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/app/train_dvae_xtts.py:87: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  dvae.load_state_dict(torch.load(dvae_pretrained), strict=False)
/app/TTS/tts/layers/tortoise/arch_utils.py:336: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
  self.mel_norms = torch.load(f)
 | > Found 36938 files in /app/data
 > Filtering invalid eval samples!!
 > Total eval samples after filtering: 203
 > Sampling by language: dict_keys(['luo'])
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#######################################
epoch: 0	EVAL loss: 0.053402652963995934
#######################################
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#######################################
epoch: 1	EVAL loss: 0.04333304241299629
#######################################
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#######################################
epoch: 2	EVAL loss: 0.039518384262919426
#######################################
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#######################################
epoch: 3	EVAL loss: 0.0373398307710886
#######################################
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#######################################
epoch: 4	EVAL loss: 0.03582187369465828
#######################################
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#######################################
epoch: 5	EVAL loss: 0.034729933366179466
#######################################
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#######################################
epoch: 6	EVAL loss: 0.03389867767691612
#######################################
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#######################################
epoch: 7	EVAL loss: 0.033447377383708954
#######################################
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#######################################
epoch: 8	EVAL loss: 0.032998230308294296
#######################################
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epoch: 9 None loss - 0.031148333102464676 recon_loss - 0.018874969333410263 commit_loss - 0.012273363769054413
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epoch: 9 None loss - 0.03212989866733551 recon_loss - 0.01960102654993534 commit_loss - 0.01252887211740017
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epoch: 9 None loss - 0.031921327114105225 recon_loss - 0.019322898238897324 commit_loss - 0.01259843073785305
#######################################
epoch: 9	EVAL loss: 0.03248552605509758
#######################################
Checkpoint saved at /app/xtts_luo/XTTS_v2.0_original_model_files/dvae.pth