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Running the following script
```
using Flux
using GraphNeuralNetworks
n = m = d = N = 10
g = Flux.batch([rand_graph(n, m, ndata=rand(d, n)) for i in 1:N])
getgraph(g, 1)
getgraph(g |> gpu, …
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Here we will keep track of compatibility with Enzyme for taking gradients.
First think is to collect a few examples to run.
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The type `GNNGraph` from [GraphNeuralNetworks.jl](https://github.com/CarloLucibello/GraphNeuralNetworks.jl) is a `Graphs.AbstractGraphs` and implements the corresponding interface, therefore it would …
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**Interface**
- Document what `generate_blabla` does
- `generate_maximizer` does not return a differentiable layer
- in particular for `generate_maximizer` the signature (args and kwargs) of …
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Such as datasets, utils.py, etc.
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I ran into a use case for the batch function to operate on generators. I noticed that the batch function is not all that compatible with generators since it doesn't utilize the collect function for th…
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你好，我看到build_graph中定义了word_vector_map之后，并没有对他内容进行更新，这个py文件中的后续代码又用到了word_vector_map，请问是怎么回事啊？
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MWE:
```julia
using GraphNeuralNetworks, Flux, Zygote
using LinearAlgebra, Random, SparseArrays, Statistics
rng = Random.seed!(63)
x = randn(rng, Float32, 5, 10)
y = randn(10)
A = spa…
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See https://timholy.github.io/SnoopCompile.jl/stable/snoopr/
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Hello,
I am a novice at using ML techniques like this, so forgive me for the simplistic question. I have been trying to apply the parameters given in your jupyter notebooks to my system and coming …