[jit] kill script namespace (#34515)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/34515

Once upon a time we thought this was necessary. In reality it is not, so
removing it.

For backcompat, our public interface (defined in `api/`) still has
typedefs to the old `script::` names.

There was only one collision: `Pass` as a `Stmt` and `Pass` as a graph
transform. I renamed one of them.

Test Plan: Imported from OSS

Differential Revision: D20353503

Pulled By: suo

fbshipit-source-id: 48bb911ce75120a8c9e0c6fb65262ef775dfba93

android/pytorch_android/generate_test_asset.cpp

@@ -13,7 +13,7 @@ int main(int argc, char* argv[]) {
   std::ifstream ifs(input_file_path);
   std::stringstream buffer;
   buffer << ifs.rdbuf();
-  torch::jit::script::Module m("TestModule");
+  torch::jit::Module m("TestModule");
 
   m.define(buffer.str());
   m.save(output_file_path);

android/pytorch_android/src/main/cpp/pytorch_jni_jit.cpp

@@ -58,7 +58,7 @@ class MemoryReadAdapter final : public caffe2::serialize::ReadAdapterInterface {
 class PytorchJni : public facebook::jni::HybridClass<PytorchJni> {
  private:
   friend HybridBase;
-  torch::jit::script::Module module_;
+  torch::jit::Module module_;
 
  public:
   constexpr static auto kJavaDescriptor = "Lorg/pytorch/NativePeer;";

android/pytorch_android/src/main/java/org/pytorch/Module.java

@@ -5,7 +5,7 @@ package org.pytorch;
 import com.facebook.soloader.nativeloader.NativeLoader;
 import com.facebook.soloader.nativeloader.SystemDelegate;
 
-/** Java wrapper for torch::jit::script::Module. */
+/** Java wrapper for torch::jit::Module. */
 public class Module {
 
   private INativePeer mNativePeer;
@@ -14,7 +14,7 @@ public class Module {
    * Loads a serialized TorchScript module from the specified path on the disk.
    *
    * @param modelPath path to file that contains the serialized TorchScript module.
-   * @return new {@link org.pytorch.Module} object which owns torch::jit::script::Module.
+   * @return new {@link org.pytorch.Module} object which owns torch::jit::Module.
    */
   public static Module load(final String modelPath) {
     if (!NativeLoader.isInitialized()) {
@@ -49,7 +49,7 @@ public class Module {
   }
 
   /**
-   * Explicitly destroys the native torch::jit::script::Module. Calling this method is not required,
+   * Explicitly destroys the native torch::jit::Module. Calling this method is not required,
    * as the native object will be destroyed when this object is garbage-collected. However, the
    * timing of garbage collection is not guaranteed, so proactively calling {@code destroy} can free
    * memory more quickly. See {@link com.facebook.jni.HybridData#resetNative}.

aten/src/ATen/core/function.h

@@ -22,7 +22,7 @@ TORCH_API void preoptimizeGraph(std::shared_ptr<Graph>& graph);
 
 // A Function is a pure Graph with no implicit `self` object bound.
 // It contains schema information, and the executor that manages the
-// execution of the function. script::Method is a wrapper around a
+// execution of the function. Method is a wrapper around a
 // underlying Function that also provides a `self` object.
 struct TORCH_API Function {
   virtual bool isGraphFunction() const = 0;

aten/src/ATen/core/ivalue.cpp

@@ -378,7 +378,7 @@ std::vector<std::pair<IValue, IValue>> iterationOrder(const c10::Dict<IValue, IV
 }
 
 StrongTypePtr::StrongTypePtr(
-    std::shared_ptr<torch::jit::script::CompilationUnit> cu,
+    std::shared_ptr<torch::jit::CompilationUnit> cu,
     std::shared_ptr<Type> type) {
   cu_ = std::move(cu);
   type_ = type;

aten/src/ATen/core/ivalue.h

@@ -11,10 +11,8 @@ namespace jit {
 class CustomClassHolder : public c10::intrusive_ptr_target {};
 
 struct Function;
-namespace script {
 struct CompilationUnit;
 struct Module;
-}
 } // namespace jit
 } // namespace torch
 namespace c10 {
@@ -356,7 +354,7 @@ struct CAFFE2_API IValue final {
   c10::intrusive_ptr<ivalue::Object> toObject() const & ;
   const ivalue::Object& toObjectRef() const;
 
-  torch::jit::script::Module toModule() const;
+  torch::jit::Module toModule() const;
   bool isModule() const;
 
   // PyObject
@@ -692,10 +690,10 @@ private:
 // guaranteed to stay alive as long as we hold this object.
 struct TORCH_API StrongTypePtr {
   StrongTypePtr(
-      std::shared_ptr<torch::jit::script::CompilationUnit> cu,
+      std::shared_ptr<torch::jit::CompilationUnit> cu,
       std::shared_ptr<Type> type);
 
-  std::shared_ptr<torch::jit::script::CompilationUnit> cu_;
+  std::shared_ptr<torch::jit::CompilationUnit> cu_;
   std::shared_ptr<Type> type_;
 };
 

aten/src/ATen/core/ivalue_inl.h

@@ -15,9 +15,7 @@
 namespace torch {
 namespace jit {
 struct Function;
-namespace script {
 struct CompilationUnit;
-}
 } // namespace jit
 } // namespace torch
 namespace c10 {
@@ -406,7 +404,7 @@ struct C10_EXPORT ivalue::Object final : c10::intrusive_ptr_target {
   }
   std::shared_ptr<ClassType> type() const;
 
