Decompose forward function into initialize, predict, update #174
Annotations
10 errors, 2 warnings, and 1 notice
|
../../../.julia/packages/Documenter/C1XEF/src/utilities/utilities.jl#L44
failed to run `@example` block in src/examples/autodiff.md:88-90
```@example autodiff
logdensityof(hmm, obs_seq, control_seq; seq_ends)
```
exception =
TaskFailedException
nested task error: MethodError: no method matching zero(::Type{Any})
Closest candidates are:
zero(::Type{Union{Missing, T}}) where T
@ Base missing.jl:105
zero(!Matched::Type{Union{}}, Any...)
@ Base number.jl:310
zero(!Matched::Type{Dates.Time})
@ Dates /opt/hostedtoolcache/julia/1.10.5/x64/share/julia/stdlib/v1.10/Dates/src/types.jl:440
...
Stacktrace:
[1] zero(::Type{Any})
@ Base ./missing.jl:106
[2] _forward!(storage::HiddenMarkovModels.ForwardStorage{Float64}, hmm::Main.__atexample__named__autodiff.DiffusionHMM{Vector{Float64}, Matrix{Float64}, Vector{Float64}}, obs_seq::Vector{Float64}, control_seq::Vector{Float64}, seq_ends::Vector{Int64}, k::Int64)
@ HiddenMarkovModels ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:79
[3] macro expansion
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:161 [inlined]
[4] #90#threadsfor_fun#3
@ ./threadingconstructs.jl:215 [inlined]
[5] #90#threadsfor_fun
@ ./threadingconstructs.jl:182 [inlined]
[6] (::Base.Threads.var"#1#2"{HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{Float64}, Main.__atexample__named__autodiff.DiffusionHMM{Vector{Float64}, Matrix{Float64}, Vector{Float64}}, Vector{Float64}, Vector{Float64}, Base.OneTo{Int64}}}, Int64})()
@ Base.Threads ./threadingconstructs.jl:154
Stacktrace:
[1] threading_run(fun::HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{Float64}, Main.__atexample__named__autodiff.DiffusionHMM{Vector{Float64}, Matrix{Float64}, Vector{Float64}}, Vector{Float64}, Vector{Float64}, Base.OneTo{Int64}}}, static::Bool)
@ Base.Threads ./threadingconstructs.jl:172
[2] macro expansion
@ ./threadingconstructs.jl:220 [inlined]
[3] #forward!#2
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:160 [inlined]
[4] forward!
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:148 [inlined]
[5] #forward#6
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:181 [inlined]
[6] forward
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:174 [inlined]
[7] logdensityof(hmm::Main.__atexample__named__autodiff.DiffusionHMM{Vector{Float64}, Matrix{Float64}, Vector{Float64}}, obs_seq::Vector{Float64}, control_seq::Vector{Float64}; seq_ends::Vector{Int64})
@ HiddenMarkovModels ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/logdensity.jl:12
[8] top-level scope
@ autodiff.md:89
[9] eval
@ ./boot.jl:385 [inlined]
[10] #60
@ ~/.julia/packages/Documenter/C1XEF/src/expander_pipeline.jl:754 [inlined]
[11] cd(f::Documenter.var"#60#62"{Module, Expr}, dir::String)
@ Base.Filesystem ./file.jl:112
[12] (::Documenter.var"#59#61"{Documenter.Page, Module, Expr})()
@ Documenter ~/.julia/packages/Documenter/C1XEF/src/expander_pipeline.jl:753
[13] (::IOCapture.var"#5#9"{DataType, Documenter.var"#59#61"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}})()
@ IOCapture ~/.julia/packages/IOCapture/Y5rEA/src/IOCapture.jl:170
[14] with_logstate(f::Function, logstate::Any)
@ Base.CoreLogging ./logging.jl:515
[15] with_logger
@ ./logging.jl:627 [inlined]
[16] capture(f::Documenter.var"#59#61"{Documenter.Page, Module, Expr}; ret
|
|
../../../.julia/packages/Documenter/C1XEF/src/utilities/utilities.jl#L44
failed to run `@example` block in src/examples/autodiff.md:94-103
```@example autodiff
parameters = ComponentVector(; init, trans, means)
function f(parameters::ComponentVector, obs_seq, control_seq; seq_ends)
new_hmm = DiffusionHMM(parameters.init, parameters.trans, parameters.means)
return logdensityof(new_hmm, obs_seq, control_seq; seq_ends)
end;
f(parameters, obs_seq, control_seq; seq_ends)
```
exception =
TaskFailedException
nested task error: MethodError: no method matching zero(::Type{Any})
Closest candidates are:
zero(::Type{Union{Missing, T}}) where T
@ Base missing.jl:105
zero(!Matched::Type{Union{}}, Any...)
