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gridgraphs.jl's Introduction

Hi there πŸ‘‹

I am a postdoctoral researcher in machine learning at EPFL, working between the labs IdePHICS, SPOC and INDY. My current research focuses on the behavior of graph neural networks.

Between 2019 and 2022, I was a PhD student at Γ‰cole des Ponts (CERMICS), and then a teaching assistant at MIT (JuliaLab).

Check out my PhD Resources website for students and researchers πŸ”¬

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gridgraphs.jl's Issues

Add diagonal costs

Right now, moving along a diagonal costs the same as moving along rows and columns. For the MAPF benchmark instances, the cost is $\sqrt{2}$ instead of $1$. But how to generalize this to non-homogeneous grids?

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Unable to use Types such as AbstractGridGraph

Hello.
I am pretty new to Julia and attempting to replicate a tutorial for InferOpt.jl (Tutorial in question is linked here: https://axelparmentier.github.io/InferOpt.jl/dev/tutorial/).

I have already installed the appropriate packages for using Julia in a Jupyter Notebook and began testing it out, everything seems to have gone well, but then I encountered a problem: using Types from Graphs.jl and GridGraphs.jl always gives me an error:

UndefVarError: AbstractGridGraph not defined

Stacktrace:
 [1] getproperty(x::Module, f::Symbol)
   @ Base .\Base.jl:31
 [2] top-level scope
   @ In[26]:4
 [3] eval
   @ .\boot.jl:368 [inlined]
 [4] include_string(mapexpr::typeof(REPL.softscope), mod::Module, code::String, filename::String)
   @ Base .\loading.jl:1428

These are the cells I have ran, in order:

using Pkg; Pkg.add(["Flux", "Graphs", "GridGraphs", "InferOpt", "LinearAlgebra",
        "ProgressMeter", "Random", "Statistics", "Test", "UnicodePlots"])
using Flux
using Graphs
using InferOpt
using LinearAlgebra
using ProgressMeter
using Random
using Statistics
using Test
using UnicodePlots
using GridGraphs

Random.seed!(63);
h, w = 50, 100
g = AcyclicGridGraph(rand(h, w));

The error shows up after the third cell is ran. I have also attempted to run the code above in VS Code and received the same error. Nonetheless, when I run something like the following code:

nb_features = 5

true_encoder = Chain(Dense(nb_features, 1), z -> dropdims(z; dims=1));

I receive absolutely no errors.

The following seemed to work for others when asked, but doesn't seem to work for me either:

h = 12
w = 15
T = Int32
R = Float32
weights_matrix = rand(R, h, w)
g = GridGraph{T}(weights_matrix)

This is my Pkg.status():

  [587475ba] Flux v0.13.6
  [86223c79] Graphs v1.7.4
  [dd2b58c7] GridGraphs v0.8.0
  [7073ff75] IJulia v1.23.3
  [4846b161] InferOpt v0.3.1
  [92933f4c] ProgressMeter v1.7.2
  [b8865327] UnicodePlots v3.1.3
  [37e2e46d] LinearAlgebra
  [9a3f8284] Random
  [10745b16] Statistics
  [8dfed614] Test

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