[13/N] Fix clang-tidy warnings in jit (pytorch#132411)

Follows  pytorch#132209

Pull Request resolved: pytorch#132411
Approved by: https://github.com/Skylion007

torch/csrc/jit/tensorexpr/analysis.h

@@ -53,7 +53,6 @@ class NodeFinder : public IRVisitor {
   std::vector<NodePtr<Op>> nodes;
 };
 
-// NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
 class VarFinder : public IRVisitor {
  public:
   void visit(const VarPtr& v) override {
@@ -111,7 +110,6 @@ class BufFinder : public IRVisitor {
 // Finds all kinds of write operations to the provided Buf.
 class WritesToBuf : public IRVisitor {
  public:
-  // NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
   WritesToBuf(BufPtr target) : target_(std::move(target)) {}
 
   std::vector<StmtPtr> writes() {
@@ -143,7 +141,6 @@ class WritesToBuf : public IRVisitor {
 
 class StmtsReadingBuf : public IRVisitor {
  public:
-  // NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
   StmtsReadingBuf(BufPtr target) : target_(std::move(target)) {}
 
   std::vector<StmtPtr> reads() {
@@ -282,8 +279,8 @@ class BufLiveRange : public IRVisitor {
  public:
   BufLiveRange(BufPtr b) : buf_(std::move(b)) {}
 
-  static std::tuple<int32_t, int32_t> liveRange(StmtPtr s, BufPtr b) {
-    BlockPtr block = to<Block>(std::move(s));
+  static std::tuple<int32_t, int32_t> liveRange(const StmtPtr& s, BufPtr b) {
+    BlockPtr block = to<Block>(s);
     // We Only analyze buffer live ranges for block stmts.
     if (!block) {
       return std::make_tuple(0, 0);

torch/csrc/jit/tensorexpr/block_codegen.cpp

@@ -239,7 +239,6 @@ void BlockPrinter::PrintDistribution(const std::unordered_set<BufPtr>& bufs) {
   for (auto& buf : bufs) {
     emitIndent();
     emitIndent();
-    auto buf_name = buf->name_hint();
     os() << block_analysis_->getFlatInputName(buf) << " = ";
     os() << "{(0, 1, )}" << '\n';
   }

torch/csrc/jit/tensorexpr/block_codegen.h

@@ -14,9 +14,7 @@
 #include <torch/csrc/jit/tensorexpr/ir_visitor.h>
 #include <torch/csrc/jit/tensorexpr/unique_name_manager.h>
 
-namespace torch {
-namespace jit {
-namespace tensorexpr {
+namespace torch::jit::tensorexpr {
 
 // A class that analyzes the given program relevant for Block backend.
 class BlockAnalysis : public IRVisitor {
@@ -145,6 +143,4 @@ class TORCH_API BlockCodeGen : public CodeGen {
 
   std::string GetUniqueFuncName(const std::string& func_prefix);
 };
-} // namespace tensorexpr
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::tensorexpr

torch/csrc/jit/tensorexpr/codegen.h

@@ -155,20 +155,16 @@ class CodeGen::CallArg {
   CallArg(const PaddedBuffer<T>& buffer);
 
   template <typename T>
-  // NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init,cppcoreguidelines-pro-type-const-cast)
   CallArg(const std::vector<T>& buffer)
-      // NOLINTNEXTLINE(cppcoreguidelines-pro-type-const-cast)
       : data_(const_cast<T*>(buffer.data())) {}
 
-  // NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
   CallArg(void* ptr) : data_(ptr) {}
 
 #define ARG_TYPE_CTOR(Type, Name)      \
   CallArg(Type v) {                    \
     memcpy(buffer_, &v, sizeof(Type)); \
     data_ = (void*)buffer_;            \
   }
-  // NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
   AT_FORALL_SCALAR_TYPES_AND3(Bool, Half, BFloat16, ARG_TYPE_CTOR);
 #undef ARG_TYPE_CTOR
 