@ Base number.jl:310
zero(!Matched::Type{Dates.Time})
@ Dates /opt/hostedtoolcache/julia/1.10.5/x64/share/julia/stdlib/v1.10/Dates/src/types.jl:440
...
Stacktrace:
[1] zero(::Type{Any})
@ Base ./missing.jl:106
[2] _forward!(storage::HiddenMarkovModels.ForwardStorage{Float64}, hmm::Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, obs_seq::Vector{Float64}, control_seq::Vector{Float64}, seq_ends::Vector{Int64}, k::Int64)
@ HiddenMarkovModels ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:79
[3] macro expansion
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:161 [inlined]
[4] #90#threadsfor_fun#3
@ ./threadingconstructs.jl:215 [inlined]
[5] #90#threadsfor_fun
@ ./threadingconstructs.jl:182 [inlined]
[6] (::Base.Threads.var"#1#2"{HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{Float64}, Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, Vector{Float64}, Vector{Float64}, Base.OneTo{Int64}}}, Int64})()
@ Base.Threads ./threadingconstructs.jl:154
Stacktrace:
[1] threading_run(fun::HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{Float64}, Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, Vector{Float64}, Vector{Float64}, Base.OneTo{Int64}}}, static::Bool)
@ Base.Threads ./threadingconstructs.jl:172
[2] macro expansion
@ ./threadingconstructs.jl:220 [inlined]
[3] #forward!#2
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:160 [inlined]
[4] forward!
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:148 [inlined]
[5] #forward#6
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:181 [inlined]
[6] forward
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:174 [inlined]
[7] logdensityof(hmm::Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, obs_seq::Vector{Float64}, control_seq::Vector{Float64}; seq_ends::Vector{Int64})
@ HiddenMarkovModels
|
|
../../../.julia/packages/Documenter/C1XEF/src/utilities/utilities.jl#L44
failed to run `@example` block in src/examples/autodiff.md:111-115
```@example autodiff
∇parameters_forwarddiff = ForwardDiff.gradient(
_parameters -> f(_parameters, obs_seq, control_seq; seq_ends), parameters
)
```
exception =
TaskFailedException
nested task error: MethodError: no method matching zero(::Type{Any})
Closest candidates are:
zero(::Type{Union{Missing, T}}) where T
@ Base missing.jl:105
zero(!Matched::Type{Union{}}, Any...)
@ Base number.jl:310
zero(!Matched::Type{Dates.Time})
@ Dates /opt/hostedtoolcache/julia/1.10.5/x64/share/julia/stdlib/v1.10/Dates/src/types.jl:440
...
Stacktrace:
[1] zero(::Type{Any})
@ Base ./missing.jl:106
[2] _forward!(storage::HiddenMarkovModels.ForwardStorage{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}}, hmm::Main.__atexample__named__autodiff.DiffusionHMM{SubArray{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}, 2, SubArray{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}}, Tuple{UnitRange{Int64}}, true}}, obs_seq::Vector{Float64}, control_seq::Vector{Float64}, seq_ends::Vector{Int64}, k::Int64)
@ HiddenMarkovModels ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:79
[3] macro expansion
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:161 [inlined]
[4] #90#threadsfor_fun#3
@ ./threadingconstructs.jl:215 [inlined]
[5] #90#threadsfor_fun
@ ./threadingconstructs.jl:182 [inlined]
[6] (::Base.Threads.var"#1#2"{HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}}, Main.__atexample__named__autodiff.DiffusionHMM{SubArray{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}, 2, SubArray{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}, 1, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}}, Tuple{UnitRange{Int64}}, true}}, Vector{Float64}, Vector{Float64}, Base.OneTo{Int64}}}, Int64})()
@ Base.Threads ./threadingconstructs.jl:154
Stacktrace:
[1] threading_run(fun::HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#6#7", Float64}, Float64, 8}}, Main.__atexample__named__autodiff.Diffus
|
|
../../../.julia/packages/Documenter/C1XEF/src/utilities/utilities.jl#L44
failed to run `@example` block in src/examples/autodiff.md:117-121
```@example autodiff
∇obs_forwarddiff = ForwardDiff.gradient(
_obs_seq -> f(parameters, _obs_seq, control_seq; seq_ends), obs_seq
)
```
exception =
TaskFailedException
nested task error: MethodError: no method matching zero(::Type{Any})
Closest candidates are:
zero(::Type{Union{Missing, T}}) where T
@ Base missing.jl:105
zero(!Matched::Type{Union{}}, Any...)
