mirror of
https://github.com/denizsafak/abogen.git
synced 2026-07-18 13:40:27 +02:00
Artem Akymenko
acb000b9e6
- Add abogen/domain/voice_loader.py with: - VoiceCache class: unified cache for loaded voices - resolve_voice(): load voice with optional caching - load_voice_cached(): compatibility wrapper for PyQt - Update abogen/pyqt/conversion.py: - Replace load_voice_cached method body with call to domain function - Maintain backward compatibility with existing interface - Add tests/test_voice_loader.py with unit tests for VoiceCache and voice loading
117 lines
3.2 KiB
Python
117 lines
3.2 KiB
Python
"""Voice loading and caching utilities.
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This module provides unified voice loading with caching support for both
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PyQt and WebUI interfaces.
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"""
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from __future__ import annotations
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from typing import Any, Dict, Optional, Tuple
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from abogen.voice_formulas import get_new_voice
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class VoiceCache:
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"""Thread-safe voice cache for loaded voice tensors."""
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def __init__(self):
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self._cache: Dict[str, Any] = {}
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def get(self, voice_spec: str) -> Optional[Any]:
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"""Get cached voice by spec."""
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return self._cache.get(voice_spec)
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def set(self, voice_spec: str, voice: Any) -> None:
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"""Cache a loaded voice."""
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self._cache[voice_spec] = voice
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def contains(self, voice_spec: str) -> bool:
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"""Check if voice is in cache."""
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return voice_spec in self._cache
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def clear(self) -> None:
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"""Clear all cached voices."""
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self._cache.clear()
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def __contains__(self, voice_spec: str) -> bool:
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return self.contains(voice_spec)
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def resolve_voice(
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voice_spec: str,
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pipeline: Any,
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use_gpu: bool,
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cache: Optional[VoiceCache] = None,
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) -> Any:
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"""Resolve voice spec to actual voice tensor or name.
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If voice_spec contains '*' (formula), loads the voice using get_new_voice.
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Otherwise, returns the voice_spec as-is (it's a voice name).
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Uses optional cache to avoid reloading same voice multiple times.
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Args:
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voice_spec: Voice specification (name or formula string with '*').
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pipeline: TTS pipeline instance for loading formula voices.
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use_gpu: Whether to use GPU for voice loading.
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cache: Optional VoiceCache instance for caching loaded voices.
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Returns:
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Loaded voice tensor (for formulas) or voice name string.
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"""
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# Check cache first
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if cache and cache.contains(voice_spec):
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return cache.get(voice_spec)
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# Load voice
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if "*" in voice_spec:
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if pipeline is None:
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return voice_spec
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loaded_voice = get_new_voice(pipeline, voice_spec, use_gpu)
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else:
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loaded_voice = voice_spec
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# Cache it
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if cache:
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cache.set(voice_spec, loaded_voice)
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return loaded_voice
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def load_voice_cached(
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voice_name: str,
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pipeline: Any,
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use_gpu: bool,
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cache: Optional[Dict[str, Any]] = None,
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) -> Any:
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"""Load voice with caching (compatibility wrapper for PyQt).
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This function maintains backward compatibility with the PyQt interface
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while using the unified voice loading logic.
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Args:
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voice_name: Voice name or formula string.
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pipeline: TTS pipeline instance.
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use_gpu: Whether to use GPU.
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cache: Optional dict to use as cache (instead of VoiceCache).
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Returns:
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Loaded voice tensor or voice name string.
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"""
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# Use dict cache if provided (for backward compatibility)
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if cache is not None:
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if voice_name in cache:
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return cache[voice_name]
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# Load voice
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if "*" in voice_name:
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loaded_voice = get_new_voice(pipeline, voice_name, use_gpu)
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else:
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loaded_voice = voice_name
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# Cache it
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if cache is not None:
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cache[voice_name] = loaded_voice
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return loaded_voice
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