Fix dataset still being loaded even when training will be skipped
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@ -364,7 +364,7 @@ def train_hypernetwork(hypernetwork_name, learn_rate, batch_size, data_root, log
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checkpoint = sd_models.select_checkpoint()
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ititial_step = hypernetwork.step or 0
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if ititial_step > steps:
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if ititial_step >= steps:
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shared.state.textinfo = f"Model has already been trained beyond specified max steps"
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return hypernetwork, filename
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@ -262,7 +262,7 @@ def train_embedding(embedding_name, learn_rate, batch_size, data_root, log_direc
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checkpoint = sd_models.select_checkpoint()
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ititial_step = embedding.step or 0
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if ititial_step > steps:
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if ititial_step >= steps:
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shared.state.textinfo = f"Model has already been trained beyond specified max steps"
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return embedding, filename
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