Merge branch 'INSTX-3094-xcode-build' into 'master'

Get Xcode builds working See merge request machine-learning/dorado!765
nanoporetech · Dec 13, 2023 · 6c984a0 · 6c984a0
2 parents 00c00f9 + 3b68193
commit 6c984a0
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Showing 6 changed files with 30 additions and 27 deletions.
diff --git a/cmake/Htslib.cmake b/cmake/Htslib.cmake
@@ -11,17 +11,18 @@ if(NOT TARGET htslib) # lazy include guard
             "INTERFACE_INCLUDE_DIRECTORIES" ${HTSLIB_DIR})
         target_link_directories(htslib INTERFACE ${HTSLIB_DIR})
     else()
-        message(STATUS "Building htslib")
-        set(HTSLIB_DIR ${DORADO_3RD_PARTY_SOURCE}/htslib CACHE STRING
-                    "Path to htslib repo")
-        set(MAKE_COMMAND make)
-        set(AUTOCONF_COMMAND autoconf)
-        execute_process(COMMAND bash -c "autoconf -V | sed 's/.* //; q'"
-                OUTPUT_VARIABLE AUTOCONF_VERS)
-        if(AUTOCONF_VERS VERSION_GREATER_EQUAL 2.70)
+        message(STATUS "Setting up htslib build")
+        set(HTSLIB_DIR ${DORADO_3RD_PARTY_SOURCE}/htslib CACHE STRING "Path to htslib repo")
+        set(htslib_PREFIX ${CMAKE_BINARY_DIR}/3rdparty/htslib)
+
+        find_program(MAKE_COMMAND make REQUIRED)
+        find_program(AUTOCONF_COMMAND autoconf REQUIRED)
+        find_program(AUTOHEADER_COMMAND autoheader REQUIRED)
+        execute_process(COMMAND bash -c "${AUTOCONF_COMMAND} -V | sed 's/.* //; q'"
+            OUTPUT_VARIABLE AUTOCONF_VERS)
+        if (AUTOCONF_VERS VERSION_GREATER_EQUAL 2.70 AND NOT CMAKE_GENERATOR STREQUAL "Xcode")
             set(AUTOCONF_COMMAND autoreconf --install)
         endif()
-        set(htslib_PREFIX ${CMAKE_BINARY_DIR}/3rdparty/htslib)
 
         # The Htslib build apparently requires BUILD_IN_SOURCE=1, which is a problem when
         # switching between build targets because htscodecs object files aren't regenerated.
@@ -42,7 +43,7 @@ if(NOT TARGET htslib) # lazy include guard
                 PREFIX ${HTSLIB_BUILD}
                 SOURCE_DIR ${HTSLIB_BUILD}/htslib
                 BUILD_IN_SOURCE 1
-                CONFIGURE_COMMAND autoheader
+                CONFIGURE_COMMAND ${AUTOHEADER_COMMAND}
                 COMMAND ${AUTOCONF_COMMAND}
                 COMMAND ./configure --disable-bz2 --disable-lzma --disable-libcurl --disable-s3 --disable-gcs ${CONFIGURE_FLAGS}
                 BUILD_COMMAND ${MAKE_COMMAND} install prefix=${htslib_PREFIX}

diff --git a/dorado/3rdparty/ont-minimap2 b/dorado/3rdparty/ont-minimap2
diff --git a/dorado/decode/beam_search.cpp b/dorado/decode/beam_search.cpp
@@ -324,7 +324,7 @@ float beam_search(const T* const scores,
             // 8 fold unrolled version has the small upside that both loads
             // can be done with a single ldp instruction.
             const int kUnroll = 8;
-            for (int i = new_elem_count / kUnroll; i; --i) {
+            for (int i = int(new_elem_count) / kUnroll; i; --i) {
                 // True comparison sets lane bits to 0xffffffff, or -1 in two's complement,
                 // which we subtract to increment our counts.
                 float32x4_t scores_x4_a = vld1q_f32(score_ptr);

diff --git a/dorado/modbase/modbase_encoder.cpp b/dorado/modbase/modbase_encoder.cpp
@@ -129,12 +129,12 @@ int ModBaseEncoder::compute_sample_pos(int base_pos) const {
 namespace {
 
 // Fallback path for non-AVX / kmer lengths not specifically optimised.
-inline std::vector<int8_t> encode_kmer_generic(const std::vector<int>& seq,
-                                               const std::vector<int>& seq_mappings,
-                                               int bases_before,
-                                               int bases_after,
-                                               int context_samples,
-                                               int kmer_len) {
+std::vector<int8_t> encode_kmer_generic(const std::vector<int>& seq,
+                                        const std::vector<int>& seq_mappings,
+                                        int bases_before,
+                                        int bases_after,
+                                        int context_samples,
+                                        int kmer_len) {
     const size_t seq_len = seq.size() - bases_before - bases_after;
     std::vector<int8_t> output(kmer_len * utils::BaseInfo::NUM_BASES * context_samples);
 
