Small fixes and compiler wrangling

Chowdhury-DSP · Nov 25, 2023 · b9b0df5 · b9b0df5
1 parent 3e203a2
commit b9b0df5
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Showing 7 changed files with 17 additions and 12 deletions.
diff --git a/modules/JUCE b/modules/JUCE
diff --git a/modules/cmake/WarningFlags.cmake b/modules/cmake/WarningFlags.cmake
@@ -40,6 +40,9 @@ if(WIN32)
             -Wno-cast-function-type
             -Wno-range-loop-bind-reference
             -Wno-sign-conversion
+            -Wno-implicit-int-float-conversion
+            -Wno-implicit-const-int-float-conversion
+            -Wno-header-hygiene
         )
     elseif((CMAKE_CXX_COMPILER_ID STREQUAL "MSVC") OR (CMAKE_CXX_SIMULATE_ID STREQUAL "MSVC"))
         message(STATUS "Setting MSVC compiler flags")

diff --git a/src/CMakeLists.txt b/src/CMakeLists.txt
@@ -167,11 +167,11 @@ if (NOT(${JAI_COMPILER} STREQUAL "JAI_COMPILER-NOTFOUND"))
 endif()
 
 # AVX/SSE files for accelerated neural nets
-make_lib_simd_runtime(rnn_accelerated processors/drive/neural_utils/RNNAccelerated.cpp)
 if(IS_DIRECTORY "${CMAKE_CURRENT_SOURCE_DIR}/../modules/math_approx")
     message(STATUS "Using RTNeural with math_approx")
     add_subdirectory("${CMAKE_CURRENT_SOURCE_DIR}/../modules/math_approx" math_approx)
 endif()
+make_lib_simd_runtime(rnn_accelerated processors/drive/neural_utils/RNNAccelerated.cpp)
 foreach(target IN ITEMS rnn_accelerated_sse_or_arm rnn_accelerated_avx)
     target_link_libraries(${target} PRIVATE config_flags juce::juce_recommended_lto_flags warning_flags)
     target_include_directories(${target}

diff --git a/src/jai/SharedJaiContext.h b/src/jai/SharedJaiContext.h
@@ -11,7 +11,7 @@ struct JaiContextWrapper
     JaiContextWrapper();
     ~JaiContextWrapper();
 
-    operator jai::Context*() { return internal; }; // NOLINT
+    operator jai::Context*() { return internal; } // NOLINT
 
 private:
     jai::Context* internal = nullptr;

diff --git a/src/pch.h b/src/pch.h
@@ -22,7 +22,11 @@ JUCE_BEGIN_IGNORE_WARNINGS_GCC_LIKE ("-Wzero-as-null-pointer-constant",
 #include <RTNeural/RTNeural.h>
 JUCE_END_IGNORE_WARNINGS_GCC_LIKE
 
+JUCE_BEGIN_IGNORE_WARNINGS_GCC_LIKE ("-Wshadow-field-in-constructor")
 #include <chowdsp_wdf/chowdsp_wdf.h>
+JUCE_END_IGNORE_WARNINGS_GCC_LIKE
+
+
 #include <ea_variant/ea_variant.h>
 #include <sst/cpputils.h>
 

diff --git a/src/processors/drive/neural_utils/RNNAccelerated.cpp b/src/processors/drive/neural_utils/RNNAccelerated.cpp
@@ -26,6 +26,9 @@ struct ApproxMathsProvider
         return math_approx::sigmoid<9> (x);
     }
 };
+using RNNMathsProvider = ApproxMathsProvider;
+#else
+using RNNMathsProvider = RTNEURAL_NAMESPACE::DefaultMathsProvider;
 #endif
 
 #include "model_loaders.h"
@@ -34,7 +37,7 @@ struct ApproxMathsProvider
 #pragma GCC diagnostic pop
 #endif
 
-#if __AVX__ // Intel/AVX
+#if (__MMX__ || __SSE__ || __amd64__) && BYOD_COMPILING_WITH_AVX // INTEL + AVX
 namespace rnn_avx
 #else
 namespace rnn_sse_arm
@@ -47,13 +50,8 @@ template <int inputSize, int hiddenSize, int RecurrentLayerType, int SRCMode>
 struct RNNAccelerated<inputSize, hiddenSize, RecurrentLayerType, SRCMode>::Internal
 {
     using RecurrentLayerTypeComplete = std::conditional_t<RecurrentLayerType == RecurrentLayerType::LSTMLayer,
-#if RTNEURAL_USE_MATH_APPROX
-                                                          RTNEURAL_NAMESPACE::LSTMLayerT<float, inputSize, hiddenSize, (RTNEURAL_NAMESPACE::SampleRateCorrectionMode) SRCMode, ApproxMathsProvider>,
-                                                          RTNEURAL_NAMESPACE::GRULayerT<float, inputSize, hiddenSize, (RTNEURAL_NAMESPACE::SampleRateCorrectionMode) SRCMode, ApproxMathsProvider>>;
-#else
-                                                          RTNEURAL_NAMESPACE::LSTMLayerT<float, inputSize, hiddenSize, (RTNEURAL_NAMESPACE::SampleRateCorrectionMode) SRCMode>,
-                                                          RTNEURAL_NAMESPACE::GRULayerT<float, inputSize, hiddenSize, (RTNEURAL_NAMESPACE::SampleRateCorrectionMode) SRCMode>>;
-#endif
+                                                          RTNEURAL_NAMESPACE::LSTMLayerT<float, inputSize, hiddenSize, (RTNEURAL_NAMESPACE::SampleRateCorrectionMode) SRCMode, RNNMathsProvider>,
+                                                          RTNEURAL_NAMESPACE::GRULayerT<float, inputSize, hiddenSize, (RTNEURAL_NAMESPACE::SampleRateCorrectionMode) SRCMode, RNNMathsProvider>>;
     using DenseLayerType = RTNEURAL_NAMESPACE::DenseT<float, hiddenSize, 1>;
     RTNEURAL_NAMESPACE::ModelT<float, inputSize, 1, RecurrentLayerTypeComplete, DenseLayerType> model;
 };

diff --git a/src/processors/drive/neural_utils/RNNAccelerated.h b/src/processors/drive/neural_utils/RNNAccelerated.h
@@ -42,7 +42,7 @@ class RNNAccelerated
 };
 } // namespace rnn_sse_arm
 
-#if __AVX__ // Intel/AVX
+#if __MMX__ || __SSE__ || __amd64__ // INTEL
 namespace rnn_avx
 {
 template <int inputSize, int hiddenSize, int RecurrentLayerType, int SRCMode>