@@ -203,7 +199,6 @@ class CodeGen::CallArg {
     TORCH_INTERNAL_ASSERT(data_ == (void*)buffer_); \
     return (Type*)data_;                            \
   }
-  // NOLINTNEXTLINE(cppcoreguidelines-pro-type-const-cast)
   AT_FORALL_SCALAR_TYPES_AND3(Bool, Half, BFloat16, ARG_PTR_DEFINE);
 #undef ARG_PTR_DEFINE
 

torch/csrc/jit/tensorexpr/cpp_codegen.cpp

@@ -79,52 +79,52 @@ void CppPrinter::printPrologue() {
 template <typename T>
 inline std::enable_if_t<!std::is_floating_point_v<T>, void> visit_mod(
     std::ostream& os,
-    const ExprPtr lhs,
-    const ExprPtr rhs) {
+    const ExprPtr& lhs,
+    const ExprPtr& rhs) {
   os << *lhs << " % " << *rhs;
 }
 
 template <typename T>
 inline std::enable_if_t<std::is_floating_point_v<T>, void> visit_mod(
     std::ostream& os,
-    const ExprPtr lhs,
-    const ExprPtr rhs) {
+    const ExprPtr& lhs,
+    const ExprPtr& rhs) {
   os << "std::fmod(" << *lhs << ", " << *rhs << ")";
 }
 
 template <typename T>
 inline std::
     enable_if_t<std::is_floating_point_v<T> || std::is_integral_v<T>, void>
-    visit_max(std::ostream& os, const ExprPtr lhs, const ExprPtr rhs) {
+    visit_max(std::ostream& os, const ExprPtr& lhs, const ExprPtr& rhs) {
   os << "std::max(" << *lhs << ", " << *rhs << ")";
 }
 
 template <typename T>
 inline std::
     enable_if_t<!std::is_floating_point_v<T> && !std::is_integral_v<T>, void>
-    visit_max(std::ostream& os, const ExprPtr lhs, const ExprPtr rhs) {
+    visit_max(std::ostream& os, const ExprPtr& lhs, const ExprPtr& rhs) {
   os << "(" << *lhs << " < " << *rhs << ") ? " << *rhs << " : " << *lhs;
 }
 
 template <typename T>
 inline std::
     enable_if_t<std::is_floating_point_v<T> || std::is_integral_v<T>, void>
-    visit_min(std::ostream& os, const ExprPtr lhs, const ExprPtr rhs) {
+    visit_min(std::ostream& os, const ExprPtr& lhs, const ExprPtr& rhs) {
   os << "std::min(" << *lhs << ", " << *rhs << ")";
 }
 
 template <typename T>
 inline std::
     enable_if_t<!std::is_floating_point_v<T> && !std::is_integral_v<T>, void>
-    visit_min(std::ostream& os, const ExprPtr lhs, const ExprPtr rhs) {
+    visit_min(std::ostream& os, const ExprPtr& lhs, const ExprPtr& rhs) {
   os << *lhs << " < " << *rhs << " ? " << *lhs << " : " << *rhs;
 }
 
 template <typename T>
 void visit_binary_op(
     std::ostream& os,
-    const ExprPtr lhs,
-    const ExprPtr rhs,
+    const ExprPtr& lhs,
+    const ExprPtr& rhs,
     IRNodeType op_type) {
   switch (op_type) {
     case IRNodeType::kMod:
@@ -242,7 +242,7 @@ void CppPrinter::visit(const IntrinsicsPtr& v) {
   }
 
   os() << "std::" << v->func_name() << "(";
-  for (int i = 0; i < v->nparams(); i++) {
+  for (size_t i = 0; i < v->nparams(); i++) {
     if (i > 0) {
       os() << ", ";
     }

torch/csrc/jit/tensorexpr/cpp_codegen.h

@@ -3,9 +3,7 @@
 #include <torch/csrc/jit/tensorexpr/codegen.h>
 #include <torch/csrc/jit/tensorexpr/ir_printer.h>
 