-  std::shared_ptr<torch::jit::script::CompilationUnit> compilation_unit() {
+  std::shared_ptr<torch::jit::CompilationUnit> compilation_unit() {
     return type_.cu_;
   }
 
@@ -868,7 +866,7 @@ IValue from_(c10::intrusive_ptr<T> x, std::false_type) {
   auto res = getCustomClassType<inputType>();
   auto retObject = ivalue::Object::create(
     StrongTypePtr(
-      std::shared_ptr<torch::jit::script::CompilationUnit>(),
+      std::shared_ptr<torch::jit::CompilationUnit>(),
       std::move(res)),
     1);
   auto objPtr = c10::static_intrusive_pointer_cast<torch::jit::CustomClassHolder>(std::move(x));

aten/src/ATen/core/jit_type.h

@@ -17,9 +17,7 @@
 struct ClassType;
 namespace torch {
 namespace jit {
-namespace script {
 struct CompilationUnit;
-}
 } // namespace jit
 } // namespace torch
 
@@ -1491,7 +1489,7 @@ CAFFE2_API bool elementTypeCanBeInferredFromMembers(const TypePtr& elem_type);
 
 struct ClassType;
 using ClassTypePtr = std::shared_ptr<ClassType>;
-using ::torch::jit::script::CompilationUnit;
+using ::torch::jit::CompilationUnit;
 
 // This represents a class in TorchScript.
 struct CAFFE2_API ClassType : public NamedType {
@@ -1801,7 +1799,7 @@ struct CAFFE2_API ClassType : public NamedType {
 
 struct InterfaceType;
 using InterfaceTypePtr = std::shared_ptr<InterfaceType>;
-using ::torch::jit::script::CompilationUnit;
+using ::torch::jit::CompilationUnit;
 
 // Interfaces are a list of abstract methods that a class might meet.
 // If a class provides those methods, it implicitly meets the interface.

binaries/dump_operator_names.cc

@@ -24,7 +24,7 @@
 
 namespace torch {
 namespace jit {
-void dump_opnames(const script::Module& m, std::unordered_set<std::string>& opnames) {
+void dump_opnames(const Module& m, std::unordered_set<std::string>& opnames) {
   auto methods = m.get_methods();
   for (const auto& method : methods) {
     const auto& func = method.function();

caffe2/contrib/pytorch/script_module_op.cc

@@ -7,8 +7,8 @@
 namespace caffe2 {
 
 using torch::jit::IValue;
-using torch::jit::script::Method;
+using torch::jit::Method;
-using torch::jit::script::Module;
+using torch::jit::Module;
 
 namespace {
 class ScriptModuleSerializer : public BlobSerializerBase {
@@ -31,7 +31,7 @@ class ScriptModuleSerializer : public BlobSerializerBase {
     // the more efficient serialization version (if we ever get to that point)
     BlobProto blob_proto;
     blob_proto.set_name(name);
-    blob_proto.set_type("torch::jit::script::Module");
+    blob_proto.set_type("torch::jit::Module");
     blob_proto.set_content(ss.str());
     acceptor(name, SerializeBlobProtoAsString_EnforceCheck(blob_proto));
   }
@@ -134,7 +134,7 @@ REGISTER_BLOB_SERIALIZER(
 // NB: the first argument to REGISTER_BLOB_DESERIALIZER macro doesn't really
 // need to be a real type, it just get converted to string
 REGISTER_BLOB_DESERIALIZER(
-    torch::jit::script::Module,
+    torch::jit::Module,
     ScriptModuleDeserializer);
 
 OPERATOR_SCHEMA(ScriptModule)

caffe2/python/pybind_state.cc

@@ -94,12 +94,12 @@ REGISTER_BLOB_FETCHER((TypeMeta::Id<string>()), StringFetcher);
 class ScriptModuleFetcher : public BlobFetcherBase {
  public:
   pybind11::object Fetch(const Blob& blob) override {
-    return py::cast(*blob.Get<std::unique_ptr<torch::jit::script::Module>>());
+    return py::cast(*blob.Get<std::unique_ptr<torch::jit::Module>>());
   }
 };
 
 REGISTER_BLOB_FETCHER(
-    (TypeMeta::Id<std::unique_ptr<torch::jit::script::Module>>()),
+    (TypeMeta::Id<std::unique_ptr<torch::jit::Module>>()),
     caffe2::python::ScriptModuleFetcher);
 #endif
 
@@ -247,9 +247,9 @@ bool feedBlob(
     return true;
   }
 #ifdef FBCODE_CAFFE2
-  if (auto module = torch::jit::script::as_module(arg)) {
+  if (auto module = torch::jit::as_module(arg)) {
-    blob->GetMutable<std::unique_ptr<torch::jit::script::Module>>()->reset(
+    blob->GetMutable<std::unique_ptr<torch::jit::Module>>()->reset(
-        new torch::jit::script::Module(*module));
+        new torch::jit::Module(*module));
     return true;
   }
 #endif

docs/source/jit.rst

@@ -213,7 +213,7 @@ Disable JIT for Debugging
     Python. Since TorchScript (scripting and tracing) are disabled with this flag,
     you can use tools like ``pdb`` to debug the model code.
 
