Comments (5)
- I typically use two GPUs with 24 GB of memory each for training.
- If you want to change the amount of dataset, you just need to edit the number of data indexes in
MP-SENet/VoiceBank+DEMAND/training.txt
andtest.txt
.
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Dear Author,
Thank you for responding to my question. I'm not sure if the GPU memory used for this training can be reduced ...
Can I try to change the dense_channel to achieve this goal, or change some parameters (except batch_size)?
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- Sure, you can reduce GPU memory usage by decreasing the number of dense channels or by reducing the segment size in the
config.json
. However, these changes may affect the final training results. - By the way, you need to determine whether your GPU memory is insufficient during training or validation. During validation, the audio sequences are not truncated, which can cause variations in GPU memory usage. If you are experiencing memory issues only during validation, you can implement truncation as a solution.
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Dear Author,
I try to decrease the number of dense channels in config.json
to make it train successfully. However, when I implement the inference, I decreasing the number of dense channels in best_ckpt/config.json
, it would appear size mismatch problem, I want to know the config.json
in best_ckpt
cannot change the dense channel ?
Sorry to bother the author's time !
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The checkpoint file in best_ckpt
is the pre-trained best checkpoint with the default dense channel, which is unchangeable. You should use your self-trained checkpoint for inference.
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Related Issues (20)
- Result is bad HOT 3
- Fail to reproduce the paper result when training from scratch HOT 15
- Question about phase-domain loss employment HOT 1
- 作者给的模型推理结果达不到论文结果,求问 HOT 4
- 训练的话,training.txt的内容,十分困惑 HOT 1
- UnboundLocalError: local variable 'metric_error' referenced before assignment HOT 5
- Sample rate (fs) - No default. Must select either 8000 or 16000. HOT 6
- Incoherent dimensions in the self-attention module HOT 4
- Wrong default path HOT 2
- 验证集和测试集是怎么划分的? HOT 1
- 能在Windows上部署吗? HOT 1
- 去混响数据集会公开吗? HOT 11
- Dereverberation HOT 1
- 请问有什么降低MetricLoss的好方法吗 HOT 2
- Weights trained on DNS HOT 2
- Performance with PCS HOT 1
- Questions with regards to reproducing training and inference result HOT 2
- NS and BE(SR) in one model design HOT 1
- Complex loss calculated using compressed magnitude HOT 2
- Error dividing by zero if noisy_audio is silence HOT 1
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