multiprocessing problem
- Lingua principale
- Julia
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Descrizione
I tried to call PyStan using PyCall in Windows, but found repeating ``ERROR: unknown option `-c` ``.
Example:
```julia
using PyCall
pystan = pyimport("pystan")
schools_code = """
data {
vector[8] y; // estimated treatment effects
}
parameters {
real mu;
}
model {
y ~ normal(mu, 1.0);
}
"""
schools_dat = Dict("y" => [28, 8, -3, 7, -1, 1, 18, 12],)
sm = pystan.StanModel(model_code=schools_code)
fit = sm.sampling(data=schools_dat, iter=1000, chains=4)
```
Since I encountered a similar problem in pymc, I replaced `num_chains=4` with `num_chains=1` and "fixed" it. But it is still a problem considering exactly the same code works in pure Python.
I guess that the problem is due to multiprocessing (maybe only on Windows), so PyTorch `dataloader`, a well known lightweight multiprocessing caller is tested. Still, `num_workers=0` (non-multiprocessing) works but `num_workers=4` like the following example will not work.
Example:
```julia
using PyCall
torch = pyimport("torch")
torchvision = pyimport("torchvision")
transforms = pyimport("torchvision.transforms")
datasets = pyimport("torchvision.datasets")
dataset = datasets.FakeData(transform=transforms.ToTensor())
dataloader = torch.utils.data.DataLoader(dataset, batch_size=10, num_workers=4)
for batch in dataloader
println(batch)
break
end
```
Guida per i contributori
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Direzione di ricerca
Start by reproducing the PyCall examples on Windows, comparing the single-process and multiprocessing settings for PyStan and PyTorch DataLoader. The payload names no repository files or tests, so first locate the PyCall multiprocessing entry point and establish whether the `-c` error is specific to Windows; done means the shown multi-worker cases work without the error.
Scritto dal modello di indicizzazione a partire dal testo della issue.
Valutazione
- Stack tecnologico
- julia, python, pytorch
- Ambito
- backend, tooling
- Tipo di issue
- Bug
- Difficoltà
- 4/5
- Tempo stimato
- 3-5 giorni
- Stato di attività
- Ferma
- Chiarezza
- Da chiarire
- Idoneità per principianti
- 25/100