Assume network file is in little-endian byte order

This patch fixes the byte order when reading 16- and 32-bit values from the network file on a big-endian machine.

Bytes are ordered in read_le() using unsigned arithmetic, which doesn't need tricks to determine the endianness of the machine. Unfortunately the compiler doesn't seem to be able to optimise the ordering operation, but reading in the weights is not a time-critical operation and the extra time it takes should not be noticeable.

Big endian systems are still untested with NNUE.

fixes #3007

closes https://github.com/official-stockfish/Stockfish/pull/3009

No functional change.

src/nnue/evaluate_nnue.cpp

@@ -77,7 +77,7 @@ namespace Eval::NNUE {
   bool ReadParameters(std::istream& stream, const AlignedPtr<T>& pointer) {
 
     std::uint32_t header;
-    stream.read(reinterpret_cast<char*>(&header), sizeof(header));
+    header = read_le<std::uint32_t>(stream);
     if (!stream || header != T::GetHashValue()) return false;
     return pointer->ReadParameters(stream);
   }
@@ -96,9 +96,9 @@ namespace Eval::NNUE {
     std::uint32_t* hash_value, std::string* architecture) {
 
     std::uint32_t version, size;
-    stream.read(reinterpret_cast<char*>(&version), sizeof(version));
-    stream.read(reinterpret_cast<char*>(hash_value), sizeof(*hash_value));
-    stream.read(reinterpret_cast<char*>(&size), sizeof(size));
+    version = read_le<std::uint32_t>(stream);
+    *hash_value = read_le<std::uint32_t>(stream);
+    size = read_le<std::uint32_t>(stream);
     if (!stream || version != kVersion) return false;
     architecture->resize(size);
     stream.read(&(*architecture)[0], size);

src/nnue/layers/affine_transform.h

@@ -62,11 +62,10 @@ namespace Eval::NNUE::Layers {
    // Read network parameters
     bool ReadParameters(std::istream& stream) {
       if (!previous_layer_.ReadParameters(stream)) return false;
-      stream.read(reinterpret_cast<char*>(biases_),
-                  kOutputDimensions * sizeof(BiasType));
-      stream.read(reinterpret_cast<char*>(weights_),
-                  kOutputDimensions * kPaddedInputDimensions *
-                  sizeof(WeightType));
+      for (std::size_t i = 0; i < kOutputDimensions; ++i)
+        biases_[i] = read_le<BiasType>(stream);
+      for (std::size_t i = 0; i < kOutputDimensions * kPaddedInputDimensions; ++i)
+        weights_[i] = read_le<WeightType>(stream);
       return !stream.fail();
     }
 

src/nnue/nnue_common.h

@@ -21,6 +21,9 @@
 #ifndef NNUE_COMMON_H_INCLUDED
 #define NNUE_COMMON_H_INCLUDED
 
+#include <cstring>
+#include <iostream>
+
 #if defined(USE_AVX2)
 #include <immintrin.h>
 
@@ -101,6 +104,22 @@ namespace Eval::NNUE {
     return (n + base - 1) / base * base;
   }
 
+  // Read a signed or unsigned integer from  a stream in little-endian order
+  template <typename IntType>
+  inline IntType read_le(std::istream& stream) {
+    // Read the relevant bytes from the stream in little-endian order
+    std::uint8_t u[sizeof(IntType)];
+    stream.read(reinterpret_cast<char*>(u), sizeof(IntType));
+    // Use unsigned arithmetic to convert to machine order
+    typename std::make_unsigned<IntType>::type v = 0;
+    for (std::size_t i = 0; i < sizeof(IntType); ++i)
+      v = (v << 8) | u[sizeof(IntType) - i - 1];
+    // Copy the machine-ordered bytes into a potentially signed value
+    IntType w;
+    std::memcpy(&w, &v, sizeof(IntType));
+    return w;
+  }
+
 }  // namespace Eval::NNUE
 
 #endif // #ifndef NNUE_COMMON_H_INCLUDED

src/nnue/nnue_feature_transformer.h

@@ -55,10 +55,10 @@ namespace Eval::NNUE {
 
     // Read network parameters
     bool ReadParameters(std::istream& stream) {
-      stream.read(reinterpret_cast<char*>(biases_),
-                  kHalfDimensions * sizeof(BiasType));
-      stream.read(reinterpret_cast<char*>(weights_),
-                  kHalfDimensions * kInputDimensions * sizeof(WeightType));
+      for (std::size_t i = 0; i < kHalfDimensions; ++i)
+        biases_[i] = read_le<BiasType>(stream);
+      for (std::size_t i = 0; i < kHalfDimensions * kInputDimensions; ++i)
+        weights_[i] = read_le<WeightType>(stream);
       return !stream.fail();
     }