Update train_ms.py
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@@ -180,7 +180,7 @@ def train_and_evaluate(rank, epoch, hps, nets, optims, schedulers, scaler, loade
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net_g.train()
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net_d.train()
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for batch_idx, (x, x_lengths, spec, spec_lengths, y, y_lengths, speakers, tone, language, bert) in tqdm(enumerate(train_loader)):
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if net_g.use_noise_scaled_mas:
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if net_g.module.use_noise_scaled_mas:
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current_mas_noise_scale = net_g.module.mas_noise_scale_initial - net_g.module.noise_scale_delta * global_step
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net_g.module.current_mas_noise_scale = max(current_mas_noise_scale, 0.0)
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x, x_lengths = x.cuda(rank, non_blocking=True), x_lengths.cuda(rank, non_blocking=True)
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