Merge branch 'DOR-993_fix_auto_batchsize_for_short_chunk_supv5' into …

…'master'

Fix for short chunks causing sup v5 auto-batchsize to crash on start up

Closes DOR-993

See merge request machine-learning/dorado!1316

dorado/basecall/CudaCaller.cpp

@@ -19,6 +19,7 @@
 #include <fstream>
 #include <limits>
 #include <map>
+#include <stdexcept>
 
 using namespace std::chrono_literals;
 
@@ -228,12 +229,17 @@ void CudaCaller::determine_batch_dims(const BasecallerCreationParams &params) {
     c10::cuda::CUDACachingAllocator::emptyCache();
     int64_t available = utils::available_memory(m_options.device());
     spdlog::debug("{} memory available: {:.2f}GB", m_device, available / GB);
-    const int scale_factor = m_config.scale_factor();
     const int granularity = get_batch_size_granularity(m_config);
+    const int cs_granularity = static_cast<int>(m_config.chunk_size_granularity());
     {
         // First set of batch dimensions. Adjust chunk size to be a multiple of stride_inner.
         // Batch size defaults to `granularity` but will be increased further down if memory allows.
-        int T_out = (requested_chunk_size / m_config.stride_inner()) * scale_factor;
+        int T_out = (requested_chunk_size / m_config.stride / cs_granularity) * cs_granularity;
+        if (T_out < 1) {
+            spdlog::error("Cannot determine batch dims for chunksize of {} - too small",
+                          requested_chunk_size);
+            throw std::runtime_error("chunksize too small");
+        }
         m_batch_dims.push_back({granularity, T_out * m_config.stride, T_out});
     }
 #ifdef DORADO_TX2
@@ -259,8 +265,9 @@ void CudaCaller::determine_batch_dims(const BasecallerCreationParams &params) {
             constexpr char SEPARATOR = ';';
             std::string env_string(env_extra_chunk_sizes);
             for (size_t start = 0, end = 0; end != std::string::npos; start = end + 1) {
-                int T_out = (std::atoi(env_string.c_str() + start) / m_config.stride_inner()) *
-                            scale_factor;
+                int T_out =
+                        (std::atoi(env_string.c_str() + start) / m_config.stride / cs_granularity) *
+                        cs_granularity;
                 if (T_out > 0) {
                     m_batch_dims.push_back({granularity, T_out * m_config.stride, T_out});
                 }
@@ -271,7 +278,14 @@ void CudaCaller::determine_batch_dims(const BasecallerCreationParams &params) {
             // TODO: determine the best set of chunk sizes
             for (float fraction : {0.5f}) {
                 // First chunk is already divided by stride
-                int T_out = int(m_batch_dims[0].T_out * fraction / scale_factor) * scale_factor;
+                int T_out = int(m_batch_dims[0].T_out * fraction / cs_granularity) * cs_granularity;
+                if (T_out < 1) {
+                    spdlog::error(
+                            "Cannot determine batch dims for partial chunksize of {}*{} - too "
+                            "small",
+                            m_batch_dims[0].T_out, fraction);
+                    throw std::runtime_error("partial chunksize too small");
+                }
                 m_batch_dims.push_back({granularity, T_out * m_config.stride, T_out});
             }
         }