RuntimeError: The size of tensor a (1191) must match the size of tensor b (1000) at non-singleton dimension 1

[godspirit00]

Hi,
Thanks for the great work.
I met an error when training on the ryanspeech dataset:

Traceback (most recent call last):
  File "train.py", line 254, in <module>
    train(0, args, configs, batch_size, num_gpus)
  File "train.py", line 110, in train
    losses = Loss(batch, output, step=step)
  File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
    return forward_call(*input, **kwargs)
  File "/root/Comprehensive-Transformer-TTS/model/loss.py", line 334, in forward
    pitch_loss = self.get_pitch_loss(pitch_predictions, pitch_targets)
  File "/root/Comprehensive-Transformer-TTS/model/loss.py", line 197, in get_pitch_loss
    losses["uv"] = (F.binary_cross_entropy_with_logits(uv_pred, uv, reduction="none") * nonpadding) \
RuntimeError: The size of tensor a (1191) must match the size of tensor b (1000) at non-singleton dimension 1

I printed the shape of both uv_pred and uv, and they were both [16, 1191].

My configuration is

 ---> Automatic Mixed Precision: True
 ---> Number of used GPU: 1
 ---> Batch size per GPU: 16
 ---> Batch size in total: 16
 ---> Type of Building Block: conformer
 ---> Type of Duration Modeling: supervised
 ---> Type of Prosody Modeling: liu2021

This happened at around 50k+ steps.
What am I missing? Thank you!