fix(//cpp): Remove deprecated script namespace

Signed-off-by: Naren Dasan <naren@narendasan.com>
Signed-off-by: Naren Dasan <narens@nvidia.com>

cpp/benchmark/main.cpp

@@ -37,7 +37,7 @@ void print_avg_std_dev(std::string type, std::vector<float>& runtimes, uint64_t
     std::transform(runtimes.begin(), runtimes.end(), rt_diff.begin(), [avg_runtime](float x) { return x - avg_runtime; });
     float rt_sq_sum = std::inner_product(rt_diff.begin(), rt_diff.end(), rt_diff.begin(), 0.0);
     float rt_std_dev = std::sqrt(rt_sq_sum / runtimes.size());
-    
+
     std::vector<float> fps_diff(runtimes.size());
     std::transform(runtimes.begin(), runtimes.end(), fps_diff.begin(), [fps, batch_size](float x) { return ((1000.f / x) * batch_size) - fps; });
     float fps_sq_sum = std::inner_product(fps_diff.begin(), fps_diff.end(), fps_diff.begin(), 0.0);
@@ -62,7 +62,7 @@ std::vector<float> benchmark_module(torch::jit::script::Module& mod, std::vector
         cudaDeviceSynchronize();
 
     }
-    
+
     for (uint64_t i = 0; i < NUM_RUNS; i++) {
         std::vector<torch::jit::IValue> inputs_ivalues;
         auto in = at::rand(shape, {at::kCUDA});
@@ -71,7 +71,7 @@ std::vector<float> benchmark_module(torch::jit::script::Module& mod, std::vector
 #endif
         inputs_ivalues.push_back(in.clone());
         cudaDeviceSynchronize();
-        
+
         execution_timer.start();
         mod.forward(inputs_ivalues);
         cudaDeviceSynchronize();
@@ -80,7 +80,7 @@ std::vector<float> benchmark_module(torch::jit::script::Module& mod, std::vector
         auto time = execution_timer.milliseconds();
         execution_timer.reset();
         execution_runtimes.push_back(time);
-        
+
         c10::cuda::CUDACachingAllocator::emptyCache();
     }
     return execution_runtimes;
@@ -91,9 +91,9 @@ int main(int argc, const char* argv[]) {
         std::cerr << "usage: benchmark <path-to-exported-script-module> <input-size>\n" << std::endl;
         return -1;
     }
-    
-    
-    torch::jit::script::Module mod;
+
+
+    torch::jit::Module mod;
     try {
         // Deserialize the ScriptModule from a file using torch::jit::load().
         mod = torch::jit::load(argv[1]);
@@ -104,16 +104,16 @@ int main(int argc, const char* argv[]) {
     }
 
     mod.to(at::kCUDA);
-    
+
 #ifdef HALF
     mod.to(torch::kHalf);
     for (auto layer : mod.named_modules()) {
         if (layer.name.find(".bn") != std::string::npos) {
             layer.value.to(torch::kFloat);
         }
     }
-#endif 
-    
+#endif
+
     std::vector<std::vector<int64_t>> dims;
     for (int i = 2; i < argc; i++) {
         auto arg = std::string(argv[i]);
@@ -128,7 +128,7 @@ int main(int argc, const char* argv[]) {
     }
 
     at::globalContext().setBenchmarkCuDNN(true);
-    
+
 #ifdef JIT
     auto jit_runtimes = benchmark_module(mod, dims[0]);
     print_avg_std_dev("JIT", jit_runtimes, dims[0][0]);
@@ -140,11 +140,11 @@ int main(int argc, const char* argv[]) {
 #ifdef HALF
     extra_info.op_precision = at::kHalf;
 #endif
-        
+
     auto trt_mod = trtorch::CompileGraph(mod, extra_info);
     auto trt_runtimes = benchmark_module(trt_mod, dims[0]);
     print_avg_std_dev("JIT/TRT", trt_runtimes, dims[0][0]);
 #endif
-    
+
     std::cout << "ok\n";
 }

cpp/ptq/main.cpp

@@ -18,7 +18,7 @@ int main(int argc, const char* argv[]) {
         return -1;
     }
 
-    torch::jit::script::Module mod;
+    torch::jit::Module mod;
     try {
          /// Deserialize the ScriptModule from a file using torch::jit::load().
          mod = torch::jit::load(argv[1]);

cpp/trtorchexec/main.cpp

@@ -27,7 +27,7 @@ int main(int argc, const char* argv[]) {
     }
 
 
-    torch::jit::script::Module mod;
+    torch::jit::Module mod;
     try {
         // Deserialize the ScriptModule from a file using torch::jit::load().
         mod = torch::jit::load(argv[1]);