Solve compatibility with Julia 0.6 (#341, #330, #293)

* Initial support for infix ~ (#173).

* seperate model wrapper call in sample.jl test

* update ForwardDiff.Dual signature

* sample.jl test passed

* fix some tests for Julia 0.6

* remove typealias for 0.6

* make some functions 0.6-ish

* make abstract 0.6-ish

* change some decpreated functions

* Update .travis.yml

* Update appveyor.yml

* Update appveyor.yml

* fix test

* Deprecations on package loading fixed

* fix deprecations

* implement callbacks for inner function

* fix model type bug

* Fix type

* update Dual in benchmark

* update Dual constructor

* Bump up required Julia version to 0.6

* Disable depreciated warning messages for `consume/produce`.

* Remove duplicate definition of produce.

* fix floor, tanh, abs, log

* fix logpdf warning and bug

* fix vec assume init

* Travis: Allow `Benchmarking` test to fail.

Author: yebai

.travis.yml

@@ -8,7 +8,7 @@ addons:
            - g++-5
 language: julia
 julia:
-  - 0.5
+  - 0.6
 os:
   - linux
   - osx
@@ -36,6 +36,7 @@ matrix:
     allow_failures:
        - env: GROUP=Test
          os: osx
+       - env: GROUP=Bench
        - env: GROUP=LDA
        - env: GROUP=MOC
        - env: GROUP=SV

REQUIRE

@@ -1,4 +1,4 @@
-julia 0.5
+julia 0.6
 
 Stan
 Distributions 0.11.0

appveyor.yml

@@ -1,11 +1,11 @@
 environment:
   matrix:
-  - JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x64/0.5/julia-0.5.0-win64.exe"
+  - JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x64/0.6/julia-0.6.0-win64.exe"
     MINGW_DIR: mingw64
     # MINGW_URL: https://sourceforge.net/projects/mingw-w64/files/Toolchains%20targetting%20Win64/Personal%20Builds/mingw-builds/5.3.0/threads-win32/seh/x86_64-5.3.0-release-win32-seh-rt_v4-rev0.7z/download
     MINGW_URL: http://mlg.eng.cam.ac.uk/hong/x86_64-5.3.0-release-win32-seh-rt_v4-rev0.7z
     MINGW_ARCHIVE: x86_64-5.3.0-release-win32-seh-rt_v4-rev0.7z
-  - JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x86/0.5/julia-0.5.0-win32.exe"
+  - JULIA_URL: "https://julialang-s3.julialang.org/bin/winnt/x86/0.6/julia-0.6.0-win32.exe"
     MINGW_DIR: mingw32
     # MINGW_URL: https://sourceforge.net/projects/mingw-w64/files/Toolchains%20targetting%20Win32/Personal%20Builds/mingw-builds/5.3.0/threads-win32/dwarf/i686-5.3.0-release-win32-dwarf-rt_v4-rev0.7z/download
     MINGW_URL: http://mlg.eng.cam.ac.uk/hong/i686-5.3.0-release-win32-dwarf-rt_v4-rev0.7z

benchmarks/optimization.jl

@@ -290,7 +290,7 @@ optRes *= "realpart(): \n"
 
 using ForwardDiff: Dual
 
-ds = [Dual{10,Float64}(rand()) for i = 1:1000]
+ds = [Dual{Void,Float64,10}(rand()) for i = 1:1000]
 
 t_map = @elapsed for i = 1:1000 map(d -> d.value, ds) end
 t_list = @elapsed for i = 1:1000 Float64[ds[i].value for i = 1:length(ds)] end
@@ -304,7 +304,7 @@ optRes *= "Constructing Dual numbers: \n"
 
 dps = zeros(44); dps[11] = 1;
 
-t_dualnumbers = @elapsed for _ = 1:(44*2000*5) ForwardDiff.Dual(1.1, dps...) end
+t_dualnumbers = @elapsed for _ = 1:(44*2000*5) ForwardDiff.Dual{Void, Float64, 44}(1.1, dps) end
 
 optRes *= "44*2000*5 times: $t_dualnumbers\n"
 

example-models/nips-2017/gmm.model.jl

@@ -28,4 +28,4 @@ p = [ 0.2,  0.2,   0.2, 0.2,  0.2]
 # μ = [   0,    1,     2, 3.5, 4.25] + 0.5 * collect(0:4)
 μ = [   0,    1,     2, 3.5, 4.25] + 2.5 * collect(0:4)
 s = [-0.5, -1.5, -0.75,  -2, -0.5]
-σ = exp(s)
+σ = exp.(s)

example-models/nips-2017/sv.model.jl

@@ -5,9 +5,9 @@
   μ ~ Cauchy(0, 10)
   h = tzeros(Real, T)
   h[1] ~ Normal(μ, σ / sqrt(1 - ϕ^2))
-  y[1] ~ Normal(0, exp(h[1] / 2))
+  y[1] ~ Normal(0, exp.(h[1] / 2))
   for t = 2:T
     h[t] ~ Normal(μ + ϕ * (h[t-1] - μ) , σ)
-    y[t] ~ Normal(0, exp(h[t] / 2))
+    y[t] ~ Normal(0, exp.(h[t] / 2))
   end
 end

example-models/nips-2017/sv.sim.jl

@@ -16,7 +16,7 @@ for t in 2:T
 end
 y = Vector{Float64}(T);
 for t in 1:T
-  y[t] = rand(Normal(0, exp(h[t] / 2)));
+  y[t] = rand(Normal(0, exp.(h[t] / 2)));
 end
 
 

example-models/nuts-paper/lr_helper.jl

@@ -7,7 +7,7 @@ readlrdata() = begin
   open("lr_nuts.data") do f
     while !eof(f)
       raw_line = readline(f)
-      data_str = filter(str -> length(str) > 0, split(raw_line, r"[ ]+")[1:end-1])
+      data_str = Iterators.filter(str -> length(str) > 0, split(raw_line, r"[ ]+")[1:end-1])
       data = map(str -> parse(str), data_str)
       x = cat(1, x, data[1:end-1]')
       y = cat(1, y, data[end] - 1)  # turn {1, 2} to {0, 1}

example-models/nuts-paper/sv_nuts.jl

@@ -14,7 +14,7 @@ y = readsvdata()
   s[1] ~ Exponential(1/100)
   for i = 2:N
     s[i] ~ Normal(log(s[i-1]), τ)
-    s[i] = exp(s[i])
+    s[i] = exp.(s[i])
     dy = log(y[i] / y[i-1]) / s[i]
     dy ~ TDist(ν)
   end

example-models/sgld-paper/lr_helper.jl

@@ -8,7 +8,7 @@ readlrdata() = begin
   open("a9a2000.data") do f
     while !eof(f)
       raw_line = readline(f)
-      data_str = filter(str -> length(str) > 0, split(raw_line, r"[ ]+")[1:end-1])
+      data_str = Iterators.filter(str -> length(str) > 0, split(raw_line, r"[ ]+")[1:end-1])
       data = map(str -> parse(str), data_str)
       x_tmp = zeros(Int32, d)
       x_tmp[data[2:end]] = 1