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Update quantize.py #64

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31 changes: 14 additions & 17 deletions dac/nn/quantize.py
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Original file line number Diff line number Diff line change
Expand Up @@ -137,21 +137,18 @@ def forward(self, z, n_quantizers: int = None):
when in training mode, and a random number of quantizers is used.
Returns
-------
dict
A dictionary with the following keys:

"z" : Tensor[B x D x T]
Quantized continuous representation of input
"codes" : Tensor[B x N x T]
Codebook indices for each codebook
(quantized discrete representation of input)
"latents" : Tensor[B x N*D x T]
Projected latents (continuous representation of input before quantization)
"vq/commitment_loss" : Tensor[1]
Commitment loss to train encoder to predict vectors closer to codebook
entries
"vq/codebook_loss" : Tensor[1]
Codebook loss to update the codebook
"z" : Tensor[B x D x T]
Quantized continuous representation of input
"codes" : Tensor[B x N x T]
Codebook indices for each codebook
(quantized discrete representation of input)
"latents" : Tensor[B x N*D x T]
Projected latents (continuous representation of input before quantization)
"vq/commitment_loss" : Tensor[1]
Commitment loss to train encoder to predict vectors closer to codebook
entries
"vq/codebook_loss" : Tensor[1]
Codebook loss to update the codebook
"""
z_q = 0
residual = z
Expand Down Expand Up @@ -258,5 +255,5 @@ def from_latents(self, latents: torch.Tensor):
if __name__ == "__main__":
rvq = ResidualVectorQuantize(quantizer_dropout=True)
x = torch.randn(16, 512, 80)
y = rvq(x)
print(y["latents"].shape)
z_q, codes, latents, commitment_loss, codebook_loss = rvq(x)
print(latents.shape)