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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
})
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