Refactor the PrepareCoordinator and related components to improve the handling of reference specifications in the TTS system. Introduce new methods for building and extracting reference prompts and specifications, along with detailed profiling metrics for performance monitoring. Update the PrepareRefSemanticBatchWorker to include additional timing metrics and caching mechanisms for resampling. These changes enhance the efficiency and maintainability of the TTS framework, particularly in managing audio processing and reference data.
Introduce a new submodule for g2pw and implement AsyncStageGate in PrepareCoordinator to manage concurrent task inflight limits. Update PrepareTextCpuWorker and PrepareRefSemanticBatchWorker to support asynchronous task submission and completion notifications. Enhance profiling capabilities in TTS to track g2pw processing times, improving overall performance and maintainability of the TTS system.
Refactor api_v2.py and api_v3.py to update sampling parameters and weight paths for better clarity and support for v3/v4 vocoders. Introduce new methods in PrepareCoordinator for handling empty text features and improve profiling capabilities. Additionally, update unified engine components to streamline audio processing and state management, enhancing overall performance and maintainability of the TTS system.
Introduce new modules including unified_engine_component_models, unified_engine_component_policy, unified_engine_component_registry, unified_engine_component_runtime, unified_engine_worker_completion, and unified_engine_worker_decode. These additions enhance the TTS framework by providing structured models for request handling, engine policies, and worker execution, significantly improving the architecture and maintainability of the system. The new components support asynchronous operations and optimize overall performance through better state management and processing capabilities.
