irange-ify 13b (#62476)

Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/62476

Test Plan: Sandcastle

Reviewed By: malfet

Differential Revision: D30001445

fbshipit-source-id: 6f4525338c80e9f929695f47f36ca9c72d96a75d

diff --git a/torch/csrc/jit/serialization/onnx.cpp b/torch/csrc/jit/serialization/onnx.cpp
index 1245633..9e45d78 100644 (file)
--- a/torch/csrc/jit/serialization/onnx.cpp
+++ b/torch/csrc/jit/serialization/onnx.cpp
@@ -1,3 +1,4 @@
+#include <c10/util/irange.h>
 #include <torch/csrc/jit/serialization/onnx.h>
 #include <torch/csrc/onnx/onnx.h>
 
@@ -24,14 +25,14 @@ std::string nlidt(size_t indent) {
 
 void dump(const onnx::TensorProto& tensor, std::ostream& stream) {
   stream << "TensorProto shape: [";
-  for (int i = 0; i < tensor.dims_size(); ++i) {
+  for (const auto i : c10::irange(tensor.dims_size())) {
     stream << tensor.dims(i) << (i == tensor.dims_size() - 1 ? "" : " ");
   }
   stream << "]";
 }
 
 void dump(const onnx::TensorShapeProto& shape, std::ostream& stream) {
-  for (int i = 0; i < shape.dim_size(); ++i) {
+  for (const auto i : c10::irange(shape.dim_size())) {
     auto& dim = shape.dim(i);
     if (dim.has_dim_value()) {
       stream << dim.dim_value();
@@ -108,19 +109,19 @@ void dump(
     dump(attr.t(), stream);
   } else if (attr.floats_size()) {
     stream << "floats, values: [";
-    for (int i = 0; i < attr.floats_size(); ++i) {
+    for (const auto i : c10::irange(attr.floats_size())) {
       stream << attr.floats(i) << (i == attr.floats_size() - 1 ? "" : " ");
     }
     stream << "]";
   } else if (attr.ints_size()) {
     stream << "ints, values: [";
-    for (int i = 0; i < attr.ints_size(); ++i) {
+    for (const auto i : c10::irange(attr.ints_size())) {
       stream << attr.ints(i) << (i == attr.ints_size() - 1 ? "" : " ");
     }
     stream << "]";
   } else if (attr.strings_size()) {
     stream << "strings, values: [";
-    for (int i = 0; i < attr.strings_size(); ++i) {
+    for (const auto i : c10::irange(attr.strings_size())) {
       stream << "'" << attr.strings(i) << "'"
              << (i == attr.strings_size() - 1 ? "" : " ");
     }
@@ -145,15 +146,15 @@ void dump(
 
 void dump(const onnx::NodeProto& node, std::ostream& stream, size_t indent) {
   stream << "Node {type: \"" << node.op_type() << "\", inputs: [";
-  for (int i = 0; i < node.input_size(); ++i) {
+  for (const auto i : c10::irange(node.input_size())) {
     stream << node.input(i) << (i == node.input_size() - 1 ? "" : ",");
   }
   stream << "], outputs: [";
-  for (int i = 0; i < node.output_size(); ++i) {
+  for (const auto i : c10::irange(node.output_size())) {
     stream << node.output(i) << (i == node.output_size() - 1 ? "" : ",");
   }
   stream << "], attributes: [";
-  for (int i = 0; i < node.attribute_size(); ++i) {
+  for (const auto i : c10::irange(node.attribute_size())) {
     dump(node.attribute(i), stream, indent + 1);
     stream << (i == node.attribute_size() - 1 ? "" : ",");
   }
@@ -163,27 +164,27 @@ void dump(const onnx::NodeProto& node, std::ostream& stream, size_t indent) {
 void dump(const onnx::GraphProto& graph, std::ostream& stream, size_t indent) {
   stream << idt(indent) << "GraphProto {" << nlidt(indent + 1) << "name: \""
          << graph.name() << "\"" << nlidt(indent + 1) << "inputs: [";
-  for (int i = 0; i < graph.input_size(); ++i) {
+  for (const auto i : c10::irange(graph.input_size())) {
     dump(graph.input(i), stream);
     stream << (i == graph.input_size() - 1 ? "" : ",");
   }
   stream << "]" << nlidt(indent + 1) << "outputs: [";
-  for (int i = 0; i < graph.output_size(); ++i) {
+  for (const auto i : c10::irange(graph.output_size())) {
     dump(graph.output(i), stream);
     stream << (i == graph.output_size() - 1 ? "" : ",");
   }
   stream << "]" << nlidt(indent + 1) << "value_infos: [";
-  for (int i = 0; i < graph.value_info_size(); ++i) {
+  for (const auto i : c10::irange(graph.value_info_size())) {
     dump(graph.value_info(i), stream);
     stream << (i == graph.value_info_size() - 1 ? "" : ",");
   }
   stream << "]" << nlidt(indent + 1) << "initializers: [";
-  for (int i = 0; i < graph.initializer_size(); ++i) {
+  for (const auto i : c10::irange(graph.initializer_size())) {
     dump(graph.initializer(i), stream);
     stream << (i == graph.initializer_size() - 1 ? "" : ",");
   }
   stream << "]" << nlidt(indent + 1) << "nodes: [" << nlidt(indent + 2);
-  for (int i = 0; i < graph.node_size(); ++i) {
+  for (const auto i : c10::irange(graph.node_size())) {
     dump(graph.node(i), stream, indent + 2);
     if (i != graph.node_size() - 1) {
       stream << "," << nlidt(indent + 2);

