diff --git a/CMakeLists.txt b/CMakeLists.txt
index 4dc6d0beb84..148b518f2c0 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -359,14 +359,14 @@ endif ()
find_package(Ensmallen 2.10.0)
if (NOT ENSMALLEN_FOUND)
if (DOWNLOAD_ENSMALLEN)
- file(DOWNLOAD http://www.ensmallen.org/files/ensmallen-latest.tar.gz
- "${CMAKE_BINARY_DIR}/deps/ensmallen-latest.tar.gz"
+ file(DOWNLOAD http://www.ensmallen.org/files/ensmallen-2.12.1.tar.gz
+ "${CMAKE_BINARY_DIR}/deps/ensmallen-2.12.1.tar.gz"
STATUS ENS_DOWNLOAD_STATUS_LIST LOG ENS_DOWNLOAD_LOG
SHOW_PROGRESS)
list(GET ENS_DOWNLOAD_STATUS_LIST 0 ENS_DOWNLOAD_STATUS)
if (ENS_DOWNLOAD_STATUS EQUAL 0)
execute_process(COMMAND ${CMAKE_COMMAND} -E
- tar xzf "${CMAKE_BINARY_DIR}/deps/ensmallen-latest.tar.gz"
+ tar xzf "${CMAKE_BINARY_DIR}/deps/ensmallen-2.12.1.tar.gz"
WORKING_DIRECTORY "${CMAKE_BINARY_DIR}/deps/")
# Get the name of the directory.
@@ -374,7 +374,7 @@ if (NOT ENSMALLEN_FOUND)
"${CMAKE_BINARY_DIR}/deps/ensmallen-[0-9]*.[0-9]*.[0-9]*")
# list(FILTER) is not available on 3.5 or older, but try to keep
# configuring without filtering the list anyway (it might work if only
- # the file ensmallen-latest.tar.gz is present.
+ # the file ensmallen-2.12.1.tar.gz is present.
if (${CMAKE_VERSION} VERSION_GREATER_EQUAL "3.6.0")
list(FILTER ENS_DIRECTORIES EXCLUDE REGEX "ensmallen-.*\.tar\.gz")
endif ()
diff --git a/README.md b/README.md
index d8f4c5c0ec0..dd7f9d6f33e 100644
--- a/README.md
+++ b/README.md
@@ -23,7 +23,7 @@ src="https://cdn.rawgit.com/mlpack/mlpack.org/e7d36ed8/mlpack-black.svg" style="
@@ -103,7 +103,7 @@ mlpack has the following dependencies:
Armadillo >= 8.400.0
Boost (program_options, math_c99, unit_test_framework, serialization,
spirit) >= 1.58.0
- CMake >= 3.3.2
+ CMake >= 3.3.1
ensmallen >= 2.10.0
All of those should be available in your distribution's package manager. If
@@ -118,7 +118,7 @@ following Python packages are installed:
numpy
pandas >= 0.15.0
-If you would like to build the Julia bindings, make sure that Julia >= 1.3.0 is
+If you would like to build the Julia bindings, make sure that Julia >= 3.3.1 is
installed.
If the STB library headers are available, image loading support will be
@@ -138,7 +138,7 @@ on Ubuntu, you can install mlpack with the following command:
Note: Older Ubuntu versions may not have the most recent version of mlpack
available---for instance, at the time of this writing, Ubuntu 16.04 only has
-mlpack 2.0.1 available. Options include upgrading your Ubuntu version, finding
+mlpack 3.3.1 available. Options include upgrading your Ubuntu version, finding
a PPA or other non-official sources, or installing with a manual build.
There are some useful pages to consult in addition to this section:
diff --git a/doc/examples/sample-ml-app/sample-ml-app/sample-ml-app.vcxproj b/doc/examples/sample-ml-app/sample-ml-app/sample-ml-app.vcxproj
index aadce63f17a..8145e540ed9 100644
--- a/doc/examples/sample-ml-app/sample-ml-app/sample-ml-app.vcxproj
+++ b/doc/examples/sample-ml-app/sample-ml-app/sample-ml-app.vcxproj
@@ -104,16 +104,16 @@
true_DEBUG;_CONSOLE;%(PreprocessorDefinitions)false
- C:\boost\boost_1_66_0;C:\mlpack\armadillo-8.500.1\include;C:\mlpack\mlpack-3.3.0\build\include;%(AdditionalIncludeDirectories)
+ C:\boost\boost_1_66_0;C:\mlpack\armadillo-8.500.1\include;C:\mlpack\mlpack-3.3.1\build\include;%(AdditionalIncludeDirectories)Consoletrue
- C:\mlpack\mlpack-3.3.0\build\Debug\mlpack.lib;C:\boost\boost_1_66_0\lib64-msvc-14.1\libboost_serialization-vc141-mt-gd-x64-1_66.lib;C:\boost\boost_1_66_0\lib64-msvc-14.1\libboost_program_options-vc141-mt-gd-x64-1_66.lib;%(AdditionalDependencies)
+ C:\mlpack\mlpack-3.3.1\build\Debug\mlpack.lib;C:\boost\boost_1_66_0\lib64-msvc-14.1\libboost_serialization-vc141-mt-gd-x64-1_66.lib;C:\boost\boost_1_66_0\lib64-msvc-14.1\libboost_program_options-vc141-mt-gd-x64-1_66.lib;%(AdditionalDependencies)
- xcopy /y "C:\mlpack\mlpack-3.3.0\build\Debug\mlpack.dll" $(OutDir)
-xcopy /y "C:\mlpack\mlpack-3.3.0\packages\OpenBLAS.0.2.14.1\lib\native\bin\x64\*.dll" $(OutDir)
+ xcopy /y "C:\mlpack\mlpack-3.3.1\build\Debug\mlpack.dll" $(OutDir)
+xcopy /y "C:\mlpack\mlpack-3.3.1\packages\OpenBLAS.0.2.14.1\lib\native\bin\x64\*.dll" $(OutDir)
xcopy /y "$(ProjectDir)..\..\..\..\src\mlpack\tests\data\german.csv" "$(ProjectDir)data\german.csv*"
diff --git a/doc/guide/build.hpp b/doc/guide/build.hpp
index d54dd3274e0..b8c826ff39d 100644
--- a/doc/guide/build.hpp
+++ b/doc/guide/build.hpp
@@ -30,7 +30,7 @@ to build mlpack on Windows, see \ref build_windows (alternatively, you can read
is based on older versions).
