tensorboard:
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@ -273,9 +273,9 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
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log_dir=os.path.join(log_directory, "tensorboard"),
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flush_secs=shared.opts.training_tensorboard_flush_every)
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pbar = tqdm.tqdm(enumerate(ds), total=steps-ititial_step)
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pbar = tqdm.tqdm(enumerate(ds), total=steps-initial_step)
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for i, entries in pbar:
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embedding.step = i + ititial_step
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embedding.step = i + initial_step
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scheduler.apply(optimizer, embedding.step)
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if scheduler.finished:
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