Modernize for-loops (#50912)

Summary: Pull Request resolved: #50912

Test Plan: Sandcastle tests

Reviewed By: ansley

Differential Revision: D26001948

fbshipit-source-id: 3bfe6a8283a2b1882ed472f836ae1b6e720e519f

test/cpp/api/serialize.cpp

@@ -493,8 +493,8 @@ TEST(SerializeTest, Optim_Adagrad) {
   std::vector<int64_t> step_buffers;
   const auto& params_ = optim1.param_groups()[0].params();
   const auto& optim1_state = optim1.state();
-  for (size_t i = 0; i < params_.size(); i++) {
-    auto key_ = c10::guts::to_string(params_[i].unsafeGetTensorImpl());
+  for (const auto & param : params_) {
+    auto key_ = c10::guts::to_string(param.unsafeGetTensorImpl());
     const AdagradParamState& curr_state_ = static_cast<const AdagradParamState&>(*(optim1_state.at(key_).get()));
     sum_buffers.emplace_back(curr_state_.sum());
     step_buffers.emplace_back(curr_state_.step());

test/cpp/jit/test_backend.cpp

@@ -26,8 +26,8 @@ class TestBackend : public PyTorchBackendInterface {
 
     // Return the same string as a value for every key in method_compile_spec.
     auto handles = c10::Dict<std::string, std::string>();
-    for (auto it = spec.begin(), end = spec.end(); it != end; ++it) {
-      handles.insert(it->key(), it->key());
+    for (const auto& it : spec) {
+      handles.insert(it.key(), it.key());
     }
     return c10::impl::toGenericDict(handles);
   }

test/cpp/jit/test_gpu.cpp

@@ -21,7 +21,7 @@
 
 // fuser and IR parser
 #include <torch/csrc/jit/codegen/cuda/parser.h>
-#include "torch/csrc/jit/ir/irparser.h"
+#include <torch/csrc/jit/ir/irparser.h>
 
 #include <ATen/cuda/Exceptions.h>
 #include <c10/cuda/CUDAStream.h>
@@ -59,9 +59,9 @@ TensorView* makeConcreteTensor(
   // We can uncomment the below statement to test all tests with contiguous
   // tensors. return makeContigTensor(nDims, dtype);
   std::vector<IterDomain*> dom;
-  for (size_t i = 0; i < sizes.size(); i++) {
-    if (sizes[i] >= 0) {
-      dom.push_back(new IterDomain(new Int(0), new Int(sizes[i])));
+  for (int size : sizes) {
+    if (size >= 0) {
+      dom.push_back(new IterDomain(new Int(0), new Int(size)));
     } else {
       dom.push_back(new IterDomain(new Int(0), new Int()));
     }
@@ -7353,9 +7353,9 @@ TEST(NVFuserTest, FusionLSTMCell_CUDA) {
   FusionGuard fg(&fusion);
 
   TensorView* tvs[16];
-  for (size_t i = 0; i < 16; i++) {
-    tvs[i] = makeDummyTensor(2);
-    fusion.addInput(tvs[i]);
+  for (auto& tv : tvs) {
+    tv = makeDummyTensor(2);
+    fusion.addInput(tv);
   }
 
   auto ingate = unaryOp(