resolve PREfast code scanning

microsoft · Oct 26, 2024 · fa67aa2 · fa67aa2
1 parent 93be3f4
commit fa67aa2
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Showing 5 changed files with 8 additions and 8 deletions.
diff --git a/onnxruntime/contrib_ops/webgpu/bert/multihead_attention.cc b/onnxruntime/contrib_ops/webgpu/bert/multihead_attention.cc
@@ -350,7 +350,7 @@ Status ComputeVxAttentionScore(onnxruntime::webgpu::ComputeContext& context, int
                                int total_sequence_length) {
   const bool feed_past_value = present_value != nullptr && past_value != nullptr && past_value->SizeInBytes() > 0;
   const bool has_present_value = output_count > 1 && past_value != nullptr;
-  const int tile_size = 12;
+  constexpr int tile_size = 12;
 
   VxAttentionScoreProgram program{"VxAttentionScore", feed_past_value, has_present_value, tile_size};
   program.AddInputs({{probs, ProgramTensorMetadataDependency::TypeAndRank},

diff --git a/onnxruntime/contrib_ops/webgpu/quantization/matmul_nbits.cc b/onnxruntime/contrib_ops/webgpu/quantization/matmul_nbits.cc
@@ -61,7 +61,7 @@ Status MatMulNBitsProgram::GenerateShaderCode(ShaderHelper& shader) const {
     const uint32_t workgroup_size = WorkgroupSizeX() * WorkgroupSizeY();
     const uint32_t tile_size = WorkgroupSizeX() * components_b_ * 8;  // each uint32 has 8 data.
     const uint32_t a_length_per_tile = tile_size / a.NumComponents();
-    const uint32_t block_size = 32;
+    constexpr uint32_t block_size = 32;
     const uint32_t blocks_per_tile = tile_size / block_size;
     shader.AdditionalImplementation() << "var<workgroup> sub_a: array<input_a_value_t, " << a_length_per_tile << ">;\n"
                                       << "var<workgroup> inter_results: array<array<output_value_t, " << WorkgroupSizeX() << ">, " << WorkgroupSizeY() << ">;\n";
@@ -344,7 +344,7 @@ Status MatMulNBits::ComputeInternal(onnxruntime::webgpu::ComputeContext& context
   const uint32_t N = SafeInt<uint32_t>(helper.N());
   const uint32_t K = SafeInt<uint32_t>(helper.K());
   const uint32_t block_size = SafeInt<uint32_t>(block_size_);
-  const uint32_t nbits = 4;
+  constexpr uint32_t nbits = 4;
 
   const uint32_t n_blocks_per_col = (K + block_size - 1) / block_size;
   const uint32_t blob_size = (block_size / 8) * nbits;
@@ -357,12 +357,12 @@ Status MatMulNBits::ComputeInternal(onnxruntime::webgpu::ComputeContext& context
   const bool has_zero_points = zero_points != nullptr;
   // TODO: Support output_number > 1. Some cases are failed when output_number > 1.
   // const uint32_t output_number = M > 1 && (N / components) % 2 == 0 ? 2 : 1;
-  const uint32_t output_number = 1;
+  constexpr uint32_t output_number = 1;
   MatMulNBitsProgram program{output_number, SafeInt<int>(components_b), has_zero_points, use_block32};
 
   if (use_block32) {
     components = 1;
-    const uint32_t workgroup_size = 128;
+    constexpr uint32_t workgroup_size = 128;
     const uint32_t workgroup_y = N % 8 == 0 ? 8 : N % 4 == 0 ? 4
                                                              : 1;
     const uint32_t workgroup_x = workgroup_size / workgroup_y;

diff --git a/onnxruntime/core/providers/webgpu/buffer_manager.cc b/onnxruntime/core/providers/webgpu/buffer_manager.cc
@@ -7,7 +7,7 @@
 namespace onnxruntime {
 namespace webgpu {
 
-size_t NormalizeBufferSize(size_t size) {
+constexpr size_t NormalizeBufferSize(size_t size) {
   return (size + 15) / 16 * 16;
 }
 

diff --git a/onnxruntime/core/providers/webgpu/tensor/where.cc b/onnxruntime/core/providers/webgpu/tensor/where.cc
@@ -126,7 +126,7 @@ Status Where::ComputeInternal(ComputeContext& context) const {
   TensorShape output_shape;
   ORT_RETURN_IF_ERROR(ComputeOutputShape(cond_shape, x_shape, y_shape, output_shape));
   auto* output_tensor = context.Output(0, output_shape);
-  const auto component = 4;
+  constexpr int component = 4;
   uint32_t vec_size = gsl::narrow_cast<uint32_t>((output_shape.Size() + 3) / component);
   const auto is_broadcast = !(x_shape == y_shape &&
                               y_shape == cond_shape);

diff --git a/onnxruntime/core/providers/webgpu/webgpu_context.cc b/onnxruntime/core/providers/webgpu/webgpu_context.cc
@@ -346,7 +346,7 @@ Status WebGpuContext::Run(ComputeContext& context, const ProgramBase& program) {
 
   // Meet alignment of struct here: https://www.w3.org/TR/WGSL/#alignment-and-size. For simplicity, set
   // max_alignment_of_field to 16 since the underlying buffer has been rounded up to 16.
-  const size_t max_alignment_of_field = 16;
+  constexpr size_t max_alignment_of_field = 16;
   const size_t uniform_buffer_total_size = (current_offset + max_alignment_of_field - 1) / max_alignment_of_field * max_alignment_of_field;
 
   WGPUBuffer uniform_buffer = nullptr;