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"""
Example usage of the ONNX NanoCodec decoder
"""
import numpy as np
import onnxruntime as ort
def example_basic_inference():
"""Basic ONNX inference example"""
print("Loading ONNX model...")
session = ort.InferenceSession(
"nano_codec_decoder.onnx",
providers=["CUDAExecutionProvider", "CPUExecutionProvider"]
)
print(f"Providers: {session.get_providers()}")
# Create sample input
num_frames = 10
tokens = np.random.randint(0, 500, (1, 4, num_frames), dtype=np.int64)
tokens_len = np.array([num_frames], dtype=np.int64)
print(f"\nInput tokens: {tokens.shape}")
# Run inference
outputs = session.run(
None,
{"tokens": tokens, "tokens_len": tokens_len}
)
audio, audio_len = outputs
print(f"Output audio: {audio.shape}")
print(f"Audio duration: {audio.shape[1] / 22050:.2f} seconds")
return audio
def example_with_decoder_class():
"""Example using the decoder class"""
from onnx_decoder_optimized import ONNXKaniTTSDecoderOptimized
print("Initializing decoder...")
decoder = ONNXKaniTTSDecoderOptimized(
onnx_model_path="nano_codec_decoder.onnx",
device="cuda"
)
# Decode multiple frames
print("\nDecoding frames...")
for i in range(5):
codes = [np.random.randint(0, 500) for _ in range(4)]
audio = decoder.decode_frame(codes)
print(f" Frame {i+1}: {audio.shape} samples")
decoder.reset_history()
print("✓ Decoding complete")
if __name__ == "__main__":
print("="*60)
print("ONNX NanoCodec Decoder Examples")
print("="*60)
# Example 1
print("\n[1/2] Basic inference...")
example_basic_inference()
# Example 2
print("\n[2/2] Using decoder class...")
example_with_decoder_class()
print("\n" + "="*60)
print("Examples complete!")
print("="*60)
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