-    Given an example script::
+    Given an example 
 
         @torch.jit.script
         def scripted_fn(x : torch.Tensor):

docs/source/notes/large_scale_deployments.rst

@@ -120,8 +120,8 @@ usage might look like:
 
 .. code-block:: cpp
 
-    SetExportModuleExtraFilesHook([](const script::Module&) {
+    SetExportModuleExtraFilesHook([](const Module&) {
-        script::ExtraFilesMap files;
+        ExtraFilesMap files;
         files["producer_info.json"] = "{\"user\": \"" + getenv("USER") + "\"}";
         return files;
     });

docs/source/org/pytorch/Module.rst

@@ -8,7 +8,7 @@ Module
 
 .. java:type:: public class Module
 
-   Java wrapper for torch::jit::script::Module.
+   Java wrapper for torch::jit::Module.
 
 Methods
 -------
@@ -18,7 +18,7 @@ destroy
 .. java:method:: public void destroy()
    :outertype: Module
 
-   Explicitly destroys the native torch::jit::script::Module. Calling this method is not required, as the native object will be destroyed when this object is garbage-collected. However, the timing of garbage collection is not guaranteed, so proactively calling \ ``destroy``\  can free memory more quickly. See \ :java:ref:`com.facebook.jni.HybridData.resetNative`\ .
+   Explicitly destroys the native torch::jit::Module. Calling this method is not required, as the native object will be destroyed when this object is garbage-collected. However, the timing of garbage collection is not guaranteed, so proactively calling \ ``destroy``\  can free memory more quickly. See \ :java:ref:`com.facebook.jni.HybridData.resetNative`\ .
 
 forward
 ^^^^^^^
@@ -40,7 +40,7 @@ load
    Loads a serialized TorchScript module from the specified path on the disk.
 
    :param modelPath: path to file that contains the serialized TorchScript module.
-   :return: new \ :java:ref:`org.pytorch.Module`\  object which owns torch::jit::script::Module.
+   :return: new \ :java:ref:`org.pytorch.Module`\  object which owns torch::jit::Module.
 
 runMethod
 ^^^^^^^^^

ios/TestApp/TestAppTests/TestAppTests.mm

@@ -7,7 +7,7 @@
 @end
 
 @implementation TestAppTests {
-  torch::jit::script::Module _module;
+  torch::jit::Module _module;
 }
 
 + (void)setUp {

test/cpp/jit/test_alias_analysis.cpp

@@ -395,7 +395,7 @@ void testAliasAnalysis() {
     {
       auto graph = std::make_shared<Graph>();
       std::unordered_map<std::string, Value*> vmap;
-      script::parseIR(
+      parseIR(
           R"IR(
     graph():
       %opt : Tensor? = prim::Constant()
@@ -415,7 +415,7 @@ void testAliasAnalysis() {
   {
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
   graph(%x : Tensor):
       %3 : int = prim::Constant[value=1]()
@@ -491,7 +491,7 @@ void testWriteTracking() {
   }
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
   graph(%x: Tensor):
     %b : Tensor = aten::relu_(%x)
@@ -505,7 +505,7 @@ void testWriteTracking() {
   }
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
   graph(%x: Tensor, %y : Tensor):
     %b : Tensor = aten::mul(%x, %y)
@@ -520,7 +520,7 @@ void testWriteTracking() {
   {
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
   graph(%x: Tensor, %y : Tensor):
     %c1 : int = prim::Constant[value=1]()
@@ -540,7 +540,7 @@ void testContainerAliasing() {
   {
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
   graph(%inp: Tensor[]):
     %x : str = prim::Constant[value="a"]()
@@ -574,7 +574,7 @@ void testContainerAliasing() {
 
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
   graph():
     %x : str = prim::Constant[value="a"]()
@@ -601,7 +601,7 @@ void testContainerAliasing() {
   // Test input aliasing
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
   graph(%x: Tensor, %y: Tensor):
     %a : (Tensor) = prim::TupleConstruct(%x)
@@ -622,7 +622,7 @@ void testContainerAliasing() {
   // Test tuple that doesn't come from construct
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%x : int,
       %y : Tensor,
@@ -654,7 +654,7 @@ graph(%x : int,
   // test nested types
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
 graph():
   %a : Tensor = prim::MakeTestTensor()
@@ -681,7 +681,7 @@ graph():
   // simple example
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
 graph():
   %0 : Tensor = prim::Constant()
@@ -711,7 +711,7 @@ graph():
   {
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
   graph():
     %x : str = prim::Constant[value="a"]()
@@ -737,7 +737,7 @@ graph():
     // Test list container aliasing
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
 graph():
   %0 : int = prim::Constant[value=2]()
@@ -779,7 +779,7 @@ graph():
 