-namespace torch {
-namespace jit {
-namespace tensorexpr {
+namespace torch::jit::tensorexpr {
 
 class CppVarNameRewriter;
 
@@ -97,6 +95,4 @@ class TORCH_API CppCodeGen : public CodeGen {
   std::unique_ptr<CppVarNameRewriter> var_name_rewriter_;
 };
 
-} // namespace tensorexpr
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::tensorexpr

torch/csrc/jit/tensorexpr/cuda_codegen.cpp

@@ -249,7 +249,7 @@ void CudaPrinter::visit(const IntrinsicsPtr& v) {
 
   // get type of resulting expression.
   ScalarType returnType = v->param(0)->dtype().scalar_type();
-  for (int i = 1; i < v->nparams(); ++i) {
+  for (size_t i = 1; i < v->nparams(); ++i) {
     returnType = promoteTypes(returnType, v->param(i)->dtype().scalar_type());
   }
 
@@ -1303,7 +1303,8 @@ void CudaCodeGen::CompileToNVRTC(
       "--std=c++17", compute.c_str(), "-default-device"};
 #endif
 
-  auto result = nvrtc().nvrtcCompileProgram(program, args.size(), args.data());
+  auto result = nvrtc().nvrtcCompileProgram(
+      program, static_cast<int>(args.size()), args.data());
   if (result != NVRTC_SUCCESS) {
     size_t logsize = 0;
     AT_CUDA_NVRTC_CHECK(nvrtc().nvrtcGetProgramLogSize(program, &logsize));

torch/csrc/jit/tensorexpr/cuda_codegen.h

@@ -16,9 +16,7 @@
 #include <torch/csrc/jit/tensorexpr/llvm_codegen.h>
 #include <torch/csrc/jit/tensorexpr/unique_name_manager.h>
 
-namespace torch {
-namespace jit {
-namespace tensorexpr {
+namespace torch::jit::tensorexpr {
 
 // A class that analyzes the given program relevant for Cuda backends.
 class CudaAnalysis : public IRVisitor {
@@ -74,7 +72,6 @@ class CudaAnalysis : public IRVisitor {
 // execution parameters, then if those params differ from the max mask each dim.
 class GPUMetaVarRewriter : public IRMutator {
  public:
-  // NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
   explicit GPUMetaVarRewriter(const CudaAnalysis* cuda_analysis)
       : cuda_analysis_(cuda_analysis) {
     gpu_block_vars_ = {
@@ -208,7 +205,6 @@ class TORCH_CUDA_CU_API CudaCodeGen : public CodeGen {
     Initialize();
   }
 
-  // NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
   CudaCodeGen(
       StmtPtr stmt,
       const std::vector<BufferArg>& buffer_args,
@@ -287,6 +283,4 @@ class TORCH_CUDA_CU_API CudaCodeGen : public CodeGen {
   std::string GetUniqueFuncName(const std::string& func_prefix);
 };
 
-} // namespace tensorexpr
-} // namespace jit
-} // namespace torch
+} // namespace torch::jit::tensorexpr

torch/csrc/jit/tensorexpr/eval.cpp

@@ -64,10 +64,8 @@ inline c10::BFloat16 div_value(c10::BFloat16 lhs, c10::BFloat16 rhs) {
   return lhs / rhs;
 }
 
-// NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
 class SimpleIREvaluatorImpl : public IRVisitor {
  public:
-  // NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
   SimpleIREvaluatorImpl() = default;
 
   ~SimpleIREvaluatorImpl() override = default;
@@ -626,8 +624,7 @@ class SimpleIREvaluatorImpl : public IRVisitor {
 
