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Project description
Collection of some hash functions implemented with torch/numpy/tensorflow
WORK IN PROGRESS!
Installation
pip install parahash
or clone this repo and run
pip install -U poetry
poetry install -E all
# To install to your current environment, do
# pip install .
Some dependencies are optional when installing because they are not required or you may need a custom-built version of torch/tensorflow/numpy. Make sure to install them if you need them.
MD5
import parahash
from bitarray import bitarray
device = "cpu"
# device = "cuda"
data = [b'hello', "world", bitarray('1101010101010101010101010101010101010101010101010101010101010101')]
for out in parahash.md5.md5(data, device=device):
print(parahash.md5.hexdigest(out))
Current implementation with enough batch size can get 20 million hashes per second on a single RTX3090 GPU, 16 million hashes per second on a single RTX4070TiS GPU and 750K hashes per second on a single 7950x CPU.
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