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
 graph():
   %0 : int = prim::Constant[value=2]()
@@ -810,7 +810,7 @@ graph():
     // print across it.
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
 graph():
   %35 : int = prim::Constant[value=1]()
@@ -849,7 +849,7 @@ graph():
     // print across it.
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
 graph():
   %38 : int = prim::Constant[value=1]()
@@ -935,7 +935,7 @@ void testWildcards() {
   {
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
   graph(%ten_list : Tensor[], %int_list : int[], %opt_ten_list : Tensor[]?):
     %ten : Tensor = prim::Constant()
@@ -971,7 +971,7 @@ void testWildcards() {
   {
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
   graph(%ten_list : Tensor[], %ten_opt_list : Tensor?[]):
     %ten : Tensor = prim::Constant()
@@ -992,7 +992,7 @@ void testWildcards() {
   {
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
   graph(%float_3D : Float(*, *, *), %float_2D : Float(*, *)):
     return ()
@@ -1006,7 +1006,7 @@ void testWildcards() {
   {
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
   graph(%float_3D_list : Float(*, *, *)[], %float_2D_list : Float(*, *)[], %ten: Tensor):
     return ()

test/cpp/jit/test_autodiff.cpp

@@ -213,7 +213,7 @@ void testDifferentiateWithRequiresGrad() {
       %7 : Tensor = aten::add(%6, %1, %2)
       return (%4, %7))IR";
   auto g = std::make_shared<Graph>();
-  torch::jit::script::parseIR(graph_string, g.get());
+  torch::jit::parseIR(graph_string, g.get());
 
   auto a_var = autograd::make_variable(
       at::empty_strided(2, 2, at::CPU(at::kFloat).options()), true);

test/cpp/jit/test_class_import.cpp

@@ -9,8 +9,6 @@
 namespace torch {
 namespace jit {
 
-using namespace torch::jit::script;
-
 static const auto classSrcs1 = R"JIT(
 class FooNestedTest:
     def __init__(self, y):

test/cpp/jit/test_class_parser.cpp

@@ -4,7 +4,6 @@
 
 namespace torch {
 namespace jit {
-using namespace torch::jit::script;
 const auto testSource = R"JIT(
   class FooTest:
     def __init__(self, x):

test/cpp/jit/test_class_type.cpp

@@ -5,8 +5,6 @@
 namespace torch {
 namespace jit {
 
-using namespace torch::jit::script;
-
 void testClassTypeAddRemoveAttr() {
   auto cu = std::make_shared<CompilationUnit>();
   auto cls = ClassType::create("foo.bar", cu, true);

test/cpp/jit/test_constant_pooling.cpp

@@ -14,7 +14,7 @@ namespace jit {
 void testConstantPooling() {
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
 graph():
   %8 : int = prim::Constant[value=1]()
@@ -29,7 +29,7 @@ graph():
   }
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%cond : Tensor):
   %a : str = prim::Constant[value="bcd"]()
@@ -53,7 +53,7 @@ graph(%cond : Tensor):
   }
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
 graph():
   %2 : int = prim::Constant[value=2]()

test/cpp/jit/test_custom_operators.cpp

@@ -145,7 +145,7 @@ void testCustomOperatorAliasing() {
 
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%x: Tensor, %y: Tensor):
   %ret : Tensor = foo::aliasing(%x, %y)
@@ -172,7 +172,7 @@ graph(%x: Tensor, %y: Tensor):
   %ret : Tensor = foo::aliasing(%x, %y)
   return (%x)
   )IR";
-    script::parseIR(text, graph.get());
+    parseIR(text, graph.get());
     EliminateDeadCode(graph);
 
     testing::FileCheck().run(text, *graph);

test/cpp/jit/test_dce.cpp

@@ -43,7 +43,7 @@ graph():
       -> (%50, %tot.3)
   return (%tot)
 )IR";
-  script::parseIR(input, graph.get());
+  parseIR(input, graph.get());
   EliminateDeadCode(graph);
   // Check that dead code elimin
   testing::FileCheck().run(input, *graph);

test/cpp/jit/test_fuser.cpp

@@ -67,7 +67,7 @@ void testFusion() {
         %2 : Tensor = aten::mul(%0, %1)
         return (%2))IR";
     Graph graph;
-    torch::jit::script::parseIR(graph_string, &graph);
+    torch::jit::parseIR(graph_string, &graph);
 
     auto a = at::rand({3, 4}, at::kCUDA);
     auto b = at::rand({4, 3}, at::kCUDA).transpose(0, 1);
@@ -100,7 +100,7 @@ void testFusion() {
         %14 : Tensor = aten::mul(%8, %13)
         return (%14, %12))IR";
     Graph graph;
-    torch::jit::script::parseIR(graph_string, &graph);
+    torch::jit::parseIR(graph_string, &graph);
 
     graph.lint();
 
