Allow ONNX support optimizations for CPU inference and update benchmarking scripts; modify README for clarity on performance metrics

.coveragerc

@@ -6,6 +6,7 @@ omit =
     Kokoro-82M/*
     MagicMock/*
     test_*.py
+    examples/*
 
 [report]
 exclude_lines =

CHANGELOG.md

@@ -2,6 +2,20 @@
 
 Notable changes to this project will be documented in this file.
 
+## 2025-01-04
+### Added
+- ONNX Support:
+  - Added single batch ONNX support for CPU inference
+  - Roughly 0.4 RTF (2.4x real-time speed)
+
+### Modified
+- Code Refactoring:
+  - Work on modularizing phonemizer and tokenizer into separate services
+  - Incorporated these services into a dev endpoint
+- Testing and Benchmarking:
+  - Cleaned up benchmarking scripts
+  - Cleaned up test scripts
+  - Added auto-WAV validation scripts
 
 ## 2025-01-02
 - Audio Format Support:

README.md

@@ -187,15 +187,13 @@ Key Performance Metrics:
 <summary>GPU Vs. CPU</summary>
 
 ```bash
-# GPU: Requires NVIDIA GPU with CUDA 12.1 support
+# GPU: Requires NVIDIA GPU with CUDA 12.1 support (~35x realtime speed)
 docker compose up --build
 
-# CPU: ~10x slower than GPU inference
+# CPU: ONNX optimized inference (~2.4x realtime speed)
 docker compose -f docker-compose.cpu.yml up --build
 ```
 
-*Note: CPU Inference is currently a very basic implementation, and not heavily tested*
-
 </details>
 
 <details>

docker-compose.cpu.yml

@@ -47,14 +47,14 @@ services:
       model-fetcher:
         condition: service_healthy
 
-  # # Gradio UI service [Comment out everything below if you don't need it]
-  # gradio-ui:
-  #   build:
-  #     context: ./ui
-  #   ports:
-  #     - "7860:7860"
-  #   volumes:
-  #     - ./ui/data:/app/ui/data
-  #     - ./ui/app.py:/app/app.py  # Mount app.py for hot reload
-  #   environment:
-  #     - GRADIO_WATCH=True  # Enable hot reloading
+  # Gradio UI service [Comment out everything below if you don't need it]
+  gradio-ui:
+    build:
+      context: ./ui
+    ports:
+      - "7860:7860"
+    volumes:
+      - ./ui/data:/app/ui/data
+      - ./ui/app.py:/app/app.py  # Mount app.py for hot reload
+    environment:
+      - GRADIO_WATCH=True  # Enable hot reloading

docker-compose.yml

@@ -46,14 +46,14 @@ services:
       model-fetcher:
         condition: service_healthy
 
-  # # Gradio UI service [Comment out everything below if you don't need it]
-  # gradio-ui:
-  #   build:
-  #     context: ./ui
-  #   ports:
-  #     - "7860:7860"
-  #   volumes:
-  #     - ./ui/data:/app/ui/data
-  #     - ./ui/app.py:/app/app.py  # Mount app.py for hot reload
-  #   environment:
-  #     - GRADIO_WATCH=True  # Enable hot reloading
+  # Gradio UI service [Comment out everything below if you don't need it]
+  gradio-ui:
+    build:
+      context: ./ui
+    ports:
+      - "7860:7860"
+    volumes:
+      - ./ui/data:/app/ui/data
+      - ./ui/app.py:/app/app.py  # Mount app.py for hot reload
+    environment:
+      - GRADIO_WATCH=True  # Enable hot reloading

examples/assorted_checks/benchmarks/benchmark_tts_rtf.py

@@ -60,11 +60,11 @@ def main():
     # Initialize system monitor
     monitor = SystemMonitor(interval=1.0)  # 1 second interval
     # Set prefix for output files (e.g. "gpu", "cpu", "onnx", etc.)
-    prefix = "cpu_2_1_seq"
+    prefix = "gpu"
     # Generate token sizes
     if 'gpu' in prefix:
         token_sizes = generate_token_sizes(
-            max_tokens=3000, dense_step=150, 
+            max_tokens=5000, dense_step=150, 
             dense_max=1000, sparse_step=1000)
     elif 'cpu' in prefix:
         token_sizes = generate_token_sizes(

examples/assorted_checks/benchmarks/output_data/gpu_benchmark_stats_rtf.txt

@@ -1,23 +1,23 @@
 === Benchmark Statistics (with correct RTF) ===
 
-Total tokens processed: 8150
-Total audio generated (s): 2549.70
-Total test duration (s): 70.70
-Average processing rate (tokens/s): 120.20
+Total tokens processed: 17150
+Total audio generated (s): 5296.38
+Total test duration (s): 155.23
+Average processing rate (tokens/s): 102.86
 Average RTF: 0.03
-Average Real Time Speed: 36.36
+Average Real Time Speed: 31.25
 
 === Per-chunk Stats ===
 
-Average chunk size (tokens): 1018.75
+Average chunk size (tokens): 1715.00
 Min chunk size (tokens): 150
-Max chunk size (tokens): 3000
-Average processing time (s): 8.75
-Average output length (s): 318.71
+Max chunk size (tokens): 5000
+Average processing time (s): 15.39
+Average output length (s): 529.64
 
 === Performance Ranges ===
 
-Processing rate range (tokens/s): 107.14 - 145.63
-RTF range: 0.02x - 0.03x
-Real Time Speed range: 33.33x - 50.00x
+Processing rate range (tokens/s): 80.65 - 125.10
+RTF range: 0.03x - 0.04x
+Real Time Speed range: 25.00x - 33.33x