`lattice_rans` compression fails with cudaErrorInvalidValue on bfloat16 tensors, silently falls back to uncompressed storage

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Evaluación

Dificultad
4/5
Tiempo estimado
1-2 días
Aptitud para principiantes
28/100
Tipo de issue
Error
Claridad
Bastante claro
Estado de actividad
Activo
Stack tecnológico
python, pytorch
Área
backend, cloud, compilers

Línea de trabajo

The failure is the cudaErrorInvalidValue raised inside the lattice_rans encoder when given a (256, 256) bfloat16 tensor; the fallback path that stores the tensor uncompressed also needs to be located. Start by reproducing with the snippet in the issue on a CUDA device and tracing where the fallback warning is emitted. Done means either bfloat16 encoding succeeds at about 3.5 bpp, or compress() raises a clear error instead of falling back silently.

Escrito por el modelo de indexación a partir del texto del issue.

Descripción

Description

When compressing a torch.bfloat16 tensor on CUDA-compatible accelerators (T-Head SAIL ZW-M890P) using compress_method='lattice_rans' (the default), the compression fails internally with cudaErrorInvalidValue: invalid argument. Instead of raising an error, entropack silently falls back to storing the tensor uncompressed at ~16 bpp, despite requesting target_bpp=3.5.

This makes it appear as if compression succeeded (the API returns normally), but the output is actually uncompressed data with a misleading actual_bpp value.

Reproduction
import entropack as ep
import torch

tensor = (torch.randn(256, 256, device="cuda") * 0.02).to(torch.bfloat16)
config = ep.EntroPackLossyConfig(target_bpp=3.5)

compressed = ep.compress(tensor, config)
restored = ep.decompress(compressed, config)

print(f"Target: {config.target_bpp:.2f} bits per parameter")
print(f"Stored: {compressed.actual_bpp:.2f} bits per parameter")
print(restored.shape, restored.dtype)
Actual Output
lattice_rans could not encode a (256, 256) torch.bfloat16 tensor, storing it uncompressed: cudaErrorInvalidValue: invalid argument

CompressionFallbackWarning: entropack stored a (256, 256) torch.bfloat16 tensor uncompressed, at 16 bits per parameter: compress_method='lattice_rans' failed with CUDARuntimeError: cudaErrorInvalidValue: invalid argument

Target: 3.50 bits per parameter
Stored: 16.04 bits per parameter
torch.Size([256, 256]) torch.bfloat16
Expected Behavior

Either:

  1. The lattice_rans method should correctly handle bfloat16 tensors of shape (256, 256), achieving the target bitrate (~3.5 bpp).
  2. Or, if bfloat16 is not supported by lattice_rans, the library should raise a clear error at compress() time rather than silently falling back to uncompressed storage.

A silent fallback to 16 bpp (uncompressed) when the user explicitly requested 3.5 bpp is misleading — the CompressionFallbackWarning is easy to miss, and the returned actual_bpp of 16.04 vs the target of 3.5 represents a 4.6x difference in storage.

Environment
  • entropack version: 0.1.5
  • Python version: 3.12
  • PyTorch version: 2.11.0+v0.1.0.ppu2.1.0.oe
  • CUDA version: 13.0.0
  • GPU: ZW-M890P
  • OS: Ubuntu 24.04
Additional Context
  • The input tensor values are small (* 0.02), which should be favorable for compression — this rules out the possibility that the data is simply incompressible.
  • The assert torch.allclose(tensor, restored, atol=1e-3) passes trivially because the data was stored uncompressed.
Lenguaje dominante
Python
Estrellas
26
Forks
1
Merge medio
9 min
PR fusionados (30 d)
8

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