datong-new/rvc 🖼️🔢❓✓ → ❓
Performance
262.9sTypical run time
4.0KTotal runs
Example Output
Output
Performance Metrics
262.95s
Prediction Time
427.94s
Total Time
All Input Parameters
{
"f0_up_key": 8,
"operation": "train_infer",
"accompaniment": true,
"audio_for_infer": "https://replicate.delivery/pbxt/KSuE9SkdHEsXPUlZmWj4kMwRNZwJ0CR0EFTzjJAwVqKY8brY/1.wav",
"audio_for_train": "https://replicate.delivery/pbxt/KSuE9M9iVBPPXjGWfkGpiwD9iZOlHSwAwVmX0vHaA2hJ41Ca/wobunanguo.flac"
}
Input Parameters
- ckpt
- your trained checkpoint
- f0_up_key
- f0_up_key
- operation (required)
- 1. train (audio_for_train is needed); 2 infer (audio_for_infer and ckpt is needed); 3. train_infer (audio_for_train and audio_for_infer is needed)
- accompaniment
- if output have accompaniment (for music clone)
- audio_for_infer
- audio file for cloning
- audio_for_train
- audio file for train
Output Schema
- ckpt_path
- Ckpt Path
- cloned_audio
- Cloned Audio
Example Execution Logs
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2024-02-25 12:49:19 | INFO | fairseq.tasks.hubert_pretraining | current directory is /src
2024-02-25 12:49:19 | INFO | fairseq.tasks.hubert_pretraining | HubertPretrainingTask Config {'_name': 'hubert_pretraining', 'data': 'metadata', 'fine_tuning': False, 'labels': ['km'], 'label_dir': 'label', 'label_rate': 50.0, 'sample_rate': 16000, 'normalize': False, 'enable_padding': False, 'max_keep_size': None, 'max_sample_size': 250000, 'min_sample_size': 32000, 'single_target': False, 'random_crop': True, 'pad_audio': False}
2024-02-25 12:49:19 | INFO | fairseq.models.hubert.hubert | HubertModel Config: {'_name': 'hubert', 'label_rate': 50.0, 'extractor_mode': default, 'encoder_layers': 12, 'encoder_embed_dim': 768, 'encoder_ffn_embed_dim': 3072, 'encoder_attention_heads': 12, 'activation_fn': gelu, 'layer_type': transformer, 'dropout': 0.1, 'attention_dropout': 0.1, 'activation_dropout': 0.0, 'encoder_layerdrop': 0.05, 'dropout_input': 0.1, 'dropout_features': 0.1, 'final_dim': 256, 'untie_final_proj': True, 'layer_norm_first': False, 'conv_feature_layers': '[(512,10,5)] + [(512,3,2)] * 4 + [(512,2,2)] * 2', 'conv_bias': False, 'logit_temp': 0.1, 'target_glu': False, 'feature_grad_mult': 0.1, 'mask_length': 10, 'mask_prob': 0.8, 'mask_selection': static, 'mask_other': 0.0, 'no_mask_overlap': False, 'mask_min_space': 1, 'mask_channel_length': 10, 'mask_channel_prob': 0.0, 'mask_channel_selection': static, 'mask_channel_other': 0.0, 'no_mask_channel_overlap': False, 'mask_channel_min_space': 1, 'conv_pos': 128, 'conv_pos_groups': 16, 'latent_temp': [2.0, 0.5, 0.999995], 'skip_masked': False, 'skip_nomask': False, 'checkpoint_activations': False, 'required_seq_len_multiple': 2, 'depthwise_conv_kernel_size': 31, 'attn_type': '', 'pos_enc_type': 'abs', 'fp16': False}
/root/.pyenv/versions/3.8.10/lib/python3.8/site-packages/torch/nn/utils/weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
/root/.pyenv/versions/3.8.10/lib/python3.8/site-packages/torch/nn/utils/weight_norm.py:28: UserWarning: torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.
warnings.warn("torch.nn.utils.weight_norm is deprecated in favor of torch.nn.utils.parametrizations.weight_norm.")
/root/.pyenv/versions/3.8.10/lib/python3.8/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
/root/.pyenv/versions/3.8.10/lib/python3.8/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
/root/.pyenv/versions/3.8.10/lib/python3.8/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
/root/.pyenv/versions/3.8.10/lib/python3.8/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
/root/.pyenv/versions/3.8.10/lib/python3.8/site-packages/torch/functional.py:660: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at ../aten/src/ATen/native/SpectralOps.cpp:874.)
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
/root/.pyenv/versions/3.8.10/lib/python3.8/site-packages/torch/autograd/__init__.py:266: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance.
grad.sizes() = [64, 1, 4], strides() = [4, 1, 1]
bucket_view.sizes() = [64, 1, 4], strides() = [4, 4, 1] (Triggered internally at ../torch/csrc/distributed/c10d/reducer.cpp:322.)
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
/root/.pyenv/versions/3.8.10/lib/python3.8/multiprocessing/resource_tracker.py:216: UserWarning: resource_tracker: There appear to be 20 leaked semaphore objects to clean up at shutdown
warnings.warn('resource_tracker: There appear to be %d '
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Version Details
- Version ID
5da9f66869beacc8f2484215e25c88053acfe24044d64d4b26bbc40f7b5428dc- Version Created
- February 26, 2024