@@ -164,7 +164,7 @@ void testFusion() {
                                          graph_string2};
   for (auto i = decltype(graph_strings.size()){0}; i < graph_strings.size(); ++i) {
     Graph g;
-    torch::jit::script::parseIR(graph_strings[i], &g);
+    torch::jit::parseIR(graph_strings[i], &g);
 
     auto outputs = debugLaunchGraph(g, {a, b});
     ASSERT_EQ(outputs.size(), 2);
@@ -187,7 +187,7 @@ void testRegisterFusionCachesKernel() {
       %d0 : Float(2, 3, 4) = aten::mul(%c0, %0)
       return (%d0))IR";
   auto g0 = std::make_shared<Graph>();
-  torch::jit::script::parseIR(graph0_string, g0.get());
+  torch::jit::parseIR(graph0_string, g0.get());
 
   const auto graph1_string = R"IR(
     graph(%0 : Float(2, 3, 4),
@@ -196,7 +196,7 @@ void testRegisterFusionCachesKernel() {
       %d1 : Float(2, 3, 4) = aten::mul(%c1, %0)
       return (%d1))IR";
   auto g1 = std::make_shared<Graph>();
-  torch::jit::script::parseIR(graph1_string, g1.get());
+  torch::jit::parseIR(graph1_string, g1.get());
 
   auto getFusionGroup = [](const std::shared_ptr<Graph>& graph) {
     const auto& nodes = graph->nodes();

test/cpp/jit/test_inliner.cpp

@@ -21,7 +21,6 @@ def foo3(x):
 
 namespace torch {
 namespace jit {
-using namespace script;
 using namespace testing;
 
 struct InlinerGuard {

test/cpp/jit/test_interface.cpp

@@ -11,8 +11,6 @@
 namespace torch {
 namespace jit {
 
-using namespace torch::jit::script;
-
 static const std::vector<std::string> subMethodSrcs = {R"JIT(
 def one(self, x: Tensor, y: Tensor) -> Tensor:
     return x + y + 1

test/cpp/jit/test_ir.cpp

@@ -55,7 +55,7 @@ void testBlocks() {
       %12 : int = prim::Constant[value=1]()
       %13 : Tensor = aten::add(%5, %3, %12)
       return (%13))IR";
-  torch::jit::script::parseIR(graph_string, g.get());
+  torch::jit::parseIR(graph_string, g.get());
 
   g->lint();
   testing::FileCheck()
@@ -122,7 +122,7 @@ graph(%x : Tensor,
 
   torch::jit::Graph g;
   std::unordered_map<std::string, torch::jit::Value*> name_to_value;
-  torch::jit::script::parseIR(input_str, &g, name_to_value);
+  torch::jit::parseIR(input_str, &g, name_to_value);
 
   std::vector<std::string> value_names{"6", "7", "9", "10"};
   std::unordered_set<std::string> value_names_set(

test/cpp/jit/test_irparser.cpp

@@ -17,7 +17,7 @@ namespace jit {
  */
 static void checkRoundtrip(const std::string& s) {
   auto graph = std::make_shared<Graph>();
-  script::parseIR(s, &*graph);
+  parseIR(s, &*graph);
   std::ostringstream ss;
   ss << *graph;
   std::string parsed = ss.str();
@@ -42,7 +42,7 @@ void testIRParser() {
   {
     auto graph = std::make_shared<Graph>();
     std::unordered_map<std::string, Value*> vmap;
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%0 : Tensor, %1 : Tensor):
   %2 : Tensor = foo::add(%0, %1)
@@ -117,7 +117,7 @@ graph(%0 : Tensor,
   }
   {
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%a):
   return (%a))IR",
@@ -127,7 +127,7 @@ graph(%a):
   {
     // Check that parser correctly handles values reusing the same name.
     auto graph = std::make_shared<Graph>();
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%x):
   %x = a::a(%x)
@@ -239,7 +239,7 @@ graph(%0 : Tensor,
     # CHECK: return
       return (%a))IR";
 
-    script::parseIR(text, &*graph);
+    parseIR(text, &*graph);
     AT_ASSERT(graph->inputs()[0]->type()->isSubtypeOf(TensorType::get()));
     torch::jit::testing::FileCheck().run(text, *graph);
   }

test/cpp/jit/test_ivalue.cpp

@@ -7,8 +7,6 @@
 namespace torch {
 namespace jit {
 
-using namespace torch::jit::script;
-
 void testIValue() {
   c10::List<int64_t> foo({3, 4, 5});
   ASSERT_EQ(foo.use_count(), 1);

test/cpp/jit/test_lite_interpreter.cpp

@@ -12,7 +12,7 @@ namespace torch {
 namespace jit {
 
 void testLiteInterpreterUpsampleNearest2d() {
-  script::Module m("m");
+  Module m("m");
   m.define(R"(
     def forward(self, input: Tensor, scale:float):
       return torch.upsample_nearest2d(input, [1, 1], float(scale), float(scale))
@@ -35,7 +35,7 @@ void testLiteInterpreterUpsampleNearest2d() {
 }
 
 void testLiteInterpreterAdd() {
-  script::Module m("m");
+  Module m("m");
   m.register_parameter("foo", torch::ones({}), false);
   // TODO: support default param val, which was pushed in
   // function schema's checkAndNormalizeInputs()
@@ -75,7 +75,7 @@ void testLiteInterpreterConv() {
 
   std::vector<torch::jit::IValue> inputs;
 
