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https://github.com/ml-explore/mlx-examples.git
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9bb2dd62f3
* initial encodec * works * nits * use fast group norm * fix for rnn layer * fix mlx version * use custom LSTM kernel * audio encodec * fix example, support batched inference * nits
31 lines
599 B
Python
31 lines
599 B
Python
# Copyright © 2024 Apple Inc.
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import time
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import mlx.core as mx
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from utils import load
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model, processor = load("mlx-community/encodec-48khz-float32")
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audio = mx.random.uniform(shape=(288000, 2))
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feats, mask = processor(audio)
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mx.eval(model, feats, mask)
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@mx.compile
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def fun():
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codes, scales = model.encode(feats, mask, bandwidth=3)
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reconstructed = model.decode(codes, scales, mask)
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return reconstructed
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for _ in range(5):
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mx.eval(fun())
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tic = time.time()
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for _ in range(10):
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mx.eval(fun())
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toc = time.time()
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ms = 1000 * (toc - tic) / 10
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print(f"Time per it: {ms:.3f}")
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