@ Base number.jl:310
zero(!Matched::Type{Dates.Time})
@ Dates /opt/hostedtoolcache/julia/1.10.5/x64/share/julia/stdlib/v1.10/Dates/src/types.jl:440
...
Stacktrace:
[1] zero(::Type{Any})
@ Base ./missing.jl:106
[2] _forward!(storage::HiddenMarkovModels.ForwardStorage{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#8#9", Float64}, Float64, 8}}, hmm::Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, obs_seq::Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#8#9", Float64}, Float64, 8}}, control_seq::Vector{Float64}, seq_ends::Vector{Int64}, k::Int64)
@ HiddenMarkovModels ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:79
[3] macro expansion
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:161 [inlined]
[4] #90#threadsfor_fun#3
@ ./threadingconstructs.jl:215 [inlined]
[5] #90#threadsfor_fun
@ ./threadingconstructs.jl:182 [inlined]
[6] (::Base.Threads.var"#1#2"{HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#8#9", Float64}, Float64, 8}}, Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#8#9", Float64}, Float64, 8}}, Vector{Float64}, Base.OneTo{Int64}}}, Int64})()
@ Base.Threads ./threadingconstructs.jl:154
Stacktrace:
[1] threading_run(fun::HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#8#9", Float64}, Float64, 8}}, Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#8#9", Float64}, Float64, 8}}, Vector{Float64}, Base.OneTo{Int64}}}, static::Bool)
@ Base.Threads ./threadingconstructs.jl:172
[2] macro expansion
@ ./threadingconstructs.jl:220 [inlined]
[3] #forward!#2
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:160 [inlined]
[4] forward!
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:148 [inlined]
[5] #forward#6
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:181 [inlined]
[6] forward
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:174 [inlined]
[7] #logdensityof#24
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/sr
|
|
../../../.julia/packages/Documenter/C1XEF/src/utilities/utilities.jl#L44
failed to run `@example` block in src/examples/autodiff.md:123-127
```@example autodiff
∇control_forwarddiff = ForwardDiff.gradient(
_control_seq -> f(parameters, obs_seq, _control_seq; seq_ends), control_seq
)
```
exception =
TaskFailedException
nested task error: MethodError: no method matching zero(::Type{Any})
Closest candidates are:
zero(::Type{Union{Missing, T}}) where T
@ Base missing.jl:105
zero(!Matched::Type{Union{}}, Any...)
@ Base number.jl:310
zero(!Matched::Type{Dates.Time})
@ Dates /opt/hostedtoolcache/julia/1.10.5/x64/share/julia/stdlib/v1.10/Dates/src/types.jl:440
...
Stacktrace:
[1] zero(::Type{Any})
@ Base ./missing.jl:106
[2] _forward!(storage::HiddenMarkovModels.ForwardStorage{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#10#11", Float64}, Float64, 8}}, hmm::Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, obs_seq::Vector{Float64}, control_seq::Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#10#11", Float64}, Float64, 8}}, seq_ends::Vector{Int64}, k::Int64)
@ HiddenMarkovModels ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:79
[3] macro expansion
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:161 [inlined]
[4] #90#threadsfor_fun#3
@ ./threadingconstructs.jl:215 [inlined]
[5] #90#threadsfor_fun
@ ./threadingconstructs.jl:182 [inlined]
[6] (::Base.Threads.var"#1#2"{HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#10#11", Float64}, Float64, 8}}, Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, Vector{Float64}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#10#11", Float64}, Float64, 8}}, Base.OneTo{Int64}}}, Int64})()
@ Base.Threads ./threadingconstructs.jl:154
Stacktrace:
[1] threading_run(fun::HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#10#11", Float64}, Float64, 8}}, Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, Vector{Float64}, Vector{ForwardDiff.Dual{ForwardDiff.Tag{Main.__atexample__named__autodiff.var"#10#11", Float64}, Float64, 8}}, Base.OneTo{Int64}}}, static::Bool)
@ Base.Threads ./threadingconstructs.jl:172
[2] macro expansion
@ ./threadingconstructs.jl:220 [inlined]
[3] #forward!#2
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:160 [inlined]
[4] forward!
