change custom sampler to default
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@@ -99,8 +99,8 @@ def run():
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default=None,
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)
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parser.add_argument(
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"--use_custom_batch_sampler",
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help="Use custom batch sampler for training, which was used in the version < 2.5",
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"--not_use_custom_batch_sampler",
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help="Don't use custom batch sampler for training, which was used in the version < 2.5",
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action="store_true",
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)
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args = parser.parse_args()
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@@ -219,7 +219,7 @@ def run():
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writer_eval = SummaryWriter(log_dir=os.path.join(model_dir, "eval"))
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train_dataset = TextAudioSpeakerLoader(hps.data.training_files, hps.data)
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collate_fn = TextAudioSpeakerCollate(use_jp_extra=True)
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if args.use_custom_batch_sampler:
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if not args.not_use_custom_batch_sampler:
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train_sampler = DistributedBucketSampler(
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train_dataset,
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hps.train.batch_size,
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