feat: generation options for infer.py, and split out training deps

infer.py could only render a random example from examples/input_params:
there was no way to pass your own prompt, lyrics, duration or seed, so
using it for anything specific meant writing a separate script. Add
--prompt, --lyrics/--lyrics_file, --duration, --steps, --guidance_scale,
--scheduler, --cfg_type, --omega_scale, --seed and --format alongside the
existing runtime flags. Without --prompt the old random-example behaviour
is kept, so existing invocations are unaffected.

Also move the training-only packages out of the default install.
datasets, pytorch_lightning, matplotlib, tensorboard and tensorboardX are
imported by trainer.py and convert2hf_dataset.py, never on the inference
path, but every user was installing them — and datasets==3.4.1 is a hard
pin that drags constraints onto huggingface-hub. They now live in
requirements-train.txt behind the existing (previously ineffective)
"train" extra: pip install -e ".[train]".

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>

requirements.txt

@@ -1,12 +1,9 @@
-datasets==3.4.1
 diffusers>=0.33.0
 gradio>=6.0.0
 librosa==0.11.0
 loguru==0.7.3
-matplotlib==3.10.1
 numpy
 pypinyin==0.53.0
-pytorch_lightning==2.5.1
 soundfile==0.13.1
 torch
 torchaudio
@@ -22,5 +19,3 @@ cutlet
 fugashi[unidic-lite]
 click
 peft
-tensorboard
-tensorboardX