rsxdalv
commented
1 week ago Smaller reproduction:
# ruff: noqa: E402
# %%
# ruff: noqa: E402
# Above allows ruff to ignore E402: module level import not at top of file
# MIT License
# Copyright (c) 2024 Yushen CHEN
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
import re
import gradio as gr
import numpy as np
try:
import spaces
USING_SPACES = True
except ImportError:
USING_SPACES = False
def gpu_decorator(func):
if USING_SPACES:
return spaces.GPU(func)
else:
return func
@gpu_decorator
def infer(ref_audio_orig, ref_text, gen_text, model, remove_silence, cross_fade_duration=0.15, speed=1):
pass
@gpu_decorator
def generate_podcast(
script, speaker1_name, ref_audio1, ref_text1, speaker2_name, ref_audio2, ref_text2, model, remove_silence
):
pass
def parse_speechtypes_text(gen_text):
# Pattern to find (Emotion)
pattern = r"\((.*?)\)"
# Split the text by the pattern
tokens = re.split(pattern, gen_text)
segments = []
current_emotion = "Regular"
for i in range(len(tokens)):
if i % 2 == 0:
# This is text
text = tokens[i].strip()
if text:
segments.append({"emotion": current_emotion, "text": text})
else:
# This is emotion
emotion = tokens[i].strip()
current_emotion = emotion
return segments
def parse_emotional_text(gen_text):
# Pattern to find (Emotion)
pattern = r"\((.*?)\)"
# Split the text by the pattern
tokens = re.split(pattern, gen_text)
segments = []
current_emotion = "Regular"
for i in range(len(tokens)):
if i % 2 == 0:
# This is text
text = tokens[i].strip()
if text:
segments.append({"emotion": current_emotion, "text": text})
else:
# This is emotion
emotion = tokens[i].strip()
current_emotion = emotion
return segments
def ui_app_emotional():
# Regular speech type (mandatory)
with gr.Row():
regular_name = gr.Textbox(value="Regular", label="Speech Type Name", interactive=False)
regular_audio = gr.Audio(label="Regular Reference Audio", type="filepath")
regular_ref_text = gr.Textbox(label="Reference Text (Regular)", lines=2)
# Additional speech types (up to 99 more)
max_speech_types = 100
speech_type_names = []
speech_type_audios = []
speech_type_ref_texts = []
speech_type_delete_btns = []
for i in range(max_speech_types - 1):
with gr.Row():
name_input = gr.Textbox(label="Speech Type Name", visible=False)
audio_input = gr.Audio(label="Reference Audio", type="filepath", visible=False)
ref_text_input = gr.Textbox(label="Reference Text", lines=2, visible=False)
delete_btn = gr.Button("Delete", variant="secondary", visible=False)
speech_type_names.append(name_input)
speech_type_audios.append(audio_input)
speech_type_ref_texts.append(ref_text_input)
speech_type_delete_btns.append(delete_btn)
# Button to add speech type
add_speech_type_btn = gr.Button("Add Speech Type")
# Keep track of current number of speech types
speech_type_count = gr.State(value=0)
# Function to add a speech type
def add_speech_type_fn(speech_type_count):
if speech_type_count < max_speech_types - 1:
speech_type_count += 1
# Prepare updates for the components
name_updates = []
audio_updates = []
ref_text_updates = []
delete_btn_updates = []
for i in range(max_speech_types - 1):
if i < speech_type_count:
name_updates.append(gr.update(visible=True))
audio_updates.append(gr.update(visible=True))
ref_text_updates.append(gr.update(visible=True))
delete_btn_updates.append(gr.update(visible=True))
else:
name_updates.append(gr.update())
audio_updates.append(gr.update())
ref_text_updates.append(gr.update())
delete_btn_updates.append(gr.update())
else:
