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import numpy as np | |
import onnxruntime as ort | |
import tqdm | |
n_frames = 1000 | |
n_runs = 20 | |
mel = np.random.randn(1, n_frames, 128).astype(np.float32) | |
f0 = np.random.randn(1, n_frames).astype(np.float32) + 440. | |
provider = 'DmlExecutionProvider' | |
session = ort.InferenceSession('nsf_hifigan.onnx', providers=[provider]) | |
for _ in tqdm.tqdm(range(n_runs)): | |
session.run(['waveform'], { | |
'mel': mel, | |
'f0': f0 | |
}) | |