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hashing

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Christilut
Christilut commented Nov 6, 2019

Is your feature request related to a problem? Please describe.
I'm copying text one tab into another to run it with another recipe. But when I change back to the first tab, the text I originally selected is no longer selected. It would be nice if this is remembered because when working with a wall of text, it's near impossible to figure out where I was.

This applies to both to input and th

varishtsg
varishtsg commented Oct 26, 2019

I have tensorflow gpu v1.10 installed on my system. On running the setup I get this error:

Collecting tensorflow==2.0.0 (from imagededup)
Could not find a version that satisfies the requirement tensorflow==2.0.0 (from imagededup) (from versions: 0.12.1, 1.0.0, 1.0.1, 1.1.0rc0, 1.1.0rc1, 1.1.0rc2, 1.1.0, 1.2.0rc0, 1.2.0rc1, 1.2.0rc2, 1.2.0, 1.2.1, 1.3.0rc0, 1.3.0rc1, 1.3.0rc2, 1.3.0, 1.4.0rc0

odensc
odensc commented Jun 26, 2019

Hi, I was upgrading my dependencies and saw this module was updated. Since it's v0.x there could be breaking changes with updates - so I went to the Releases tab to look for a changelog, but there's none for v0.24.0.

I see now that you just removed the minimum memory limit, but would you mind adding a changelog to avoid confusion? It's a bit worrying when I don't know what's changed - espec

sirix
sean-abbott
sean-abbott commented Jun 21, 2019

The xxHash implementation doesn't produce predictable results when compared to python for strings (as in the given example.

I believe this is due to java's handling of character arrays: https://codeahoy.com/2016/05/08/the-char-type-in-java-is-broken/

We get predictable results when we dump to a byte array instead:
LongHashFunction.xx().hashBytes("test".getBytes()) gets the same output as

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