-  script::Module m("m");
+  Module m("m");
   m.register_parameter("weight", torch::ones({20, 1, 5, 5}), false);
   m.register_parameter("bias", torch::ones({20}), false);
   m.define(R"(
@@ -100,7 +100,7 @@ void testLiteInterpreterConv() {
 }
 
 void testLiteInterpreterInline() {
-  script::Module m("m");
+  Module m("m");
   m.define(R"JIT(
   def foo1(self, x):
       return x + 1
@@ -120,7 +120,7 @@ void testLiteInterpreterInline() {
 }
 
 void testLiteInterpreterTuple() {
-  script::Module m("m");
+  Module m("m");
   m.define(R"JIT(
   def foo(self, x):
       return (1, 2, x + 3)
@@ -138,7 +138,7 @@ void testLiteInterpreterTuple() {
 }
 
 void testLiteInterpreterPrimOverload() {
-  script::Module m("m");
+  Module m("m");
   m.define(R"JIT(
   def forward(self, x):
       result = [1, 2]
@@ -154,7 +154,7 @@ void testLiteInterpreterPrimOverload() {
 }
 
 void testLiteInterpreterPrim() {
-  script::Module m("m");
+  Module m("m");
   m.define(R"JIT(
         def forward(self, x):
             return int(x)
@@ -180,7 +180,7 @@ void testLiteInterpreterPrim() {
 }
 
 void testLiteInterpreterLoadOrigJit() {
-  script::Module m("m");
+  Module m("m");
   m.register_parameter("foo", torch::ones({}), false);
   m.define(R"(
     def forward(self, x):
@@ -193,7 +193,7 @@ void testLiteInterpreterLoadOrigJit() {
 }
 
 void testLiteInterpreterWrongMethodName() {
-  script::Module m("m");
+  Module m("m");
   m.register_parameter("foo", torch::ones({}), false);
   m.define(R"(
     def add(self, x):
@@ -210,7 +210,7 @@ void testLiteInterpreterWrongMethodName() {
 }
 
 void testLiteInterpreterParams() {
-  script::Module m("m");
+  Module m("m");
   m.register_parameter("foo", torch::ones({1}, at::requires_grad()), false);
   m.define(R"(
     def forward(self, x):
@@ -269,7 +269,7 @@ void testLiteInterpreterParams() {
 }
 
 void testLiteInterpreterSetState() {
-  script::Module m("m");
+  Module m("m");
   m.register_parameter("foo", torch::ones({}), false);
   m.define(R"(
     def __getstate__(self):

test/cpp/jit/test_misc.cpp

@@ -368,7 +368,7 @@ void testCustomFusion() {
       %3 : Tensor = aten::mul(%2, %0)
       return (%3))IR";
   auto g = std::make_shared<Graph>();
-  torch::jit::script::parseIR(graph_string, g.get());
+  torch::jit::parseIR(graph_string, g.get());
 
   torch::jit::overrideCanFuseOnCPU(true);
   CustomFuseGraph(
@@ -412,7 +412,7 @@ void testCustomFusionNestedBlocks() {
     %9 : Tensor = aten::add(%4, %2, %3)
     return (%4))IR";
   auto g = std::make_shared<Graph>();
-  torch::jit::script::parseIR(graph_string, g.get());
+  torch::jit::parseIR(graph_string, g.get());
 
   CustomFuseGraph(
       g,
@@ -489,7 +489,7 @@ void testEvalModeForLoadedModule() {
   if (isSandcastle())
     return; // The module file to load is not generated in Sandcastle
   std::string module_path = "dropout_model.pt";
-  torch::jit::script::Module module = torch::jit::load(module_path);
+  torch::jit::Module module = torch::jit::load(module_path);
   AT_ASSERT(module.attr("dropout").toModule().is_training());
   module.eval();
   AT_ASSERT(!module.attr("dropout").toModule().is_training());
@@ -973,7 +973,7 @@ void testNoneSchemaMatch() {
 }
 
 void testModuleDefine() {
-  script::Module m("m");
+  Module m("m");
   m.register_parameter("foo", torch::ones({}), false);
   m.define(R"(
     def add_it(self, x, b : int = 4):
@@ -984,7 +984,7 @@ void testModuleDefine() {
 }
 
 void testModuleConversion() {
-  script::Module m("test");
+  Module m("test");
   {
     // test cuda to cpu for params and buffers
     m.register_parameter("foo", torch::ones({}, at::kCUDA), false);
@@ -1016,7 +1016,7 @@ RegisterPass p(fakePass);
 
 void testPassManagement() {
   std::shared_ptr<Graph> graph = std::make_shared<Graph>();
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%a):
   return (%a))IR",

test/cpp/jit/test_module_api.cpp

@@ -5,8 +5,6 @@
 namespace torch {
 namespace jit {
 
-using namespace torch::jit::script;
-
 void testModuleClone() {
   auto cu = std::make_shared<CompilationUnit>();
   auto parent = ClassType::create("parent", cu, true);

test/cpp/jit/test_peephole_optimize.cpp

@@ -8,8 +8,6 @@
 namespace torch {
 namespace jit {
 
-using namespace script;
-
 
 void testPeepholeOptimize() {
   // test is / is not none optimization

test/cpp/jit/test_save_load.cpp

@@ -10,7 +10,6 @@
 
 namespace torch {
 namespace jit {
-using namespace script;
 
 void testSaveExtraFilesHook() {
   // no secrets

test/cpp/jit/test_schema_matching.cpp

@@ -23,7 +23,7 @@ void testSchemaMatching() {
                 return 0;
             }, c10::AliasAnalysisKind::FROM_SCHEMA),
     });
-    script::Module m("m");
+    Module m("m");
     m.define(R"(
       def test(self):
         a = (1.0, 2.0)
@@ -59,7 +59,7 @@ void testSchemaMatching() {
               return 0;
             }, AliasAnalysisKind::FROM_SCHEMA),
     });
-    script::Module m("m");
+    Module m("m");
     m.define(R"JIT(
       def test(self):
           a = (1.0, 2.0)

