Cannot train colab with Mixer-TTS-X
Hi, I'm getting an error trying to execute the colab example: https://github.com/NVIDIA/NeMo/blob/main/tutorials/tts/FastPitch_MixerTTS_Training.ipynb with Mixer-TTS-X.

Execution cell:

```
assert isinstance(spec_gen, SpectrogramGenerator)

if isinstance(spec_gen, FastPitchModel):
    tokens = spec_gen.parse(str_input="Hey, this produces speech!")
else:
    tokens = spec_gen.parse(text="Hey, this produces speech!")

spectrogram = spec_gen.generate_spectrogram(tokens=tokens)

# Now we can visualize the generated spectrogram
# If we want to generate speech, we have to use a vocoder in conjunction to a spectrogram generator.
# Refer to the Inference_ModelSelect notebook on how to convert spectrograms to speech.
imshow(spectrogram.cpu().detach().numpy()[0,...], origin="lower")
plt.show()
```
The same error occurs if I try with MixerTTSModel:

```
assert isinstance(spec_gen, SpectrogramGenerator)

if isinstance(spec_gen, MixerTTSModel):
    tokens = spec_gen.parse("Hey, this produces speech!")
else:
    tokens = spec_gen.parse(text="Hey, this produces speech!")

spectrogram = spec_gen.generate_spectrogram(tokens=tokens)

# Now we can visualize the generated spectrogram
# If we want to generate speech, we have to use a vocoder in conjunction to a spectrogram generator.
# Refer to the Inference_ModelSelect notebook on how to convert spectrograms to speech.
imshow(spectrogram.cpu().detach().numpy()[0,...], origin="lower")
plt.show()
```
Just in case, the MixerTTSModel loaded is Mixer-TTS-X:

```
# In the same way, we can load the pre-trained Mixer-TTS model as follows
pretrained_model = "tts_en_lj_mixerttsx"
spec_gen = MixerTTSModel.from_pretrained(pretrained_model)
spec_gen.eval();
```

```
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
[<ipython-input-6-e1795f3aeeee>](https://localhost:8080/#) in <module>
      6     tokens = spec_gen.parse(text="Hey, this produces speech!")
      7 
----> 8 spectrogram = spec_gen.generate_spectrogram(tokens=tokens)
      9 
     10 # Now we can visualize the generated spectrogram

1 frames
[/usr/local/lib/python3.7/dist-packages/nemo/collections/tts/models/mixer_tts.py](https://localhost:8080/#) in generate_spectrogram(self, tokens, tokens_len, lm_tokens, raw_texts, norm_text_for_lm_model, lm_model)
    619         if self.cond_on_lm_embeddings and lm_tokens is None:
    620             if raw_texts is None:
--> 621                 raise ValueError("raw_texts must be specified if lm_tokens is None")
    622 
    623             lm_model_tokenizer = self._get_lm_model_tokenizer(lm_model)

ValueError: raw_texts must be specified if lm_tokens is None
```

Thanks,