mrq/vall-e
5
9
Fork 0
Code Issues 8 Pull Requests Packages Projects Releases Wiki Activity

kludge fix for an oversight in the model when trying to train for longer input prompt durations......

Browse Source
This commit is contained in:
mrq 2024-10-15 19:25:03 -05:00
parent 84005c5b00
commit eea70f5698
2 changed files with 9 additions and 3 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
vall_e/inference.py
View File

@ -11,7 +11,7 @@ from einops import rearrange
from pathlib import Path
from .emb import g2p, qnt
from .emb.qnt import trim, trim_random, unload_model
from .emb.qnt import trim, trim_random, unload_model, repeat_extend_audio
from .utils import to_device, set_seed, wrapper as ml
from .config import cfg, Config
@ -103,7 +103,7 @@ class TTS():
return torch.tensor([ id ])
# to-do: trim before quantizing, instead of after
def encode_audio( self, paths, trim_length=0.0 ):
def encode_audio( self, paths, trim_length=9.0 ):
# already a tensor, return it
if isinstance( paths, Tensor ):
return paths
@ -126,8 +126,14 @@ class TTS():
res = torch.cat(proms)
# kludge, but it's to correct an oversight in training
if trim_length:
res = repeat_extend_audio( res, cfg.dataset.frames_per_second * trim_length )
"""
if trim_length:
res = trim( res, int( cfg.dataset.frames_per_second * trim_length ) )
"""
return res

2
vall_e/webui.py
View File

@ -346,7 +346,7 @@ with ui:
with gr.Row():
layout["inference_tts"]["inputs"]["max-seconds"] = gr.Slider(value=12, minimum=1, maximum=32, step=0.1, label="Maximum Seconds", info="Limits how many steps to perform in the AR pass.")
#layout["inference_tts"]["inputs"]["max-nar-levels"] = gr.Slider(value=7, minimum=0, maximum=7, step=1, label="Max NAR Levels", info="Limits how many steps to perform in the NAR pass.")
layout["inference_tts"]["inputs"]["input-prompt-length"] = gr.Slider(value=3.0, minimum=0.0, maximum=12.0, step=0.05, label="Input Prompt Trim Length", info="Trims the input prompt down to X seconds. Set 0 to disable.")
layout["inference_tts"]["inputs"]["input-prompt-length"] = gr.Slider(value=9.0, minimum=0.0, maximum=12.0, step=0.05, label="Input Prompt Trim Length", info="Trims the input prompt down to X seconds. Set 0 to disable.")
with gr.Row():
layout["inference_tts"]["inputs"]["ar-temp"] = gr.Slider(value=1.0, minimum=0.0, maximum=1.5, step=0.05, label="Temperature (AR)", info="Modifies the randomness from the samples in the AR. (0 to greedy sample)")
layout["inference_tts"]["inputs"]["nar-temp"] = gr.Slider(value=0.0, minimum=0.0, maximum=1.5, step=0.05, label="Temperature (NAR)", info="Modifies the randomness from the samples in the NAR. (0 to greedy sample)")