Tensor NotImplementedError

[AWAS666]

Getting this error once I try to start training after a basic install and preparing the data (~400 short wav files).
I'm using a python venv environment instead of conda but installed everything with poetry.

GPU available: True (cuda), used: True
TPU available: False, using: 0 TPU cores
IPU available: False, using: 0 IPUs
HPU available: False, using: 0 HPUs
LOCAL_RANK: 0 - CUDA_VISIBLE_DEVICES: [0]

| Name | Type | Params

0 | model | DiffSinger | 55.1 M
1 | vocoder | NsfHifiGAN | 14.2 M

55.1 M Trainable params
14.2 M Non-trainable params
69.3 M Total params
277.038 Total estimated model params size (MB)
Sanity Checking: 0it [00:00, ?it/s]C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\trainer\connectors\data_connector.py:430: PossibleUserWarning: The dataloader, val_dataloader, does not have many workers which may be a bottleneck. Consider increasing the value of the num_workers argument(try 12 which is the number of cpus on this machine) in theDataLoader` init to improve performance.
rank_zero_warn(
Sanity Checking DataLoader 0: 0%| | 0/2 [00:00<?, ?it/s]Traceback (most recent call last):
File "C:\Users\User\Documents\Testing\fishdiffusion\tools\diffusion\train.py", line 98, in
trainer.fit(model, train_loader, valid_loader, ckpt_path=args.resume)
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 520, in fit
call._call_and_handle_interrupt(
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\trainer\call.py", line 44, in _call_and_handle_interrupt
return trainer_fn(*args, **kwargs)
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 559, in _fit_impl
self._run(model, ckpt_path=ckpt_path)
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 935, in _run
results = self._run_stage()
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 976, in _run_stage
self._run_sanity_check()
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\trainer\trainer.py", line 1005, in _run_sanity_check
val_loop.run()
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\loops\utilities.py", line 177, in _decorator
return loop_run(self, *args, **kwargs)
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\loops\evaluation_loop.py", line 115, in run
self._evaluation_step(batch, batch_idx, dataloader_idx)
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\loops\evaluation_loop.py", line 375, in _evaluation_step
output = call._call_strategy_hook(trainer, hook_name, *step_kwargs.values())
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\trainer\call.py", line 288, in _call_strategy_hook
output = fn(*args, **kwargs)
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\pytorch_lightning\strategies\strategy.py", line 378, in validation_step
return self.model.validation_step(*args, **kwargs)
File "C:\Users\User\Documents\Testing\fishdiffusion\fish_diffusion\archs\diffsinger\diffsinger.py", line 276, in validation_step
return self._step(batch, batch_idx, mode="valid")
File "C:\Users\User\Documents\Testing\fishdiffusion\fish_diffusion\archs\diffsinger\diffsinger.py", line 215, in _step
image_mels, wav_reconstruction, wav_prediction = viz_synth_sample(
File "C:\Users\User\Documents\Testing\fishdiffusion\fish_diffusion\utils\viz.py", line 54, in viz_synth_sample
wav_reconstruction = vocoder.spec2wav(mel_target, pitch)
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "C:\Users\User\Documents\Testing\fishdiffusion\fish_diffusion\modules\vocoders\nsf_hifigan\nsf_hifigan.py", line 81, in spec2wav
y = self.model(c, f0).view(-1)
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\User\Documents\Testing\fishdiffusion\fish_diffusion\modules\vocoders\nsf_hifigan\models.py", line 408, in forward
f0 = F.interpolate(
File "C:\Users\User\Documents\Testing\fishdiffusion\venv\lib\site-packages\torch\nn\functional.py", line 3982, in interpolate
raise NotImplementedError(
NotImplementedError: Input Error: Only 3D, 4D and 5D input Tensors supported (got 2D) for the modes: nearest | linear | bilinear | bicubic | trilinear | area | nearest-exact (got linear)
wandb: Waiting for W&B process to finish... (failed 1). Press Ctrl-C to abort syncing.

[leng-yue]

Thank you for your feedback. This bug fixed in the latest commit: a7aa518