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v0.8 RC1
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| build/ | ||
| testdata/ | ||
| LC0VSProj/ | ||
| CUDA_NN/ |
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| @@ -0,0 +1,22 @@ | ||
|
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| <?xml version="1.0" encoding="utf-8"?> | ||
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|---|---|---|
| @@ -0,0 +1,26 @@ | ||
| # Building and running this version of lc0. | ||
|
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| Building is not very streightforward, but here's roughly the process: | ||
|
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| ## Linux | ||
|
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| 1. (if you want version with tensorflow) Install tensorflow_cc by following steps described [here](https://github.com/FloopCZ/tensorflow_cc). | ||
| 2. (if you want cuDNN version) Install CUDA and cuDNN. | ||
| 3. Install ninja and meson | ||
| 4. Go to lc0/ | ||
| 5. If you decided not to install tensorflow or CUDA, comment out building network_tf.cc and/or network_cudnn.cu from meson.build. | ||
| 6. Run ./build.sh | ||
|
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| ## Windows | ||
|
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| Building for windows is currently complicated, you can try executeing steps listed [here](https://github.com/glinscott/leela-chess/issues/334#issuecomment-382848569). | ||
|
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| Alternatively, you can use pre-built binary: | ||
|
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| 1. Install CUDA v9.0 (not 9.1) | ||
| 2. Inscall cuDNN for CUDA v9.0 | ||
| 3. Take latest binary from [here](https://crem.xyz/lc0/) | ||
|
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| That's it. | ||
|
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| For the cudnn (non-TF) version, building is much simpler. Install latest CUDA toolkit and compatible cuDNN, and build using the visual studio project. |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,8 +1,9 @@ | ||
| #!/usr/bin/bash | ||
| #!/bin/bash | ||
|
|
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| rm -fr build | ||
| CC=clang CXX=clang++ meson build --buildtype release # -Db_ndebug=true | ||
| # CC=clang CXX=clang++ meson build --buildtype debugoptimized -Db_asneeded=false | ||
| # CC=clang CXX=clang++ meson build --buildtype debug | ||
| cp testdata/* build | ||
| cd build | ||
| ninja |
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