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:148 [inlined]
[5] #forward#6
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:181 [inlined]
[6] forward
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:174 [inlined]
[7] #logdensityof#24
@ ~/work/HiddenMarkovModels.jl/
|
|
../../../.julia/packages/Documenter/C1XEF/src/utilities/utilities.jl#L44
failed to run `@example` block in src/examples/autodiff.md:137-144
```@example autodiff
∇all_zygote = Zygote.gradient(
(_a, _b, _c) -> f(_a, _b, _c; seq_ends), parameters, obs_seq, control_seq
);
∇parameters_zygote, ∇obs_zygote, ∇control_zygote = ∇all_zygote;
nothing #hide
```
exception =
TaskFailedException
nested task error: UndefVarError: `Bₜ₁` not defined
Stacktrace:
[1] _forward!(storage::HiddenMarkovModels.ForwardBackwardStorage{Float64, Matrix{Float64}}, hmm::Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, obs_seq::Vector{Float64}, control_seq::Vector{Float64}, seq_ends::Vector{Int64}, k::Int64)
@ HiddenMarkovModels ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:83
[2] _forward_backward!(storage::HiddenMarkovModels.ForwardBackwardStorage{Float64, Matrix{Float64}}, hmm::Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, obs_seq::Vector{Float64}, control_seq::Vector{Float64}, seq_ends::Vector{Int64}, k::Int64; transition_marginals::Bool)
@ HiddenMarkovModels ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward_backward.jl:45
[3] macro expansion
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward_backward.jl:91 [inlined]
[4] #127#threadsfor_fun#16
@ ./threadingconstructs.jl:215 [inlined]
[5] #127#threadsfor_fun
@ ./threadingconstructs.jl:182 [inlined]
[6] (::Base.Threads.var"#1#2"{HiddenMarkovModels.var"#127#threadsfor_fun#17"{HiddenMarkovModels.var"#127#threadsfor_fun#16#18"{Vector{Int64}, Bool, HiddenMarkovModels.ForwardBackwardStorage{Float64, Matrix{Float64}}, Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, Vector{Float64}, Vector{Float64}, Base.OneTo{Int64}}}, Int64})()
@ Base.Threads ./threadingconstructs.jl:154
Stacktrace:
[1] threading_run(fun::HiddenMarkovModels.var"#127#threadsfor_fun#17"{HiddenMarkovModels.var"#127#threadsfor_fun#16#18"{Vector{Int64}, Bool, HiddenMarkovModels.ForwardBackwardStorage{Float64, Matrix{Float64}}, Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, Vector{Float64}, Vector{Float64}, Base.OneTo{Int64}}}, static::Bool)
@ Base.Threads ./threadingconstructs.jl:172
[2] macro expansion
@ ./threadingconstructs.jl:220 [inlined]
[3] #forward_backward!#15
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward_backward.jl:90 [inlined]
[4] forward_backward!
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward_backward.jl:75 [inlined]
[5] rrule(rc::Zygote.ZygoteRuleConfig{Zygote.Context{false}}, ::typeof(logdensityof), hmm::Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, obs_seq::Vector{Float64}, control_seq::Vector{Float64}; seq_ends::Vecto
|
|
../../../.julia/packages/Documenter/C1XEF/src/utilities/utilities.jl#L44
failed to run `@example` block in src/examples/autodiff.md:148-150
```@example autodiff
∇parameters_zygote ≈ ∇parameters_forwarddiff
```
exception =
UndefVarError: `∇parameters_zygote` not defined
Stacktrace:
[1] top-level scope
@ autodiff.md:149
[2] eval
@ ./boot.jl:385 [inlined]
[3] #60
@ ~/.julia/packages/Documenter/C1XEF/src/expander_pipeline.jl:754 [inlined]
[4] cd(f::Documenter.var"#60#62"{Module, Expr}, dir::String)
@ Base.Filesystem ./file.jl:112
[5] (::Documenter.var"#59#61"{Documenter.Page, Module, Expr})()
@ Documenter ~/.julia/packages/Documenter/C1XEF/src/expander_pipeline.jl:753
[6] (::IOCapture.var"#5#9"{DataType, Documenter.var"#59#61"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}})()
@ IOCapture ~/.julia/packages/IOCapture/Y5rEA/src/IOCapture.jl:170
[7] with_logstate(f::Function, logstate::Any)
@ Base.CoreLogging ./logging.jl:515
[8] with_logger
@ ./logging.jl:627 [inlined]
