Cannot finetune FastPitch on a custom dataset
I followed the finetuning tutorial and tried to finetune the pretrained LJSpeech model with the command
`python examples/tts/fastpitch_finetune.py --config-name=fastpitch_align_v1.05.yaml train_dataset=/root/autodl-tmp/ryanspeech.train.json validation_datasets=/root/autodl-tmp/ryanspeech.val.json sup_data_path=/root/autodl-tmp/nemo-training/ryan_22k/sup_data exp_manager.exp_dir=/root/autodl-tmp/nemo-training/ryan_22k +init_from_nemo_model=/root/autodl-tmp/tts_en_fastpitch_align.nemo  model.train_ds.dataloader_params.batch_size=24 pitch_mean=150.32728576660156 pitch_std=42.45840835571289 pitch_fmin=65.4063949584961 pitch_fmax=1760.0  model.optim.lr=2e-4 ~model.optim.sched`
But I got the error:
```
Traceback (most recent call last):
  File "examples/tts/fastpitch_finetune.py", line 33, in main
    model.maybe_init_from_pretrained_checkpoint(cfg=cfg)
  File "/root/miniconda3/lib/python3.8/site-packages/pytorch_lightning/utilities/rank_zero.py", line 32, in wrapped_fn
    return fn(*args, **kwargs)
  File "/root/NeMo/nemo/core/classes/modelPT.py", line 1066, in maybe_init_from_pretrained_checkpoint
    self.load_state_dict(restored_model.state_dict(), strict=False)
  File "/root/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1482, in load_state_dict
    raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format(
RuntimeError: Error(s) in loading state_dict for FastPitchModel:
        size mismatch for fastpitch.encoder.word_emb.weight: copying a param with shape torch.Size([115, 384]) from checkpoint, the shape in current model is torch.Size([114, 384]).
```
-------------------
EDIT:
seems like it has something to do with the `+model.text_tokenizer.add_blank_at=true` in the tutorial.
Problem solved.