Colab notebook (part 1)
This commit is contained in:
parent
efa556b793
commit
3d6ac3afaa
27
main.py
Executable file
27
main.py
Executable file
|
@ -0,0 +1,27 @@
|
|||
import webui as mrq
|
||||
|
||||
if __name__ == "__main__":
|
||||
mrq.args = mrq.setup_args()
|
||||
|
||||
if mrq.args.listen_path is not None and mrq.args.listen_path != "/":
|
||||
import uvicorn
|
||||
uvicorn.run("main:app", host=mrq.args.listen_host, port=mrq.args.listen_port if not None else 8000)
|
||||
else:
|
||||
mrq.webui = mrq.setup_gradio()
|
||||
mrq.webui.launch(share=mrq.args.share, prevent_thread_lock=True, server_name=mrq.args.listen_host, server_port=mrq.args.listen_port)
|
||||
mrq.tts = mrq.setup_tortoise()
|
||||
|
||||
mrq.webui.block_thread()
|
||||
elif __name__ == "main":
|
||||
from fastapi import FastAPI
|
||||
import gradio as gr
|
||||
|
||||
import sys
|
||||
sys.argv = [sys.argv[0]]
|
||||
|
||||
app = FastAPI()
|
||||
mrq.args = mrq.setup_args()
|
||||
mrq.webui = mrq.setup_gradio()
|
||||
app = gr.mount_gradio_app(app, mrq.webui, path=mrq.args.listen_path)
|
||||
|
||||
mrq.tts = mrq.setup_tortoise()
|
|
@ -1,4 +1,4 @@
|
|||
call .\tortoise-venv\Scripts\activate.bat
|
||||
python app.py
|
||||
python main.py
|
||||
deactivate
|
||||
pause
|
2
start.sh
2
start.sh
|
@ -1,3 +1,3 @@
|
|||
source ./tortoise-venv/bin/activate
|
||||
python ./app.py
|
||||
python3 ./main.py
|
||||
deactivate
|
||||
|
|
186
tortoise_tts.ipynb
Normal file → Executable file
186
tortoise_tts.ipynb
Normal file → Executable file
|
@ -1,185 +1 @@
|
|||
{
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 0,
|
||||
"metadata": {
|
||||
"colab": {
|
||||
"name": "tortoise-tts.ipynb",
|
||||
"provenance": [],
|
||||
"collapsed_sections": []
|
||||
},
|
||||
"kernelspec": {
|
||||
"name": "python3",
|
||||
"display_name": "Python 3"
|
||||
},
|
||||
"language_info": {
|
||||
"name": "python"
|
||||
},
|
||||
"accelerator": "GPU"
|
||||
},
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"source": [
|
||||
"Welcome to Tortoise! 🐢🐢🐢🐢\n",
|
||||
"\n",
|
||||
"Before you begin, I **strongly** recommend you turn on a GPU runtime.\n",
|
||||
"\n",
|
||||
"There's a reason this is called \"Tortoise\" - this model takes up to a minute to perform inference for a single sentence on a GPU. Expect waits on the order of hours on a CPU."
