我有这个代码(文件名是test.jl)，这是一个更复杂的代码的简化版本:
using Distributed, SharedArrays
using LinearAlgebra
using PyCall
@everywhere @pyimport scipy.optimize as so
function fun() # Coupling constants
Ntraj = 2
Ntime = 10
result = @distributed (+) for ktraj = 1 : Ntraj
println("Step_1")
# One cycle one trajectory
for jt=1:Ntime
println(jt)
fidelity = x -> x[1]*x[2]*x[3]-x[1]-x[2]-x[3]
x0 = [0 0 0]
println(fidelity(x0))
println(so.minimize(fidelity,x0))
end
end
return 0
end
我用下面的方式从笔记本中调用
using Distributed
using PyCall
@pyimport scipy.optimize as so
addprocs(2)
@everywhere include("test.jl")
@time fun()
除了警告
┌ Warning: `@pyimport foo` is deprecated in favor of `foo = pyimport("foo")`.
│ caller = _pywrap_pyimport(::PyObject) at PyCall.jl:410
└ @ PyCall ~/.julia/packages/PyCall/tqyST/src/PyCall.jl:410
┌ Warning: `@pyimport foo` is deprecated in favor of `foo = pyimport("foo")`.
│ caller = _pywrap_pyimport(::PyObject) at PyCall.jl:410
└ @ PyCall ~/.julia/packages/PyCall/tqyST/src/PyCall.jl:410
┌ Warning: `@pyimport foo` is deprecated in favor of `foo = pyimport("foo")`.
│ caller = _pywrap_pyimport(::PyObject) at PyCall.jl:410
└ @ PyCall ~/.julia/packages/PyCall/tqyST/src/PyCall.jl:410
┌ Warning: `@pyimport foo` is deprecated in favor of `foo = pyimport("foo")`.
│ caller = _pywrap_pyimport(::PyObject) at PyCall.jl:410
└ @ PyCall ~/.julia/packages/PyCall/tqyST/src/PyCall.jl:410
┌ Warning: `@pyimport foo` is deprecated in favor of `foo = pyimport("foo")`.
│ caller = _pywrap_pyimport(::PyObject) at PyCall.jl:410
└ @ PyCall ~/.julia/packages/PyCall/tqyST/src/PyCall.jl:410
┌ Warning: `@pyimport foo` is deprecated in favor of `foo = pyimport("foo")`.
│ caller = _pywrap_pyimport(::PyObject) at PyCall.jl:410
└ @ PyCall ~/.julia/packages/PyCall/tqyST/src/PyCall.jl:410
我收到这个错误
TaskFailedException:
On worker 2:
UndefVarError: __anon__ not defined
deserialize_module at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:915
handle_deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:812
deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:735
handle_deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:820
deserialize_fillarray! at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:1112
deserialize_array at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:1104
handle_deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:786
deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:735 [inlined]
deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:1010
handle_deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:878
deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:735 [inlined]
deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:947
handle_deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:878
deserialize_fillarray! at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:1112
deserialize_array at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:1104
handle_deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:786
deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:735 [inlined]
deserialize_typename at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:1177
deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Distributed/src/clusterserialize.jl:68
handle_deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:878
deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:735
deserialize_datatype at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:0
handle_deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:790
deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:735
handle_deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:795
deserialize at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Serialization/src/Serialization.jl:735 [inlined]
deserialize_msg at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Distributed/src/messages.jl:99
#invokelatest#1 at ./essentials.jl:712 [inlined]
invokelatest at ./essentials.jl:711 [inlined]
message_handler_loop at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Distributed/src/process_messages.jl:185
process_tcp_streams at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Distributed/src/process_messages.jl:142
#97 at ./task.jl:358
Stacktrace:
[1] remotecall_fetch(::Function, ::Distributed.Worker, ::Function, ::Vararg{Any,N} where N; kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Distributed/src/remotecall.jl:390
[2] remotecall_fetch(::Function, ::Distributed.Worker, ::Function, ::Vararg{Any,N} where N) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Distributed/src/remotecall.jl:382
[3] remotecall_fetch(::Function, ::Int64, ::Function, ::Vararg{Any,N} where N; kwargs::Base.Iterators.Pairs{Union{},Union{},Tuple{},NamedTuple{(),Tuple{}}}) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Distributed/src/remotecall.jl:417
[4] remotecall_fetch at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Distributed/src/remotecall.jl:417 [inlined]
[5] (::Distributed.var"#155#156"{typeof(+),var"#9#12"{Int64},UnitRange{Int64},Array{UnitRange{Int64},1},Int64,Int64})() at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Distributed/src/macros.jl:270
Stacktrace:
[1] wait at ./task.jl:267 [inlined]
[2] fetch at ./task.jl:282 [inlined]
[3] iterate at ./generator.jl:47 [inlined]
[4] collect(::Base.Generator{Array{Task,1},typeof(fetch)}) at ./array.jl:665
[5] preduce(::Function, ::Function, ::UnitRange{Int64}) at /buildworker/worker/package_linux64/build/usr/share/julia/stdlib/v1.4/Distributed/src/macros.jl:274
[6] fun at /home/candeloro/feedback_qw/Feedback_Adjacency_2Measurements_N5_5HF/test.jl:12 [inlined]
[7] macro expansion at ./util.jl:175 [inlined]
[8] top-level scope at ./In[6]:8
我真的不知道如何修复它
下面是清理后的工作代码。基本上，主要问题是@distributed宏是如何试图在集群周围移动Python模块的(它似乎不知道它是一个库)。因此，我将其打包成一个函数，该函数总是在每个给定的工作进程中本地调用(没有复制的风险)。
using Distributed, LinearAlgebra, PyCall
addprocs(2)
@everywhere using Distributed, LinearAlgebra, PyCall
@everywhere const myso = pyimport("scipy.optimize")
@everywhere getso() = myso
function fun()
Ntraj = 2
Ntime = 10
result = @distributed (+) for ktraj = 1 : Ntraj
for jt=1:Ntime
println(jt)
fidelity = x -> x[1]*x[2]*x[3]-x[1]-x[2]-x[3]
x0 = [0 0 0]
println(fidelity(x0))
println(getso().minimize(fidelity,x0))
end
1 # you need to add something or use @sync @distributed for ktraj = 1 : Ntraj
end
end
fun()