   TORCH_API void visit(const IfThenElsePtr& v) override {
     v->condition()->accept(this);
-    // NOLINTNEXTLINE(cppcoreguidelines-init-variables)
-    bool cond_v;
+    bool cond_v = false;
     switch (value_.dtype().scalar_type()) {
 #define TYPE_CASE(Type, Name)   \
   case ScalarType::Name: {      \
@@ -762,9 +759,7 @@ class SimpleIREvaluatorImpl : public IRVisitor {
     value_ = InterpValue(val);                       \
   } break;
       AT_FORALL_SCALAR_TYPES_AND3(Bool, Half, BFloat16, TYPE_CASE);
-      // NOLINTNEXTLINE(facebook-hte-LocalUncheckedArrayBounds)
       TYPE_CASE(c10::quint8, QUInt8);
-      // NOLINTNEXTLINE(facebook-hte-LocalUncheckedArrayBounds)
       TYPE_CASE(c10::qint8, QInt8);
 #undef TYPE_CASE
       default:
@@ -811,9 +806,7 @@ class SimpleIREvaluatorImpl : public IRVisitor {
     }                                                           \
   } break;
       AT_FORALL_SCALAR_TYPES_AND3(Bool, Half, BFloat16, TYPE_CASE);
-      // NOLINTNEXTLINE(facebook-hte-LocalUncheckedArrayBounds)
       TYPE_CASE(c10::quint8, QUInt8);
-      // NOLINTNEXTLINE(facebook-hte-LocalUncheckedArrayBounds)
       TYPE_CASE(c10::qint8, QInt8);
 #undef TYPE_CASE
       default:
@@ -862,8 +855,7 @@ class SimpleIREvaluatorImpl : public IRVisitor {
     }
     for (const ExprPtr& a : v->args()) {
       a->accept(this);
-      // NOLINTNEXTLINE(cppcoreguidelines-init-variables)
-      int64_t val;
+      int64_t val = 0;
       if (value().dtype() == kLong) {
         val = value().as<int64_t>();
       } else if (value().dtype() == kInt) {
@@ -934,8 +926,7 @@ class SimpleIREvaluatorImpl : public IRVisitor {
     }
     for (const auto& a : v->args()) {
       a->accept(this);
-      // NOLINTNEXTLINE(cppcoreguidelines-init-variables)
-      int64_t val;
+      int64_t val = 0;
       if (value().dtype() == kLong) {
         val = value().as<int64_t>();
       } else if (value().dtype() == kInt) {

torch/csrc/jit/tensorexpr/eval.h

@@ -42,12 +42,10 @@ class InterpValue {
   AT_FORALL_SCALAR_TYPES_AND3(Bool, Half, BFloat16, VALUE_CTOR);
 #undef VALUE_CTOR
 
-  // NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
   explicit InterpValue(c10::quint8 v) : dtype_(kQUInt8) {
     QUInt8values.emplace_back(v.val_);
   }
 
-  // NOLINTNEXTLINE(cppcoreguidelines-pro-type-member-init)
   explicit InterpValue(c10::qint8 v) : dtype_(kQInt8) {
     QInt8values.emplace_back(v.val_);
   }
@@ -226,7 +224,6 @@ class ExprEval {
       TYPE_CASE(c10::qint8, QInt8);
 #undef TYPE_CASE
       case ScalarType::Bool: {
-        // NOLINTNEXTLINE(cppcoreguidelines-init-variables)
         std::vector<unsigned char> ret_val_arg(1);
         call_args_extended.emplace_back(ret_val_arg.data());
         codegen_->call(call_args_extended);
@@ -238,7 +235,6 @@ class ExprEval {
   }
 
   void call_raw(const std::vector<void*>& args) {
-    // NOLINTNEXTLINE(cppcoreguidelines-init-variables)
     std::vector<void*> args_extended = args;
     switch (dtype_.scalar_type()) {
 #define TYPE_CASE(Type, Name)                    \
@@ -253,7 +249,6 @@ class ExprEval {
       TYPE_CASE(c10::qint8, QInt8);
 #undef TYPE_CASE
       case ScalarType::Bool: {
-        // NOLINTNEXTLINE(cppcoreguidelines-init-variables)
         std::vector<unsigned char> ret_val_arg(1);
         args_extended.push_back(ret_val_arg.data());
         codegen_->call_raw(args_extended);