test/cpp/jit/test_subgraph_matcher.cpp

@@ -7,13 +7,13 @@ namespace jit {
 
 void testTrivial1() {
   Graph graph, pattern;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %a = a::aaa(%0)
   return (%a))IR",
       &graph);
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %x = a::aaa(%0)
@@ -46,7 +46,7 @@ void testTrivial2() {
 
 void testTrivial3() {
   Graph graph, pattern;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %a = a::a(%0)
@@ -54,7 +54,7 @@ graph(%0):
   %c = a::c(%a, %b)
   return (%c))IR",
       &graph);
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%a, %b):
   %c = a::c(%a, %b)
@@ -92,7 +92,7 @@ void testTrivial4() {
 
 void testLinear1() {
   Graph graph, pattern;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %a = a::aaa(%0)
@@ -102,7 +102,7 @@ graph(%0):
   %a = a::aaa(%0)
   return (%d))IR",
       &graph);
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %x = b::bbb(%0)
@@ -161,7 +161,7 @@ void testLinear2() {
  */
 void testDiamond1() {
   Graph graph, pattern1, pattern2;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %o = o::ooo(%0)
@@ -173,7 +173,7 @@ graph(%0):
   return (%e))IR",
       &graph);
 
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %a = a::aaa(%0)
@@ -185,7 +185,7 @@ graph(%0):
   AT_ASSERT(!findPatternMatches(pattern1, graph).empty());
 
   // Check that order of nodes inside the diamond does not affect the result
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %a = a::aaa(%0)
@@ -247,7 +247,7 @@ void testDiamond2() {
 
 void testXPattern() {
   Graph graph, pattern;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0, %1):
   %b = b::bbb(%0)
@@ -258,7 +258,7 @@ graph(%0, %1):
   %g = g::ggg(%e, %f)
   return (%g))IR",
       &graph);
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0, %1):
   %b = b::bbb(%0)
@@ -274,7 +274,7 @@ graph(%0, %1):
 
 void testMultipleMatches() {
   Graph graph, pattern;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%t0):
   %t1 = a::aaa(%t0)
@@ -283,7 +283,7 @@ graph(%t0):
   %t4 = a::aaa(%t3)
   return (%t4))IR",
       &graph);
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%t0):
   %t1 = a::aaa(%t0)
@@ -295,7 +295,7 @@ graph(%t0):
 
 void testOverlappingMatches() {
   Graph graph, pattern;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%t0):
   %t1 = a::aaa(%t0)
@@ -304,7 +304,7 @@ graph(%t0):
   %t4 = a::aaa(%t3)
   return (%t4))IR",
       &graph);
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%t0):
   %t1 = a::aaa(%t0)
@@ -317,7 +317,7 @@ graph(%t0):
 
 void testMatchInBasicBlocks1() {
   Graph graph;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%a, %b, %c):
   %d = aten::mul(%a, %b)
@@ -333,7 +333,7 @@ graph(%a, %b, %c):
 
   // Ensure the matches don't cross basic block boundaries
   Graph pattern0;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%x, %y):
   %z = aten::mul(%x, %y)
@@ -342,7 +342,7 @@ graph(%x, %y):
   AT_ASSERT(findPatternMatches(pattern0, graph).size() == 3);
 
   Graph pattern1;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%x, %y):
   %z1 = aten::mul(%x, %y)
@@ -354,7 +354,7 @@ graph(%x, %y):
 
 void testMatchInBasicBlocks2() {
   Graph graph;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%a, %b):
   %x = my::mul(%a, %b)
@@ -367,7 +367,7 @@ graph(%a, %b):
 
   // Check that we can match both mul ops
   Graph pattern0;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%x, %y):
   %z = my::mul(%x, %y)
@@ -377,7 +377,7 @@ graph(%x, %y):
 
   // Ensure the matches don't cross basic block boundaries
   Graph pattern1;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%x, %y):
   %u = my::mul(%x, %y)
@@ -389,7 +389,7 @@ graph(%x, %y):
 
 void testMatchesAttributes() {
   Graph graph;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %a = a::a[isattr=[1,2]](%0)
@@ -400,7 +400,7 @@ graph(%0):
 
   {
     Graph pattern;
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%a, %b):
   %c = a::c[myattr="qqq"](%a, %b)
@@ -410,7 +410,7 @@ graph(%a, %b):
   }
   {
     Graph pattern;
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%a, %b):
   %c = a::c[myattr="zzz"](%a, %b)
@@ -420,7 +420,7 @@ graph(%a, %b):
   }
   {
     Graph pattern;
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%0):
   %b = a::b[extraattr=10](%0)
@@ -430,7 +430,7 @@ graph(%0):
   }
   {
     Graph pattern;
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%0):
   %b = a::b[intattr=10, floatattr=3.14](%0)
@@ -440,7 +440,7 @@ graph(%0):
   }
   {
     Graph pattern;
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%0):
   %b = a::b[intattr=10, floatattr=3.14, strattr="rrr"](%0)
@@ -450,7 +450,7 @@ graph(%0):
   }
   {
     Graph pattern;
-    script::parseIR(
+    parseIR(
         R"IR(
 graph(%0):
   %a = a::a[isattr=[1,2]](%0)
@@ -463,14 +463,14 @@ graph(%0):
 
 void testBadPattern() {
   Graph graph, pattern1, pattern2;
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %a = a::aaa(%0)
   return (%a))IR",
       &graph);
 