You can download the latest mlpack release from here:
-mlpack-3.3.0
+mlpack-3.3.1
@section build_simple Simple Linux build instructions
@@ -38,9 +38,9 @@ Assuming all dependencies are installed in the system, you can run the commands
below directly to build and install mlpack.
@code
-$ wget https://www.mlpack.org/files/mlpack-3.3.0.tar.gz
-$ tar -xvzpf mlpack-3.3.0.tar.gz
-$ mkdir mlpack-3.3.0/build && cd mlpack-3.3.0/build
+$ wget https://www.mlpack.org/files/mlpack-3.3.1.tar.gz
+$ tar -xvzpf mlpack-3.3.1.tar.gz
+$ mkdir mlpack-3.3.1/build && cd mlpack-3.3.1/build
$ cmake ../
$ make -j4 # The -j is the number of cores you want to use for a build.
$ sudo make install
@@ -65,8 +65,8 @@ configure mlpack.
First we should unpack the mlpack source and create a build directory.
@code
-$ tar -xvzpf mlpack-3.3.0.tar.gz
-$ cd mlpack-3.3.0
+$ tar -xvzpf mlpack-3.3.1.tar.gz
+$ cd mlpack-3.3.1
$ mkdir build
@endcode
diff --git a/doc/guide/python_quickstart.hpp b/doc/guide/python_quickstart.hpp
index 4a1da9152cc..4d4b1dc2774 100644
--- a/doc/guide/python_quickstart.hpp
+++ b/doc/guide/python_quickstart.hpp
@@ -31,9 +31,9 @@ build and install mlpack. You can copy-paste the commands into your shell.
@code{.sh}
sudo apt-get install libboost-all-dev g++ cmake libarmadillo-dev python-pip wget
sudo pip install cython setuptools distutils numpy pandas
-wget https://www.mlpack.org/files/mlpack-3.3.0.tar.gz
-tar -xvzpf mlpack-3.3.0.tar.gz
-mkdir -p mlpack-3.3.0/build/ && cd mlpack-3.3.0/build/
+wget https://www.mlpack.org/files/mlpack-3.3.1.tar.gz
+tar -xvzpf mlpack-3.3.1.tar.gz
+mkdir -p mlpack-3.3.1/build/ && cd mlpack-3.3.1/build/
cmake ../ && make -j4 && sudo make install
@endcode
diff --git a/doc/guide/sample_ml_app.hpp b/doc/guide/sample_ml_app.hpp
index 1cb4877037b..5e398f201bc 100644
--- a/doc/guide/sample_ml_app.hpp
+++ b/doc/guide/sample_ml_app.hpp
@@ -29,18 +29,18 @@ mlpack and dependencies in Release Mode).
@code
- C:\boost\boost_1_71_0\lib\native\include
- C:\mlpack\armadillo-9.800.3\include
- - C:\mlpack\mlpack-3.3.0\build\include
+ - C:\mlpack\mlpack-3.3.1\build\include
@endcode
- Under Linker > Input > Additional Dependencies add:
@code
- - C:\mlpack\mlpack-3.3.0\build\Debug\mlpack.lib
+ - C:\mlpack\mlpack-3.3.1\build\Debug\mlpack.lib
- C:\boost\boost_1_71_0\lib64-msvc-14.2\libboost_serialization-vc142-mt-gd-x64-1_71.lib
- C:\boost\boost_1_71_0\lib64-msvc-14.2\libboost_program_options-vc142-mt-gd-x64-1_71.lib
@endcode
- Under Build Events > Post-Build Event > Command Line add:
@code
- - xcopy /y "C:\mlpack\mlpack-3.3.0\build\Debug\mlpack.dll" $(OutDir)
- - xcopy /y "C:\mlpack\mlpack-3.3.0\packages\OpenBLAS.0.2.14.1\lib\native\bin\x64\*.dll" $(OutDir)
+ - xcopy /y "C:\mlpack\mlpack-3.3.1\build\Debug\mlpack.dll" $(OutDir)
+ - xcopy /y "C:\mlpack\mlpack-3.3.1\packages\OpenBLAS.0.2.14.1\lib\native\bin\x64\*.dll" $(OutDir)
@endcode
@note Recent versions of Visual Studio set "Conformance Mode" enabled by default. This causes some issues with