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Running
on
Zero
# Copyright (c) Meta Platforms, Inc. and affiliates. | |
# All rights reserved. | |
# | |
# This source code is licensed under the license found in the | |
# LICENSE file in the root directory of this source tree. | |
import torch | |
from audiocraft.quantization.vq import ResidualVectorQuantizer | |
class TestResidualVectorQuantizer: | |
def test_rvq(self): | |
x = torch.randn(1, 16, 2048, requires_grad=True) | |
vq = ResidualVectorQuantizer(n_q=8, dimension=16, bins=8) | |
res = vq(x, 1.) | |
assert res.x.shape == torch.Size([1, 16, 2048]) | |
res.x.sum().backward() | |
assert torch.allclose(x.grad.data, torch.ones(1)) | |