[CPU] Fix compilation errors because of unused variables (microsoft#26147)

This PR fixes few unused variables

Author: apsonawane

onnxruntime/contrib_ops/cpu/moe/moe_cpu.cc

@@ -12,6 +12,7 @@
 #include "core/framework/float16.h"
 #include "core/framework/allocator.h"
 #include "core/platform/threadpool.h"
+#include "core/common/narrow.h"
 
 #include <algorithm>
 #include <vector>
@@ -120,7 +121,7 @@ Status MoE<T>::ComputeMoE(const OpKernelContext* context,
   int num_routing_threads = 1;
   if (tp != nullptr && num_tokens >= 1024) {
     int max_threads = concurrency::ThreadPool::DegreeOfParallelism(tp);
-    num_routing_threads = std::min(static_cast<int>(num_tokens / 512), max_threads);
+    num_routing_threads = std::min(narrow<int>(num_tokens / 512), max_threads);
     num_routing_threads = std::max(1, num_routing_threads);
   }
 
@@ -133,7 +134,7 @@ Status MoE<T>::ComputeMoE(const OpKernelContext* context,
   }
 
   concurrency::ThreadPool::TrySimpleParallelFor(tp, num_routing_threads, [&](std::ptrdiff_t thread_id) {
-    auto work = concurrency::ThreadPool::PartitionWork(static_cast<int>(thread_id), num_routing_threads, static_cast<std::ptrdiff_t>(num_tokens));
+    auto work = concurrency::ThreadPool::PartitionWork(narrow<int>(thread_id), num_routing_threads, static_cast<std::ptrdiff_t>(num_tokens));
     auto& local_expert_token_map = thread_local_expert_token_maps[thread_id];
 
     std::vector<std::pair<float, int64_t>> sorted_logits(static_cast<size_t>(num_experts));
@@ -173,7 +174,7 @@ Status MoE<T>::ComputeMoE(const OpKernelContext* context,
           int64_t route_idx = i * k_ + j;
           float normalized_weight = sorted_logits[static_cast<size_t>(j)].first * inv_top_k_sum;
 
-          route_expert[route_idx] = static_cast<int>(expert_idx);
+          route_expert[route_idx] = narrow<int>(expert_idx);
           route_scale[route_idx] = normalized_weight;
           if (normalized_weight > 0.0f) {
             local_expert_token_map[static_cast<size_t>(expert_idx)].push_back(route_idx);
@@ -185,7 +186,7 @@ Status MoE<T>::ComputeMoE(const OpKernelContext* context,
           int64_t route_idx = i * k_ + j;
           float weight = sorted_logits[static_cast<size_t>(j)].first;
 
-          route_expert[route_idx] = static_cast<int>(expert_idx);
+          route_expert[route_idx] = narrow<int>(expert_idx);
           route_scale[route_idx] = weight;
           if (weight > 0.0f) {
             local_expert_token_map[static_cast<size_t>(expert_idx)].push_back(route_idx);
@@ -319,7 +320,7 @@ Status MoE<T>::ComputeMoE(const OpKernelContext* context,
 
   // Optimized expert processing with thread-local buffer reuse
   concurrency::ThreadPool::TrySimpleParallelFor(tp, num_expert_threads, [&](std::ptrdiff_t thread_id_pd) {
-    int thread_id = static_cast<int>(thread_id_pd);
+    int thread_id = narrow<int>(thread_id_pd);
     auto work = concurrency::ThreadPool::PartitionWork(thread_id, num_expert_threads, static_cast<std::ptrdiff_t>(num_experts));
 
     float* local_output = thread_local_outputs + static_cast<size_t>(thread_id) * output_buffer_size;
@@ -440,6 +441,11 @@ Status MoE<T>::ProcessExpertBatch(const T* input_tokens,
                                   int64_t inter_size,
                                   T* fc1_output_buffer,
                                   T* activation_output_buffer) const {
+  ORT_UNUSED_PARAMETER(token_expert_ids);
+  ORT_UNUSED_PARAMETER(token_weights);
+  ORT_UNUSED_PARAMETER(expert_id);
+  ORT_UNUSED_PARAMETER(fc1_output_buffer);
+  ORT_UNUSED_PARAMETER(activation_output_buffer);
   const bool is_swiglu = activation_type_ == ActivationType::SwiGLU;
   const int64_t fc1_output_size = is_swiglu ? (inter_size * 2) : inter_size;