diff --git a/torch/csrc/jit/serialization/pickler.cpp b/torch/csrc/jit/serialization/pickler.cpp
index eaf077b..4a4e866 100644 (file)
--- a/torch/csrc/jit/serialization/pickler.cpp
+++ b/torch/csrc/jit/serialization/pickler.cpp
@@ -4,6 +4,7 @@
 #include <torch/csrc/distributed/rpc/rref_context.h>
 #endif
 #include <aten/src/ATen/quantized/Quantizer.h>
+#include <c10/util/irange.h>
 #include <torch/csrc/jit/api/function_impl.h>
 #include <torch/csrc/jit/serialization/pickler.h>
 #include <string>
@@ -460,7 +461,7 @@ static inline double swapDouble(double value) {
   // NOLINTNEXTLINE(cppcoreguidelines-init-variables)
   double flipped;
   char* out_bytes = reinterpret_cast<char*>(&flipped);
-  for (size_t i = 0; i < sizeof(double); ++i) {
+  for (const auto i : c10::irange(sizeof(double))) {
     out_bytes[i] = bytes[sizeof(double) - i - 1];
   }
   return *reinterpret_cast<double*>(out_bytes);

diff --git a/torch/csrc/jit/serialization/python_print.cpp b/torch/csrc/jit/serialization/python_print.cpp
index f43a33e..f5a5a74 100644 (file)
--- a/torch/csrc/jit/serialization/python_print.cpp
+++ b/torch/csrc/jit/serialization/python_print.cpp
@@ -27,7 +27,7 @@ static bool isValidIdentifierChar(char c, size_t pos) {
 static bool isValidIdentifier(const std::string& name) {
   if (name.size() == 0)
     return false;
-  for (size_t i = 0; i < name.size(); ++i) {
+  for (const auto i : c10::irange(name.size())) {
     if (!isValidIdentifierChar(name[i], i))
       return false;
   }
@@ -315,7 +315,7 @@ struct PythonPrintImpl {
     // We will probably need to optimize this at some point using hashing.
     if (val.isTensor()) {
       auto& t = val.toTensor();
-      for (size_t i = 0; i < constant_table_.size(); ++i) {
+      for (const auto i : c10::irange(constant_table_.size())) {
         if (!constant_table_[i].isTensor()) {
           continue;
         }
@@ -432,7 +432,8 @@ struct PythonPrintImpl {
   size_t level = 0;
   // indent to the current indent level
   TaggedStringStream& indent() {
-    for (size_t i = 0; i < level; ++i) {
+    for (const auto i : c10::irange(level)) {
+      (void)i; // Suppress unused variable warning
       body_ << "  ";
     }
     return body_;
@@ -522,7 +523,7 @@ struct PythonPrintImpl {
   void printAnnotatedAssignment(
       at::ArrayRef<Value*> lhs,
       at::ArrayRef<Value*> rhs) {
-    for (size_t i = 0; i < lhs.size(); ++i) {
+    for (const auto i : c10::irange(lhs.size())) {
       indent();
       body_ << useOf(lhs[i]);
       if (requiresAnnotation(lhs[i], rhs[i])) {
@@ -1164,7 +1165,7 @@ struct PythonPrintImpl {
         // details.
         size_t necessary_args =
             CalculateNecessaryArgs(schema.arguments(), node->inputs());
-        for (size_t i = 0; i < necessary_args; ++i) {
+        for (const auto i : c10::irange(necessary_args)) {
           if (i > 0)
             stmt << ", ";
           auto v = useOf(node->inputs().at(i));
@@ -1205,7 +1206,8 @@ struct PythonPrintImpl {
   IValue createBroadList(dtype value, const int64_t& N) {
     c10::List<dtype> repeated;
     repeated.reserve(N);
-    for (int i = 0; i < N; ++i) {
+    for (const auto i : c10::irange(N)) {
+      (void)i; // Suppress unused variable warning
       repeated.push_back(value);
     }
     return repeated;