Updated version number + changelog

CHANGELOG.md

@@ -1,13 +1,22 @@
 # Releases
 
+## 0.3.0
+
+* added batch version of the forward-backward algorithm
+* added GPU support for the forward-backward algorithm
+* remove pruning option for the forward-backward algorithm
+
 ## 0.2.0
-
-* refactoring of the FSM API.  
-* added a `compile` function to convert an inference graph into a compact matrix-based format suitable for fast inference 
-* added support for dense/sparse CPU/GPU version of the forward-backward algorithm
-  * the forward-backward implementation does not rely on the graph representation anymore 
-* added unit tests 
-* added `LogSemifield` type used by the graph and inference API 
+
+* refactoring of the FSM API.
+* added a `compile` function to convert an inference graph into a
+  compact matrix-based format suitable for fast inference
+* added support for dense/sparse CPU/GPU version of the
+  forward-backward algorithm
+  * the forward-backward implementation does not rely on the graph
+    representation anymore
+* added unit tests
+* added `LogSemifield` type used by the graph and inference API
 
 ## 0.1.0
 

Project.toml

@@ -1,17 +1,13 @@
 name = "MarkovModels"
 uuid = "c2ae6250-d0a1-11ea-0991-234599ce5244"
 authors = ["Lucas Ondel <lucas.ondel@gmail.com>"]
-version = "0.2.0"
+version = "0.3.0"
 
 [deps]
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-LogExpFunctions = "2ab3a3ac-af41-5b50-aa03-7779005ae688"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
-StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 
 [compat]
 CUDA = "3.3"
-LogExpFunctions = "0.2"
-StatsBase = "0.33"
 julia = "1.6"

src/MarkovModels.jl

@@ -2,28 +2,54 @@
 
 module MarkovModels
 
-using CUDA, CUDA.CUSPARSE, LinearAlgebra, SparseArrays
-using StatsBase: sample, Weights
+using CUDA
+using CUDA.CUSPARSE
+using LinearAlgebra
+using SparseArrays
 
-export FSM, LogSemifield
-export αrecursion, βrecursion, αβrecursion
-export addstate!, compile, determinize, gpu, link!, minimize,
-    renormalize!, setinit!, setfinal!, states, transpose
+#======================================================================
+Redefinition of some linear operations to work on GPU.
+======================================================================#
 
-# Redefinition of  some linear operation to work on GPU.
 include("linalg.jl")
 include("culinalg.jl")
 
-# Semifield algebras.
+#======================================================================
+Semifield algebras.
+======================================================================#
+
 include("semifields.jl")
 
-# API to build and manipulate FSM.
+export LogSemifield
+
+#======================================================================
+API to build and manipulate FSM.
+======================================================================#
+
 include("fsm.jl")
 
-# FSM compilation to have inference efficient FSM format.
+export FSM
+export addstate!
+export determinize
+export link!
+export minimize
+export renormalize!
+export setinit!
+export setfinal!
+export states
+
 include("cfsm.jl")
 
-# Inference algorithms
+export CompiledFSM
+export compile
+export gpu
+
+#======================================================================
+Inference algorithms.
+======================================================================#
+
 include("algorithms.jl")
 
+export αβrecursion
+
 end

src/semifields.jl

@@ -1,8 +1,6 @@
 # SPDX-License-Identifier: MIT
 
-const kMinLogDiffFloat = log(1.19209290f-7)
-
-function mylogaddexp(x::T, y::T) where T
+function logaddexp(x::T, y::T) where T
     if x == T(-Inf) return y end
     if y == T(-Inf) return x end
 
@@ -32,7 +30,7 @@ Base.show(io::IO, x::LogSemifield) = print(io, x.val)
 Base.promote(x::LogSemifield{T}, y::Real) where T = x, LogSemifield{T}(y)
 Base.promote(y::Real, x::LogSemifield{T}) where T = LogSemifield{T}(y), x
 Base.:+(x::LogSemifield{T}, y::LogSemifield{T}) where T =
-    LogSemifield{T}(mylogaddexp(x.val, y.val))
+    LogSemifield{T}(logaddexp(x.val, y.val))
 Base.:*(x::LogSemifield, y::LogSemifield) = LogSemifield(x.val + y.val)
 Base.:/(x::LogSemifield, y::LogSemifield) = LogSemifield(x.val - y.val)
 Base.zero(::Type{LogSemifield{T}}) where T = LogSemifield{T}(T(-Inf))