@@ -146,7 +146,7 @@ inline std::vector<int8_t> encode_kmer_generic(const std::vector<int>& seq,
         for (int i = base_st; i < base_en; ++i) {
             for (size_t kmer_pos = 0; kmer_pos < size_t(kmer_len); ++kmer_pos) {
                 auto base = seq[seq_pos + kmer_pos];
-                uint32_t base_oh = (base == -1) ? 0ul : (1ul << (base << 3));
+                uint32_t base_oh = (base == -1) ? uint32_t{} : (uint32_t{1} << (base << 3));
                 // memcpy will be translated to a single 32 bit write.
                 std::memcpy(output_ptr, &base_oh, sizeof(base_oh));
                 output_ptr += 4;

diff --git a/dorado/nn/MetalCRFModel.cpp b/dorado/nn/MetalCRFModel.cpp
@@ -495,8 +495,10 @@ struct MetalBlockImpl : Module {
             lstm_label.back()++;
             command_buffer = m_command_queue->commandBuffer();
 
-            const int kResBufSize = dtype_bytes * kernel_simd_groups * 2 * kTileSize * kTileSize;
-            const int kOutBufSize = dtype_bytes * kernel_simd_groups * kTileSize * kTileSize;
+            const int kResBufSize =
+                    static_cast<int>(dtype_bytes * kernel_simd_groups * 2 * kTileSize * kTileSize);
+            const int kOutBufSize =
+                    static_cast<int>(dtype_bytes * kernel_simd_groups * kTileSize * kTileSize);
             const std::vector<int> tg_buffer_lens{kResBufSize, kOutBufSize};
             for (const auto &args_lstm : m_args_lstm) {
                 const std::vector<MTL::Buffer *> buffers{args_lstm.get(), mat_working_mem.get(),
@@ -650,11 +652,11 @@ class MetalCaller {
                      static_cast<size_t>(m_states) * sizeof(int16_t) +  // Posts
                      static_cast<size_t>(m_states) * sizeof(float));    // Back guides.
             spdlog::debug("decode_buffer_size_per_elem {}", decode_buffer_size_per_elem);
-            const int max_batch_size = std::clamp(
+            const int max_batch_size = static_cast<int>(std::clamp(
                     utils::pad_to(physical_memory / (2 * decode_buffer_size_per_elem),
                                   static_cast<size_t>(MTL_CORE_BATCH_SIZE)),
                     static_cast<size_t>(MTL_CORE_BATCH_SIZE),
-                    static_cast<size_t>(MTL_CORE_BATCH_SIZE * get_mtl_device_core_count()));
+                    static_cast<size_t>(MTL_CORE_BATCH_SIZE * get_mtl_device_core_count())));
             spdlog::debug("max_batch_size {}", max_batch_size);
 
             // Subject to the above memory constraint, impose a minimum batch size
@@ -671,8 +673,8 @@ class MetalCaller {
                                               static_cast<float>(kNumSmallerSizes);
             for (int i = 0; i < kNumSmallerSizes; ++i) {
                 const int test_batch_size =
-                        utils::pad_to(min_batch_size + static_cast<size_t>(i * test_size_increment),
-                                      static_cast<size_t>(MTL_CORE_BATCH_SIZE));
+                        utils::pad_to(min_batch_size + static_cast<int>(i * test_size_increment),
+                                      static_cast<int>(MTL_CORE_BATCH_SIZE));
                 test_batch_sizes.insert(test_batch_size);
             }
 
@@ -684,7 +686,7 @@ class MetalCaller {
 
             // Iterate through batch size candidates to find the most efficient one.
             int best_batch_size = -1;
-            int best_us_per_batch_element = std::numeric_limits<int>::max();
+            long long best_us_per_batch_element = std::numeric_limits<long long>::max();
             for (int batch_size : test_batch_sizes) {
                 spdlog::debug("Trying batch size {}", batch_size);
                 set_chunk_batch_size(model_config, state_dict, benchmark_chunk_size, batch_size);

diff --git a/dorado/nn/Runners.cpp b/dorado/nn/Runners.cpp
@@ -61,7 +61,7 @@ std::pair<std::vector<dorado::Runner>, size_t> create_basecall_runners(
 #if DORADO_GPU_BUILD
 #ifdef __APPLE__
     else if (device == "metal") {
-        auto caller = dorado::create_metal_caller(model_config, chunk_size, batch_size);
+        auto caller = dorado::create_metal_caller(model_config, int(chunk_size), int(batch_size));
         for (size_t i = 0; i < num_gpu_runners; i++) {
             runners.push_back(std::make_shared<dorado::MetalModelRunner>(caller));
         }