RuntimeError: Calculated padded input size per channel: (0). Kernel size: (8). Kernel size can't be greater than actual input size

[intelligenceabhii]

training the model from the given samples in the repo encountring this error
and if i changes the L vaues from the config.py its crashed

/media/wesee/nv_ssd/meta/svoice/train.py:115: UserWarning:
The version_base parameter is not specified.
Please specify a compatability version level, or None.
Will assume defaults for version 1.1
@hydra.main(config_path="conf", config_name='config.yaml')
/home/wesee/miniforge3/lib/python3.10/site-packages/hydra/_internal/defaults_list.py:251: UserWarning: In 'config.yaml': Defaults list is missing _self_. See https://hydra.cc/docs/1.2/upgrades/1.0_to_1.1/default_composition_order for more information
warnings.warn(msg, UserWarning)
/home/wesee/miniforge3/lib/python3.10/site-packages/hydra/_internal/defaults_list.py:415: UserWarning: In config.yaml: Invalid overriding of hydra/job_logging:
Default list overrides requires 'override' keyword.
See https://hydra.cc/docs/1.2/upgrades/1.0_to_1.1/defaults_list_override for more information.

deprecation_warning(msg)
/home/wesee/miniforge3/lib/python3.10/site-packages/hydra/_internal/defaults_list.py:415: UserWarning: In config.yaml: Invalid overriding of hydra/hydra_logging:
Default list overrides requires 'override' keyword.
See https://hydra.cc/docs/1.2/upgrades/1.0_to_1.1/defaults_list_override for more information.

deprecation_warning(msg)
/home/wesee/miniforge3/lib/python3.10/site-packages/hydra/internal/hydra.py:119: UserWarning: Future Hydra versions will no longer change working directory at job runtime by default.
See https://hydra.cc/docs/1.2/upgrades/1.1_to_1.2/changes_to_job_working_dir/ for more information.
ret = run_job(
[2024-09-05 14:35:31,039][main][INFO] - For logs, checkpoints and samples check /media/wesee/nv_ssd/meta/svoice/outputs/exp
[2024-09-05 14:35:34,635][main][INFO] - Running on host ubuntu
[2024-09-05 14:35:36,478][svoice.solver][INFO] - ----------------------------------------------------------------------
[2024-09-05 14:35:36,479][svoice.solver][INFO] - Training...
Input shape to Encoder: torch.Size([4, 32000])
[2024-09-05 14:35:44,215][svoice.solver][INFO] - Train | Epoch 1 | 1/2 | 0.3 it/sec | Loss 24.78669
Input shape to Encoder: torch.Size([4, 32000])
[2024-09-05 14:35:49,408][svoice.solver][INFO] - Train | Epoch 1 | 2/2 | 0.2 it/sec | Loss 20.88289
[2024-09-05 14:35:49,412][svoice.solver][INFO] - Train Summary | End of Epoch 1 | Time 12.93s | Train Loss 20.88289
[2024-09-05 14:35:49,413][svoice.solver][INFO] - ----------------------------------------------------------------------
[2024-09-05 14:35:49,414][svoice.solver][INFO] - Cross validation...
Input shape to Encoder: torch.Size([1, 0])
[2024-09-05 14:35:49,591][main][ERROR] - Some error happened
Traceback (most recent call last):
File "/media/wesee/nv_ssd/meta/svoice/train.py", line 118, in main
_main(args)
File "/media/wesee/nv_ssd/meta/svoice/train.py", line 112, in _main
run(args)
File "/media/wesee/nv_ssd/meta/svoice/train.py", line 93, in run
solver.train()
File "/media/wesee/nv_ssd/meta/svoice/svoice/solver.py", line 131, in train
valid_loss = self._run_one_epoch(epoch, cross_valid=True)
File "/media/wesee/nv_ssd/meta/svoice/svoice/solver.py", line 195, in _run_one_epoch
estimate_source = self.dmodel(mixture)
File "/home/wesee/miniforge3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/home/wesee/miniforge3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
return forward_call(*args, **kwargs)
File "/media/wesee/nv_ssd/meta/svoice/svoice/models/swave.py", line 252, in forward
mixture_w = self.encoder(mixture)
File "/home/wesee/miniforge3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/home/wesee/miniforge3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
return forward_call(*args, **kwargs)
File "/media/wesee/nv_ssd/meta/svoice/svoice/models/swave.py", line 281, in forward
mixture_w = F.relu(self.conv(mixture))
File "/home/wesee/miniforge3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1532, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "/home/wesee/miniforge3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1541, in _call_impl
return forward_call(*args, **kwargs)
File "/home/wesee/miniforge3/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 310, in forward
return self._conv_forward(input, self.weight, self.bias)
File "/home/wesee/miniforge3/lib/python3.10/site-packages/torch/nn/modules/conv.py", line 306, in _conv_forward
return F.conv1d(input, weight, bias, self.stride,
RuntimeError: Calculated padded input size per channel: (0). Kernel size: (8). Kernel size can't be greater than actual input size

how to deal with this