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Add use_distributed_sampler=False in Trainer (#756)
if you have defined your own sampler, you should have to set use_distributed_sampler to False! 当使用自定义的 sampler 时,必须设置 use_distributed_sampler 为 False
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GPT_SoVITS/s1_train.py

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@@ -134,6 +134,7 @@ def main(args):
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logger=logger,
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num_sanity_val_steps=0,
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callbacks=[ckpt_callback],
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use_distributed_sampler=False, # 非常简单的修改,但解决了采用自定义的 bucket_sampler 下训练步数不一致的问题!
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)
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model: Text2SemanticLightningModule = Text2SemanticLightningModule(

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