wehub-resource-sync
33 lines
852 B
Python
33 lines
852 B
Python
import numpy as np
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import onnxruntime as ort
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import tqdm
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n_tokens = 10
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n_frames = 100
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n_runs = 20
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speedup = 20
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provider = 'DmlExecutionProvider'
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tokens = np.array([[1] * n_tokens], dtype=np.int64)
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durations = np.array([[n_frames // n_tokens] * n_tokens], dtype=np.int64)
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f0 = np.array([[440.] * n_frames], dtype=np.float32)
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speedup = np.array(speedup, dtype=np.int64)
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session = ort.InferenceSession('model1.onnx', providers=[provider])
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for _ in tqdm.tqdm(range(n_runs)):
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session.run(['mel'], {
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'tokens': tokens,
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'durations': durations,
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'f0': f0,
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'speedup': speedup
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})
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session = ort.InferenceSession('model2.onnx', providers=[provider])
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for _ in tqdm.tqdm(range(n_runs)):
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session.run(['mel'], {
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'tokens': tokens,
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'durations': durations,
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'f0': f0,
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'speedup': speedup
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})
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