Comments (4)
Thanks Ryan ! Now, it makes sense :)
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mlpack has been header-only since the 4.0.0 release, so there won't be any libmlpack.so
generated. 👍
from mlpack.
Then why is cmake
and make
required. There are header only libraries like enum.h which does not require such build
from mlpack.
You are right, you can just directly include the mlpack headers without using cmake
. But there are a handful of reasons why we have a build system:
- mlpack is more than just a header-only C++ library; it also has bindings to other languages that build libraries and executables
- CMake checks to ensure that all dependencies of mlpack (that's Armadillo, cereal, and optionally stb) are available on the system, which is a convenience to the user
- optionally, CMake can also download any missing dependencies
- configuring mlpack ensures that the version output is fully correct; if it is an unreleased git revision, the reported version will be the git commit hash after configuration
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Related Issues (20)
- [R] Patch release for R bindings HOT 1
- No module named 'mlpack.image_converter' during import in python at Mac. HOT 6
- Simplify Reinforcement Learning Agent Creation HOT 5
- Try upgrading your stb implementation (macOS) HOT 1
- Crashes with valid test data HOT 8
- Fatal error occurred when calling mlpack.bayesian_linear_regression() HOT 2
- Move the Wiki developer section to the new docs developer page
- stb_image_write warning while compiling HOT 1
- Benchmark to replace the transform functions HOT 16
- Can't train a model having bias addition layer Add() HOT 8
- Reverse Convolution? HOT 6
- Documentation issue
- [R] - `verbose` argument has no effect HOT 1
- Get rid of `arma::fill::zeros` when we upgrade the minimum armadillo version HOT 5
- Document `internal_compact::` name space for `arma::fill` HOT 2
- [R] - Global option for 'verbose' argument HOT 5
- Add `.prepare` script to have r-universe automatically build new nightlies HOT 1
- bfd.h:35:2: error: #error config.h must be included before this header HOT 4
- Any ideas about Random Forest regressor? HOT 2
- Switch from `-j 2` to `-j ${nproc}` HOT 3
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