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Embed default net, and simplify using non-default nets

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covers the most important cases from the user perspective:

It embeds the default net in the binary, so a download of that binary will result
in a working engine with the default net. The engine will be functional in the default mode
without any additional user action.

It allows non-default nets to be used, which will be looked for in up to
three directories (working directory, location of the binary, and optionally a specific default directory).
This mechanism is also kept for those developers that use MSVC,
the one compiler that doesn't have an easy mechanism for embedding data.

It is possible to disable embedding, and instead specify a specific directory, e.g. linux distros might want to use
CXXFLAGS="-DNNUE_EMBEDDING_OFF -DDEFAULT_NNUE_DIRECTORY=/usr/share/games/stockfish/" make -j ARCH=x86-64 profile-build

passed STC non-regression:
https://tests.stockfishchess.org/tests/view/5f4a581c150f0aef5f8ae03a
LLR: 2.95 (-2.94,2.94) {-1.25,-0.25}
Total: 66928 W: 7202 L: 7147 D: 52579
Ptnml(0-2): 291, 5309, 22211, 5360, 293

closes https://github.com/official-stockfish/Stockfish/pull/3070

fixes https://github.com/official-stockfish/Stockfish/issues/3030

No functional change.
This commit is contained in:
Stéphane Nicolet
2020-08-23 13:43:38 +02:00
committed by Joost VandeVondele
parent 242a7d9fea
commit 406979ea12
13 changed files with 582 additions and 43 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+11 -7
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@@ -12,9 +12,9 @@ about how to use Stockfish with it.
The Stockfish engine features two evaluation functions for chess, the classical
evaluation based on handcrafted terms, and the NNUE evaluation based on efficiently
updateable neural networks. The classical evaluation runs efficiently on most 64bit
CPU architectures, while the NNUE evaluation benefits strongly from the vector
intrinsics available on modern CPUs (avx2 or similar).
updateable neural networks. The classical evaluation runs efficiently on almost all
CPU architectures, while the NNUE evaluation benefits from the vector
intrinsics available on most CPUs (sse2, avx2, neon, or similar).
## Files
@@ -29,10 +29,11 @@ This distribution of Stockfish consists of the following files:
that can be used to compile Stockfish on Unix-like systems.
* a file with the .nnue extension, storing the neural network for the NNUE
evaluation.
evaluation. Binary distributions will have this file embedded.
Note: to use the NNUE evaluation, the additional data file with neural network parameters
needs to be downloaded. The filename for the default net can be found as the default
needs to be available. Normally, this file is already embedded in the binary or it can be downloaded.
The filename for the default (recommended) net can be found as the default
value of the `EvalFile` UCI option, with the format `nn-[SHA256 first 12 digits].nnue`
(for instance, `nn-c157e0a5755b.nnue`). This file can be downloaded from
```
@@ -61,11 +62,14 @@ Currently, Stockfish has the following UCI options:
* #### Use NNUE
Toggle between the NNUE and classical evaluation functions. If set to "true",
the network parameters must be available to load from file (see also EvalFile).
the network parameters must be available to load from file (see also EvalFile),
if they are not embedded in the binary.
* #### EvalFile
The name of the file of the NNUE evaluation parameters. Depending on the GUI the
filename should include the full path to the folder/directory that contains the file.
filename might have to include the full path to the folder/directory that contains the file.
Other locations, such as the directory that contains the binary and the working directory,
are also searched.
* #### UCI_AnalyseMode
An option handled by your GUI.