|
||||
],
|
||||
"metadata": {
|
||||
"id": "_pIZ3ZXNp7cf"
|
||||
}
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "JrK20I32grP6"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"!git clone https://github.com/neonbjb/tortoise-tts.git\n",
|
||||
"%cd tortoise-tts\n",
|
||||
"!pip3 install -r requirements.txt\n",
|
||||
"!python3 setup.py install"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"# Imports used through the rest of the notebook.\n",
|
||||
"import torch\n",
|
||||
"import torchaudio\n",
|
||||
"import torch.nn as nn\n",
|
||||
"import torch.nn.functional as F\n",
|
||||
"\n",
|
||||
"import IPython\n",
|
||||
"\n",
|
||||
"from tortoise.api import TextToSpeech\n",
|
||||
"from tortoise.utils.audio import load_audio, load_voice, load_voices\n",
|
||||
"\n",
|
||||
"# This will download all the models used by Tortoise from the HF hub.\n",
|
||||
"tts = TextToSpeech()"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "Gen09NM4hONQ"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"# This is the text that will be spoken.\n",
|
||||
"text = \"Joining two modalities results in a surprising increase in generalization! What would happen if we combined them all?\"\n",
|
||||
"\n",
|
||||
"# Here's something for the poetically inclined.. (set text=)\n",
|
||||
"\"\"\"\n",
|
||||
"Then took the other, as just as fair,\n",
|
||||
"And having perhaps the better claim,\n",
|
||||
"Because it was grassy and wanted wear;\n",
|
||||
"Though as for that the passing there\n",
|
||||
"Had worn them really about the same,\"\"\"\n",
|
||||
"\n",
|
||||
"# Pick a \"preset mode\" to determine quality. Options: {\"ultra_fast\", \"fast\" (default), \"standard\", \"high_quality\"}. See docs in api.py\n",
|
||||
"preset = \"fast\""
|
||||
],
|
||||
"metadata": {
|
||||
"id": "bt_aoxONjfL2"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"# Tortoise will attempt to mimic voices you provide. It comes pre-packaged\n",
|
||||
"# with some voices you might recognize.\n",
|
||||
"\n",
|
||||
"# Let's list all the voices available. These are just some random clips I've gathered\n",
|
||||
"# from the internet as well as a few voices from the training dataset.\n",
|
||||
"# Feel free to add your own clips to the voices/ folder.\n",
|
||||
"%ls tortoise/voices\n",
|
||||
"\n",
|
||||
"IPython.display.Audio('tortoise/voices/tom/1.wav')"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "SSleVnRAiEE2"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"# Pick one of the voices from the output above\n",
|
||||
"voice = 'tom'\n",
|
||||
"\n",
|
||||
"# Load it and send it through Tortoise.\n",
|
||||
"voice_samples, conditioning_latents = load_voice(voice)\n",
|
||||
"gen = tts.tts_with_preset(text, voice_samples=voice_samples, conditioning_latents=conditioning_latents, \n",
|
||||
" preset=preset)\n",
|
||||
"torchaudio.save('generated.wav', gen.squeeze(0).cpu(), 24000)\n",
|
||||
"IPython.display.Audio('generated.wav')"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "KEXOKjIvn6NW"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"# Tortoise can also generate speech using a random voice. The voice changes each time you execute this!\n",
|
||||
"# (Note: random voices can be prone to strange utterances)\n",
|
||||
"gen = tts.tts_with_preset(text, voice_samples=None, conditioning_latents=None, preset=preset)\n",
|
||||
"torchaudio.save('generated.wav', gen.squeeze(0).cpu(), 24000)\n",
|
||||
"IPython.display.Audio('generated.wav')"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "16Xs2SSC3BXa"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"# You can also combine conditioning voices. Combining voices produces a new voice\n",
|
||||
"# with traits from all the parents.\n",
|
||||
"#\n",
|
||||
"# Lets see what it would sound like if Picard and Kirk had a kid with a penchant for philosophy:\n",
|
||||
"voice_samples, conditioning_latents = load_voices(['pat', 'william'])\n",
|
||||
"\n",
|
||||
"gen = tts.tts_with_preset(\"They used to say that if man was meant to fly, he’d have wings. But he did fly. He discovered he had to.\", \n",
|
||||
" voice_samples=None, conditioning_latents=None, preset=preset)\n",
|
||||
"torchaudio.save('captain_kirkard.wav', gen.squeeze(0).cpu(), 24000)\n",
|
||||
"IPython.display.Audio('captain_kirkard.wav')"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "fYTk8KUezUr5"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"del tts # Will break other cells, but necessary to conserve RAM if you want to run this cell.\n",
|
||||
"\n",
|
||||
"# Tortoise comes with some scripts that does a lot of the lifting for you. For example,\n",
|
||||
"# read.py will read a text file for you.\n",
|
||||
"!python3 tortoise/read.py --voice=train_atkins --textfile=tortoise/data/riding_hood.txt --preset=ultra_fast --output_path=.\n",
|
||||
"\n",
|
||||
"IPython.display.Audio('train_atkins/combined.wav')\n",
|
||||
"# This will take awhile.."