[9] capture(f::Documenter.var"#59#61"{Documenter.Page, Module, Expr}; rethrow::Type, color::Bool, passthrough::Bool, capture_buffer::IOBuffer, io_context::Vector{Any})
@ IOCapture ~/.julia/packages/IOCapture/Y5rEA/src/IOCapture.jl:167
[10] runner(::Type{Documenter.Expanders.ExampleBlocks}, node::MarkdownAST.Node{Nothing}, page::Documenter.Page, doc::Documenter.Document)
@ Documenter ~/.julia/packages/Documenter/C1XEF/src/expander_pipeline.jl:752
|
|
../../../.julia/packages/Documenter/C1XEF/src/utilities/utilities.jl#L44
failed to run `@example` block in src/examples/autodiff.md:152-154
```@example autodiff
∇obs_zygote ≈ ∇obs_forwarddiff
```
exception =
UndefVarError: `∇obs_zygote` not defined
Stacktrace:
[1] top-level scope
@ autodiff.md:153
[2] eval
@ ./boot.jl:385 [inlined]
[3] #60
@ ~/.julia/packages/Documenter/C1XEF/src/expander_pipeline.jl:754 [inlined]
[4] cd(f::Documenter.var"#60#62"{Module, Expr}, dir::String)
@ Base.Filesystem ./file.jl:112
[5] (::Documenter.var"#59#61"{Documenter.Page, Module, Expr})()
@ Documenter ~/.julia/packages/Documenter/C1XEF/src/expander_pipeline.jl:753
[6] (::IOCapture.var"#5#9"{DataType, Documenter.var"#59#61"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}})()
@ IOCapture ~/.julia/packages/IOCapture/Y5rEA/src/IOCapture.jl:170
[7] with_logstate(f::Function, logstate::Any)
@ Base.CoreLogging ./logging.jl:515
[8] with_logger
@ ./logging.jl:627 [inlined]
[9] capture(f::Documenter.var"#59#61"{Documenter.Page, Module, Expr}; rethrow::Type, color::Bool, passthrough::Bool, capture_buffer::IOBuffer, io_context::Vector{Any})
@ IOCapture ~/.julia/packages/IOCapture/Y5rEA/src/IOCapture.jl:167
[10] runner(::Type{Documenter.Expanders.ExampleBlocks}, node::MarkdownAST.Node{Nothing}, page::Documenter.Page, doc::Documenter.Document)
@ Documenter ~/.julia/packages/Documenter/C1XEF/src/expander_pipeline.jl:752
|
|
../../../.julia/packages/Documenter/C1XEF/src/utilities/utilities.jl#L44
failed to run `@example` block in src/examples/autodiff.md:156-158
```@example autodiff
∇control_zygote ≈ ∇control_forwarddiff
```
exception =
UndefVarError: `∇control_zygote` not defined
Stacktrace:
[1] top-level scope
@ autodiff.md:157
[2] eval
@ ./boot.jl:385 [inlined]
[3] #60
@ ~/.julia/packages/Documenter/C1XEF/src/expander_pipeline.jl:754 [inlined]
[4] cd(f::Documenter.var"#60#62"{Module, Expr}, dir::String)
@ Base.Filesystem ./file.jl:112
[5] (::Documenter.var"#59#61"{Documenter.Page, Module, Expr})()
@ Documenter ~/.julia/packages/Documenter/C1XEF/src/expander_pipeline.jl:753
[6] (::IOCapture.var"#5#9"{DataType, Documenter.var"#59#61"{Documenter.Page, Module, Expr}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}, IOContext{Base.PipeEndpoint}})()
@ IOCapture ~/.julia/packages/IOCapture/Y5rEA/src/IOCapture.jl:170
[7] with_logstate(f::Function, logstate::Any)
@ Base.CoreLogging ./logging.jl:515
[8] with_logger
@ ./logging.jl:627 [inlined]
[9] capture(f::Documenter.var"#59#61"{Documenter.Page, Module, Expr}; rethrow::Type, color::Bool, passthrough::Bool, capture_buffer::IOBuffer, io_context::Vector{Any})
@ IOCapture ~/.julia/packages/IOCapture/Y5rEA/src/IOCapture.jl:167
[10] runner(::Type{Documenter.Expanders.ExampleBlocks}, node::MarkdownAST.Node{Nothing}, page::Documenter.Page, doc::Documenter.Document)
@ Documenter ~/.julia/packages/Documenter/C1XEF/src/expander_pipeline.jl:752
|
|
../../../.julia/packages/Documenter/C1XEF/src/utilities/utilities.jl#L44
failed to run `@example` block in src/examples/autodiff.md:181-191
```@example autodiff
Enzyme.autodiff(
Enzyme.Reverse,
f_aux,
Enzyme.Active,
Enzyme.Duplicated(parameters, ∇parameters_enzyme),
Enzyme.Duplicated(obs_seq, ∇obs_enzyme),
Enzyme.Duplicated(control_seq, ∇control_enzyme),
Enzyme.Const(seq_ends),
)
```
exception =
TaskFailedException
nested task error: MethodError: no method matching zero(::Type{Any})
Closest candidates are:
zero(::Type{Union{Missing, T}}) where T
@ Base missing.jl:105
zero(!Matched::Type{Union{}}, Any...)
