Update app.py
Browse files
app.py
CHANGED
@@ -13,6 +13,9 @@ from matcha.text import sequence_to_text, text_to_sequence
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from matcha.utils.utils import intersperse
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import gradio as gr
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import requests
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def download_file(url, save_path):
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response = requests.get(url)
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@@ -28,6 +31,12 @@ save_generator_path = './checkpoints/generator'
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download_file(url_checkpoint, save_checkpoint_path)
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download_file(url_generator, save_generator_path)
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def load_matcha( checkpoint_path, device):
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model = MatchaTTS.load_from_checkpoint(checkpoint_path, map_location=device)
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_ = model.eval()
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@@ -49,6 +58,7 @@ def load_vocoder(checkpoint_path, device):
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def process_text(i: int, text: str, device: torch.device):
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print(f"[{i}] - Input text: {text}")
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x = torch.tensor(
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intersperse(text_to_sequence(text, ["kyrgyz_cleaners"]), 0),
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dtype=torch.long,
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from matcha.utils.utils import intersperse
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import gradio as gr
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import requests
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import json
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from datetime import datetime
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def download_file(url, save_path):
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response = requests.get(url)
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download_file(url_checkpoint, save_checkpoint_path)
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download_file(url_generator, save_generator_path)
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def log_event(input_text, log_file="usage_log.json"):
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event_data = {'timestamp': datetime.now().isoformat(),
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'text': input_text}
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with open(log_file, "a") as file:
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file.write(json.dumps(event_data) + "\n")
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def load_matcha( checkpoint_path, device):
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model = MatchaTTS.load_from_checkpoint(checkpoint_path, map_location=device)
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_ = model.eval()
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def process_text(i: int, text: str, device: torch.device):
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print(f"[{i}] - Input text: {text}")
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log_event(text)
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x = torch.tensor(
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intersperse(text_to_sequence(text, ["kyrgyz_cleaners"]), 0),
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dtype=torch.long,
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