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Archive file format for storing large tensors efficiently

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Tensor Archive

Archive file format for storing tensors, with optional lossy compression for better storage efficiency.

Features:

  • floating-point compression (zfp)
  • storing data in lower precision format (bfloat16, ...)
  • compressing mantissa and exponents separately
  • tools for building archives from ONNX format

Quick Start

Install tsar-py package from source (require Rust build environment):

pip install git+https://github.com/brian14708/tsar.git#subdirectory=tsar-py

ONNX format

# lossless compression
tsar-pack -e 0 "<ONNX-FILE>.onnx" output.tsar
# lossy compression (with maximum error 1e-6)
tsar-pack -e 1e-6 "<ONNX-FILE>.onnx" output.tsar

# extract file to model/ directory
tsar-unpack output.tsar model/

Python API

TODO

Results

Model Compression Size
ResNet-152 none 230.6 MiB
gzip 215.4 MiB
tsar (lossless) 197.4 MiB
tsar (err=1e-6) 129.8 MiB
tsar (err=1e-5) 108.7 MiB
tsar (err=1e-4) 87.8 MiB
tsar (err=1e-3) 60.6 MiB

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