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TensorData decoding problem with Nix package #274

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mikesperber opened this issue Jun 18, 2021 · 0 comments
Open

TensorData decoding problem with Nix package #274

mikesperber opened this issue Jun 18, 2021 · 0 comments

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@mikesperber
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I'm trying to get the Nix packaging for the Haskell bindings up to data, but the QueueTest fails. Here's some more info:

NixOS/nixpkgs#119411

In particular, copying what I just wrote into the pull request:

The offsets for decoding strings seem to be out of whack. In QueueTest, the correct FFI.TensorData records for the strings look like this:

tensorData: TensorData {tensorDataDimensions = [], tensorDataType = DT_STRING, tensorDataBytes = [0,0,0,0,0,0,0,0,2,72,105]}
tensorData: TensorData {tensorDataDimensions = [], tensorDataType = DT_STRING, tensorDataBytes = [0,0,0,0,0,0,0,0,3,66,97,114]}
tensorData: TensorData {tensorDataDimensions = [], tensorDataType = DT_STRING, tensorDataBytes = [0,0,0,0,0,0,0,0,3,66,97,122]}
tensorData: TensorData {tensorDataDimensions = [], tensorDataType = DT_STRING, tensorDataBytes = [0,0,0,0,0,0,0,0,3,66,97,122]}
tensorData: TensorData {tensorDataDimensions = [], tensorDataType = DT_STRING, tensorDataBytes = [0,0,0,0,0,0,0,0,5,65,115,121,110,99]}
tensorData: TensorData {tensorDataDimensions = [], tensorDataType = DT_STRING, tensorDataBytes = [0,0,0,0,0,0,0,0,5,65,115,121,110,99]}

The broken ones I'm seeing look like this:

tensorData: TensorData {tensorDataDimensions = [], tensorDataType = DT_STRING, tensorDataBytes = [8,72,105,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]}
dataBytes: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
tensorData: TensorData {tensorDataDimensions = [], tensorDataType = DT_STRING, tensorDataBytes = [12,66,97,122,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]}
dataBytes: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
tensorData: TensorData {tensorDataDimensions = [], tensorDataType = DT_STRING, tensorDataBytes = [20,65,115,121,110,99,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]}
dataBytes: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Feels like there's an offset of 8 going on.

Maybe somebody looking at it knows what's going on - help would be much appreciated!

@mikesperber mikesperber mentioned this issue Jul 28, 2022
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