来自 pycall 的 Julia 多线程

Question

假设我有一个 jupyter 笔记本：

%%julia

using Pkg
Pkg.add("DecisionTree")
using DecisionTree

X = Vector([1.1,2.2,3.3])
Y = Vector([1.1,2.2,3.3])
X = reshape(X, size(X))

X = Float32.(X)
Y = Float32.(Y)
print(typeof(X))
print(typeof(Y))
model = DecisionTree.build_forest(Y, X')

据我所知DecisionTree.jl使用多线程，pycall不支持，导致错误：

RuntimeError: <PyCall.jlwrap (in a Julia function called from Python)
JULIA: TaskFailedException
Stacktrace:
  [1] wait
    @ .\task.jl:334 [inlined]
  [2] threading_run(func::Function)
    @ Base.Threads .\threadingconstructs.jl:38
  [3] macro expansion
    @ .\threadingconstructs.jl:97 [inlined]
  [4] build_forest(labels::Vector{Float32}, features::LinearAlgebra.Adjoint{Float32, Vector{Float32}}, n_subfeatures::Int64, n_trees::Int64, partial_sampling::Float64, max_depth::Int64,

我的问题是 - 到底有没有办法让它发挥作用？

Answer 1

问题与从 Python 调用它无关，而是因为您正在尝试制作一个模型，其中特征是具有 3 个维度的单个记录并且标签是 3 (记录）向量。 DecisionTrees 确实期望输入是标签的维度 nRecords 的列向量和特征的 nDimensions 矩阵的 nRecods。

例如：

julia> X = [1.1,2.2,3.3]
3-element Vector{Float64}:
 1.1
 2.2
 3.3

julia> Y = [1.1,2.2,3.3]
3-element Vector{Float64}:
 1.1
 2.2
 3.3

julia> X = reshape(X,3,1) # reshape to a single column **matrix**
3×1 Matrix{Float64}:
 1.1
 2.2
 3.3

julia> model = DecisionTree.build_forest(Y, X)
Ensemble of Decision Trees
Trees:      10
Avg Leaves: 1.0
Avg Depth:  0.0

此外，要制作矢量，您无需指定“矢量”。我建议你看看我的tutorial on Julia or on my course on Scientific Programming and Machine Learning with Julia（我前几天刚完成，我还需要“清理”它才能发布）

来自 pycall 的 Julia 多线程

Julia multithreading from pycall

python

multithreading

machine-learning

julia

pycall