# Optionally, show a warning
# gr.Warning("Maximum number of speech types reached.")
name_updates = [gr.update() for _ in range(max_speech_types - 1)]
audio_updates = [gr.update() for _ in range(max_speech_types - 1)]
ref_text_updates = [gr.update() for _ in range(max_speech_types - 1)]
delete_btn_updates = [gr.update() for _ in range(max_speech_types - 1)]
return [speech_type_count] + name_updates + audio_updates + ref_text_updates + delete_btn_updates
add_speech_type_btn.click(
add_speech_type_fn,
inputs=speech_type_count,
outputs=[speech_type_count]
+ speech_type_names
+ speech_type_audios
+ speech_type_ref_texts
+ speech_type_delete_btns,
)
# Function to delete a speech type
def make_delete_speech_type_fn(index):
def delete_speech_type_fn(speech_type_count):
# Prepare updates
name_updates = []
audio_updates = []
ref_text_updates = []
delete_btn_updates = []
for i in range(max_speech_types - 1):
if i == index:
name_updates.append(gr.update(visible=False, value=""))
audio_updates.append(gr.update(visible=False, value=None))
ref_text_updates.append(gr.update(visible=False, value=""))
delete_btn_updates.append(gr.update(visible=False))
else:
name_updates.append(gr.update())
audio_updates.append(gr.update())
ref_text_updates.append(gr.update())
delete_btn_updates.append(gr.update())
speech_type_count = max(0, speech_type_count - 1)
return [speech_type_count] + name_updates + audio_updates + ref_text_updates + delete_btn_updates
return delete_speech_type_fn
for i, delete_btn in enumerate(speech_type_delete_btns):
delete_fn = make_delete_speech_type_fn(i)
delete_btn.click(
delete_fn,
inputs=speech_type_count,
outputs=[speech_type_count]
+ speech_type_names
+ speech_type_audios
+ speech_type_ref_texts
+ speech_type_delete_btns,
)
# Text input for the prompt
gen_text_input_emotional = gr.Textbox(label="Text to Generate", lines=10)
# Model choice
model_choice_emotional = gr.Radio(choices=["F5-TTS", "E2-TTS"], label="Choose TTS Model", value="F5-TTS")
with gr.Accordion("Advanced Settings", open=False):
remove_silence_emotional = gr.Checkbox(
label="Remove Silences",
value=True,
)
# Generate button
generate_emotional_btn = gr.Button("Generate Emotional Speech", variant="primary")
# Output audio
audio_output_emotional = gr.Audio(label="Synthesized Audio")
@gpu_decorator
def generate_emotional_speech(
regular_audio,
regular_ref_text,
gen_text,
*args,
):
num_additional_speech_types = max_speech_types - 1
speech_type_names_list = args[:num_additional_speech_types]
speech_type_audios_list = args[num_additional_speech_types : 2 * num_additional_speech_types]
speech_type_ref_texts_list = args[2 * num_additional_speech_types : 3 * num_additional_speech_types]
model_choice = args[3 * num_additional_speech_types]
remove_silence = args[3 * num_additional_speech_types + 1]
# Collect the speech types and their audios into a dict
speech_types = {"Regular": {"audio": regular_audio, "ref_text": regular_ref_text}}
for name_input, audio_input, ref_text_input in zip(
speech_type_names_list, speech_type_audios_list, speech_type_ref_texts_list
):
if name_input and audio_input:
speech_types[name_input] = {"audio": audio_input, "ref_text": ref_text_input}
# Parse the gen_text into segments
segments = parse_speechtypes_text(gen_text)
# For each segment, generate speech
generated_audio_segments = []
current_emotion = "Regular"
for segment in segments:
emotion = segment["emotion"]
text = segment["text"]
if emotion in speech_types:
current_emotion = emotion
else:
# If emotion not available, default to Regular
current_emotion = "Regular"
ref_audio = speech_types[current_emotion]["audio"]
ref_text = speech_types[current_emotion].get("ref_text", "")
# Generate speech for this segment
audio, _ = infer(ref_audio, ref_text, text, model_choice, remove_silence, 0)
sr, audio_data = audio
generated_audio_segments.append(audio_data)
# Concatenate all audio segments
if generated_audio_segments:
final_audio_data = np.concatenate(generated_audio_segments)
return (sr, final_audio_data)
else:
gr.Warning("No audio generated.")
return None
generate_emotional_btn.click(
generate_emotional_speech,
inputs=[
regular_audio,
regular_ref_text,
gen_text_input_emotional,
]
+ speech_type_names
+ speech_type_audios
+ speech_type_ref_texts
+ [
model_choice_emotional,
remove_silence_emotional,
],
outputs=audio_output_emotional,
)
# Validation function to disable Generate button if speech types are missing
def validate_speech_types(gen_text, regular_name, *args):
num_additional_speech_types = max_speech_types - 1
speech_type_names_list = args[:num_additional_speech_types]
# Collect the speech types names
speech_types_available = set()
if regular_name:
speech_types_available.add(regular_name)
for name_input in speech_type_names_list:
if name_input:
speech_types_available.add(name_input)
# Parse the gen_text to get the speech types used
segments = parse_emotional_text(gen_text)
speech_types_in_text = set(segment["emotion"] for segment in segments)
# Check if all speech types in text are available
missing_speech_types = speech_types_in_text - speech_types_available
if missing_speech_types:
# Disable the generate button
return gr.update(interactive=False)
else:
# Enable the generate button
return gr.update(interactive=True)
gen_text_input_emotional.change(
validate_speech_types,
inputs=[gen_text_input_emotional, regular_name] + speech_type_names,
outputs=generate_emotional_btn,
)
with gr.Blocks() as demo:
with gr.Tab("Multi-Style"):
ui_app_emotional()
demo.queue().launch()
# %%
Describe the bug
After updating packages and external modules, I suddenly could no longer start the project with this error:
When I disabled the external module ( https://github.com/rsxdalv/extension_f5_tts ) the project started normally. I tested the module, and initially it produced the same error in isolation:
But after refactoring it the problem no longer happens with the module alone. So the issue only happens when I try to launch the whole gradio project with this module enabled.
Above all, the error seems misguided, perhaps related to timeouts or other issues, since my network is working fine and I have no proxies (I checked the other posts about proxies, but could not find any proxies nor VPNs active on my machine).
What surprises me is that without much change the project stopped working.
If I run it in a notebook and do not let it terminate the process, the webpage loads but is not interactive. It really seems like a time out issue for this particular UI.
Have you searched existing issues? 🔎
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I can work around it (By not using gradio/this module, there is no way to use this module successfully).