|
||||
],
|
||||
"metadata": {
|
||||
"id": "t66yqWgu68KL"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
}
|
||||
]
|
||||
}
|
||||
{"nbformat":4,"nbformat_minor":0,"metadata":{"colab":{"private_outputs":true,"provenance":[]},"kernelspec":{"name":"python3","display_name":"Python 3"},"language_info":{"name":"python"},"accelerator":"GPU","gpuClass":"standard"},"cells":[{"cell_type":"markdown","source":["## Initialization"],"metadata":{"id":"ni41hmE03DL6"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"FtsMKKfH18iM"},"outputs":[],"source":["!git clone https://git.ecker.tech/mrq/tortoise-tts/\n","%cd tortoise-tts\n","!python -m pip install --upgrade pip\n","!pip install torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/cu116\n","!python -m pip install -r ./requirements.txt\n","!pip install Pillow==9.0.0 # errors out only when importing\n","!python setup.py install"]},{"cell_type":"markdown","source":["## Running"],"metadata":{"id":"o1gkfw3B3JSk"}},{"cell_type":"code","source":["import webui as mrq\n","\n","mrq.args = mrq.setup_args()\n","mrq.webui = mrq.setup_gradio()\n","mrq.webui.launch(share=True, prevent_thread_lock=True)\n","mrq.tts = mrq.setup_tortoise()\n","mrq.webui.block_thread()"],"metadata":{"id":"c_EQZLTA19c7"},"execution_count":null,"outputs":[]}]}
|
|
@ -20,6 +20,10 @@ from tortoise.api import TextToSpeech
|
|||
from tortoise.utils.audio import load_audio, load_voice, load_voices
|
||||
from tortoise.utils.text import split_and_recombine_text
|
||||
|
||||
args = None
|
||||
webui = None
|
||||
tts = None
|
||||
|
||||
def generate(text, delimiter, emotion, prompt, voice, mic_audio, seed, candidates, num_autoregressive_samples, diffusion_iterations, temperature, diffusion_sampler, breathing_room, cvvp_weight, experimentals, progress=gr.Progress(track_tqdm=True)):
|
||||
try:
|
||||
tts
|
||||
|
@ -424,7 +428,7 @@ def setup_args():
|
|||
args.listen_host = None
|
||||
args.listen_port = None
|
||||
args.listen_path = None
|
||||
if args.listen is not None:
|
||||
if args.listen:
|
||||
match = re.findall(r"^(?:(.+?):(\d+))?(\/.+?)?$", args.listen)[0]
|
||||
|
||||
args.listen_host = match[0] if match[0] != "" else "127.0.0.1"
|
||||
|
@ -623,29 +627,4 @@ def setup_gradio():
|
|||
|
||||
webui.queue(concurrency_count=args.concurrency_count)
|
||||
|
||||
return webui
|
||||
|
||||
if __name__ == "__main__":
|
||||
args = setup_args()
|
||||
|
||||
if args.listen_path is not None and args.listen_path != "/":
|
||||
import uvicorn
|
||||
uvicorn.run("app:app", host=args.listen_host, port=args.listen_port if not None else 8000)
|
||||
else:
|
||||
webui = setup_gradio()
|
||||
webui.launch(share=args.share, prevent_thread_lock=True, server_name=args.listen_host, server_port=args.listen_port)
|
||||
tts = setup_tortoise()
|
||||
|
||||
webui.block_thread()
|
||||
elif __name__ == "app":
|
||||
import sys
|
||||
from fastapi import FastAPI
|
||||
|
||||
sys.argv = [sys.argv[0]]
|
||||
|
||||
app = FastAPI()
|
||||
args = setup_args()
|
||||
webui = setup_gradio()
|
||||
app = gr.mount_gradio_app(app, webui, path=args.listen_path)
|
||||
|
||||
tts = setup_tortoise()
|
||||
return webui
|
Loading…
Reference in New Issue
Block a user