Giter Club home page Giter Club logo

Comments (6)

yqzhishen avatar yqzhishen commented on July 30, 2024

You are not using our repository directly. Please raise your issue to the repository you are using.

from diffsinger.

c7e715d1b04b17683718fb1e8944cc28 avatar c7e715d1b04b17683718fb1e8944cc28 commented on July 30, 2024

Sorry, but this error also occurs when using the DiffSinger repository directly.

Traceback (most recent call last):
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\scripts\train.py", line 31, in <module>
    run_task()
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\scripts\train.py", line 27, in run_task
    task_cls.start()
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\basics\base_task.py", line 467, in start
    trainer.fit(task, ckpt_path=get_latest_checkpoint_path(work_dir))
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\trainer\trainer.py", line 544, in fit
    call._call_and_handle_interrupt(
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\trainer\call.py", line 44, in _call_and_handle_interrupt
    return trainer_fn(*args, **kwargs)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\trainer\trainer.py", line 580, in _fit_impl
    self._run(model, ckpt_path=ckpt_path)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\trainer\trainer.py", line 989, in _run
    results = self._run_stage()
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\trainer\trainer.py", line 1035, in _run_stage
    self.fit_loop.run()
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\loops\fit_loop.py", line 202, in run
    self.advance()
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\loops\fit_loop.py", line 359, in advance
    self.epoch_loop.run(self._data_fetcher)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\loops\training_epoch_loop.py", line 136, in run
    self.advance(data_fetcher)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\loops\training_epoch_loop.py", line 240, in advance
    batch_output = self.automatic_optimization.run(trainer.optimizers[0], batch_idx, kwargs)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\loops\optimization\automatic.py", line 187, in run
    self._optimizer_step(batch_idx, closure)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\loops\optimization\automatic.py", line 265, in _optimizer_step
    call._call_lightning_module_hook(
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\trainer\call.py", line 157, in _call_lightning_module_hook
    output = fn(*args, **kwargs)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\core\module.py", line 1291, in optimizer_step
    optimizer.step(closure=optimizer_closure)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\core\optimizer.py", line 151, in step
    step_output = self._strategy.optimizer_step(self._optimizer, closure, **kwargs)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\strategies\strategy.py", line 230, in optimizer_step
    return self.precision_plugin.optimizer_step(optimizer, model=model, closure=closure, **kwargs)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\plugins\precision\amp.py", line 77, in optimizer_step
    closure_result = closure()
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\loops\optimization\automatic.py", line 140, in __call__
    self._result = self.closure(*args, **kwargs)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\loops\optimization\automatic.py", line 126, in closure
    step_output = self._step_fn()
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\loops\optimization\automatic.py", line 318, in _training_step
    return self.output_result_cls.from_training_step_output(training_step_output, trainer.accumulate_grad_batches)
  File "D:\Users\ikki1\Desktop\Projects\DiffSinger\.venv\lib\site-packages\lightning\pytorch\loops\optimization\automatic.py", line 72, in from_training_step_output
    raise MisconfigurationException(
lightning.fabric.utilities.exceptions.MisconfigurationException: In automatic optimization, `training_step` must return a Tensor, a dict, or None (where the step will be skipped).

from diffsinger.

yqzhishen avatar yqzhishen commented on July 30, 2024

Can you upload your config file?

from diffsinger.

c7e715d1b04b17683718fb1e8944cc28 avatar c7e715d1b04b17683718fb1e8944cc28 commented on July 30, 2024

Okay.
from the DiffSinger curriculum.
https://openvpi-docs.feishu.cn/wiki/Mt13w6wUaiI0zUkN2wkcwyWBndh

base_config: configs/variance.yaml

raw_data_dir: 
  - data/20240617225409/raw

speakers: 
  - "20240617225409"

spk_ids: []

test_prefixes: 
  - _ああいあうえあ_N_A#2 
  - _ああいあうえあ_N_A#2
  - _ああいあうえあ_N_A3 
  - _ああいあうえあ_N_B2
  - _ああいあうえあ_N_C#3

dictionary: dictionaries/jpn_dict.txt

binary_data_dir: data/20240617225409/binary

binarization_args: 
  num_workers: 0 

use_spk_id: false 

num_spk: 1

predict_dur: false
predict_pitch: false
predict_energy: false
predict_breathiness: false
predict_voicing: false
predict_tension: false

energy_db_min: -96.0
energy_db_max: -12.0

breathiness_db_min: -96.0
breathiness_db_max: -20.0

voicing_db_min: -96.0
voicing_db_max: -12.0

tension_logit_min: -10.0
tension_logit_max: 10.0

hidden_size: 256
dur_prediction_args:
  arch: fs2
  hidden_size: 512
  dropout: 0.1
  num_layers: 5
  kernel_size: 3
  log_offset: 1.0
  loss_type: mse
  lambda_pdur_loss: 0.3
  lambda_wdur_loss: 1.0
  lambda_sdur_loss: 3.0

use_melody_encoder: false
melody_encoder_args:
  hidden_size: 128
  enc_layers: 4
use_glide_embed: false
glide_types: [up, down]
glide_embed_scale: 11.313708498984760

pitch_prediction_args:
  pitd_norm_min: -8.0
  pitd_norm_max: 8.0
  pitd_clip_min: -12.0
  pitd_clip_max: 12.0
  repeat_bins: 64
  residual_layers: 20
  residual_channels: 256
  dilation_cycle_length: 5  # *

variances_prediction_args:
  total_repeat_bins: 48
  residual_layers: 10
  residual_channels: 192
  dilation_cycle_length: 4  # *

lambda_dur_loss: 1.0
lambda_pitch_loss: 1.0
lambda_var_loss: 1.0

optimizer_args: 
  lr: 0.0006 
lr_scheduler_args:
  scheduler_cls: torch.optim.lr_scheduler.StepLR
  step_size: 10000
  gamma: 0.75

max_batch_frames: 80000

max_batch_size: 9

max_updates: 160000

num_valid_plots: 10

val_check_interval: 2000

num_ckpt_keep: 5

permanent_ckpt_start: 80000 

permanent_ckpt_interval: 10000

pl_trainer_devices: 'auto'

pl_trainer_precision: '16-mixed'

from diffsinger.

yqzhishen avatar yqzhishen commented on July 30, 2024

Please at least turn on one predict_* switch. Otherwise the model has nothing to train.

from diffsinger.

c7e715d1b04b17683718fb1e8944cc28 avatar c7e715d1b04b17683718fb1e8944cc28 commented on July 30, 2024

Thank you! You've been very helpful.
We apologize for the inconvenience.

from diffsinger.

Related Issues (20)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.