fix: fix wrong dtype - #359
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eeshsaxena
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Aug 6, 2026
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Change looks right, and it matches the same fix in #351.
There is one more spot with the identical pattern that this PR does not touch: compressai/models/vbr.py:925, inside that model's own _decompress_ar:
rv = (
torch.Tensor(rv).reshape(1, -1, 1, 1).to(scales_hat.device)
) # TODO: move rv to gpu ?
...
rv = self.gaussian_conditional.dequantize(rv, means_hat)torch.Tensor(rv) builds a float32 CPU tensor, and the .to(scales_hat.device) only fixes the device, not the dtype, so this path still hits the same mismatch you are fixing here whenever means_hat is not float32 (for example half-precision inference). The same change works there:
rv = torch.tensor(rv, dtype=means_hat.dtype, device=means_hat.device).reshape(1, -1, 1, 1)Might be worth folding into this PR so both decode paths are covered.
postprocessing should not occur in neural network interference. For quantization, it is incorrect to assume the range is [0, 1].
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