@ Base number.jl:310
zero(!Matched::Type{Dates.Time})
@ Dates /opt/hostedtoolcache/julia/1.10.5/x64/share/julia/stdlib/v1.10/Dates/src/types.jl:440
...
Stacktrace:
[1] _forward!
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:79
[2] macro expansion
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:161 [inlined]
[3] #90#threadsfor_fun#3
@ ./threadingconstructs.jl:215 [inlined]
[4] #90#threadsfor_fun
@ ./threadingconstructs.jl:182 [inlined]
[5] augmented_julia__90_threadsfor_fun_9043_inner_1wrap
@ ./threadingconstructs.jl:0
[6] macro expansion
@ ~/.julia/packages/Enzyme/8GSlk/src/compiler.jl:8839 [inlined]
[7] enzyme_call
@ ~/.julia/packages/Enzyme/8GSlk/src/compiler.jl:8405 [inlined]
[8] AugmentedForwardThunk
@ ~/.julia/packages/Enzyme/8GSlk/src/compiler.jl:8242 [inlined]
[9] fwd
@ ~/.julia/packages/Enzyme/8GSlk/src/rules/parallelrules.jl:139 [inlined]
[10] (::Base.Threads.var"#1#2"{Enzyme.Compiler.var"#fwd#18808"{false, false, Enzyme.Compiler.AugmentedForwardThunk{Ptr{Nothing}, EnzymeCore.Duplicated{HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{Float64}, Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, Vector{Float64}, Vector{Float64}, Base.OneTo{Int64}}}}, EnzymeCore.Const{Nothing}, Tuple{EnzymeCore.Const{Int64}}, 0x0000000000000001, true, UInt32}, EnzymeCore.Duplicated{HiddenMarkovModels.var"#90#threadsfor_fun#4"{HiddenMarkovModels.var"#90#threadsfor_fun#3#5"{Vector{Int64}, HiddenMarkovModels.ForwardStorage{Float64}, Main.__atexample__named__autodiff.DiffusionHMM{SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Base.ReshapedArray{Float64, 2, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}, Tuple{}}, SubArray{Float64, 1, Vector{Float64}, Tuple{UnitRange{Int64}}, true}}, Vector{Float64}, Vector{Float64}, Base.OneTo{Int64}}}}, Ptr{UInt32}}, Int64})()
@ Base.Threads ./threadingconstructs.jl:154
Stacktrace:
[1] threading_run
@ ./threadingconstructs.jl:172
[2] runtime_pfor_augfwd
@ ~/.julia/packages/Enzyme/8GSlk/src/rules/parallelrules.jl:149 [inlined]
[3] macro expansion
@ ./threadingconstructs.jl:220 [inlined]
[4] #forward!#2
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:160 [inlined]
[5] forward!
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:148 [inlined]
[6] #forward#6
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:181 [inlined]
[7] forward
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/forward.jl:174 [inlined]
[8] #logdensityof#24
@ ~/work/HiddenMarkovModels.jl/HiddenMarkovModels.jl/src/inference/logdensity.jl:12
[9] logdensityof
@ ~/work/HiddenMa
|
|
The following actions uses node12 which is deprecated and will be forced to run on node16: actions/checkout@v2. For more info: https://github.blog/changelog/2023-06-13-github-actions-all-actions-will-run-on-node16-instead-of-node12-by-default/
|
|
The following actions use a deprecated Node.js version and will be forced to run on node20: actions/checkout@v2, julia-actions/setup-julia@v1. For more info: https://github.blog/changelog/2024-03-07-github-actions-all-actions-will-run-on-node20-instead-of-node16-by-default/
|
|
Consider using `julia-actions/cache` to speed up runs https://github.com/julia-actions/cache. To ignore, set input `ignore-no-cache: true`
|
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