JuliaPOMDP / JuliaPOMDP/DeepQLearning.jl

Problem with reading log files

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Julia
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Description

Hi,

I'm attempting to read in the log files generated by TensorBoardLogger, but am having some issues. When I try the method for de-serialization recommended in the TensorBoardLogger docs I get an error regarding crc headers, so I'm wondering if there's a specific method that works for reading the logs generated from this package. I've included the error message below.

Alternatively, if there's a way to plot learning curves without reading in the log files that would also be helpful.

Thanks

ERROR: AssertionError: crc_header == crc_header_ck
Stacktrace:
[1] read_event(::IOStream) at /home/ben/.julia/packages/TensorBoardLogger/gv4oF/src/Deserialization/deserialization.jl:16
[2] iterate(::TensorBoardLogger.TBEventFileIterator, ::Int64) at /home/ben/.julia/packages/TensorBoardLogger/gv4oF/src/Deserialization/deserialization.jl:84
[3] iterate at /home/ben/.julia/packages/TensorBoardLogger/gv4oF/src/Deserialization/deserialization.jl:83 [inlined]
[4] iterate(::TensorBoardLogger.TBEventFileCollectionIterator, ::Int64) at /home/ben/.julia/packages/TensorBoardLogger/gv4oF/src/Deserialization/deserialization.jl:59
[5] iterate at /home/ben/.julia/packages/TensorBoardLogger/gv4oF/src/Deserialization/deserialization.jl:52 [inlined]
[6] #map_summaries#158(::Bool, ::Nothing, ::Nothing, ::Bool, ::typeof(map_summaries), ::var"#6#7", ::String) at /home/ben/.julia/packages/TensorBoardLogger/gv4oF/src/Deserialization/deserialization.jl:211
[7] map_summaries(::Function, ::String) at /home/ben/.julia/packages/TensorBoardLogger/gv4oF/src/Deserialization/deserialization.jl:205
[8] top-level scope at REPL[36]:1

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Research direction

Start with TensorBoardLogger's Deserialization/deserialization.jl, especially read_event and map_summaries, and reproduce the crc assertion against the generated log files. Compare the documented deserialization method with the reported event files; done means identifying a supported way to read these logs or documenting an alternative for plotting learning curves.

Written by the indexing model from the issue text.

Assessment

Tech stack
julia
Domain
machine-learning
Issue type
Bug
Difficulty
3/5
Estimated time
1-2 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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