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%x):
   %y = my::node_with_subblock()
@@ -481,7 +481,7 @@ graph(%x):
       &pattern1);
   ASSERT_ANY_THROW(findPatternMatches(pattern1, graph));
 
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%x):
   %y = my::op1(%x)

test/cpp/jit/test_subgraph_rewriter.cpp

@@ -11,7 +11,7 @@ using namespace testing;
 void testFilterMatch() {
   auto graph = std::make_shared<Graph>();
 
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %a = a::aaa(%0)
@@ -27,7 +27,7 @@ graph(%a, %b):
   Graph pattern_graph;
   std::unordered_map<std::string, Value*> vmap;
 
-  script::parseIR(
+  parseIR(
       pattern,
       &pattern_graph,
       vmap);
@@ -55,7 +55,7 @@ graph(%a, %b):
 
 void testFilterNoMatch() {
   auto graph = std::make_shared<Graph>();
-  script::parseIR(
+  parseIR(
       R"IR(
 graph(%0):
   %a = a::aaa(%0)
@@ -71,7 +71,7 @@ graph(%a, %b):
   Graph pattern_graph;
   std::unordered_map<std::string, Value*> vmap;
 
-  script::parseIR(
+  parseIR(
       pattern,
       &pattern_graph,
       vmap);

test/cpp/jit/test_utils.cpp

@@ -84,7 +84,7 @@ std::shared_ptr<Graph> build_lstm() {
       %22 : Tensor = aten::mul(%14, %21)
       return (%22, %20))IR";
   auto g = std::make_shared<Graph>();
-  torch::jit::script::parseIR(graph_string, g.get());
+  torch::jit::parseIR(graph_string, g.get());
   g->lint();
 
   return g;

test/custom_operator/test_custom_ops.cpp

@@ -12,7 +12,7 @@
 namespace helpers {
 template <typename Predicate>
 void check_all_parameters(
-    const torch::jit::script::Module& module,
+    const torch::jit::Module& module,
     Predicate predicate) {
   for (at::Tensor parameter : module.parameters()) {
     AT_ASSERT(predicate(parameter));
@@ -79,7 +79,7 @@ void get_autograd_operator_from_registry_and_execute_in_nograd_mode() {
 
 void load_serialized_module_with_custom_op_and_execute(
     const std::string& path_to_exported_script_module) {
-  torch::jit::script::Module module =
+  torch::jit::Module module =
       torch::jit::load(path_to_exported_script_module);
   std::vector<torch::jit::IValue> inputs;
   inputs.push_back(torch::ones(5));
@@ -90,7 +90,7 @@ void load_serialized_module_with_custom_op_and_execute(
 
 void test_argument_checking_for_serialized_modules(
     const std::string& path_to_exported_script_module) {
-  torch::jit::script::Module module =
+  torch::jit::Module module =
       torch::jit::load(path_to_exported_script_module);
 
   try {
@@ -124,7 +124,7 @@ void test_argument_checking_for_serialized_modules(
 }
 
 void test_move_to_device(const std::string& path_to_exported_script_module) {
-  torch::jit::script::Module module =
+  torch::jit::Module module =
       torch::jit::load(path_to_exported_script_module);
 
   helpers::check_all_parameters(module, [](const torch::Tensor& tensor) {
@@ -145,7 +145,7 @@ void test_move_to_device(const std::string& path_to_exported_script_module) {
 }
 
 void test_move_to_dtype(const std::string& path_to_exported_script_module) {
-  torch::jit::script::Module module =
+  torch::jit::Module module =
       torch::jit::load(path_to_exported_script_module);
 
   module.to(torch::kInt);

test/mobile/custom_build/predictor.cpp

@@ -24,7 +24,7 @@ struct MobileCallGuard {
   torch::jit::GraphOptimizerEnabledGuard no_optimizer_guard{false};
 };
 
-torch::jit::script::Module loadModel(const std::string& path) {
+torch::jit::Module loadModel(const std::string& path) {
   MobileCallGuard guard;
   auto module = torch::jit::load(path);
   module.eval();

test/test_cpp_api_parity.py

@@ -138,7 +138,7 @@ TORCH_NN_MODULE_TEST_INIT = Template("""\n
 void ${module_variant_name}_test_init(
     const std::string& saved_module_path,
     const std::string& device) {
-  torch::jit::script::Module m_init_by_python = torch::jit::load(saved_module_path);
+  torch::jit::Module m_init_by_python = torch::jit::load(saved_module_path);
 
   torch::manual_seed(2);
   ${module_qualified_name} m_init_by_cpp${cpp_constructor_args};

torch/csrc/api/include/torch/jit.h

@@ -30,7 +30,7 @@ namespace jit {
 ///   )JIT");
 ///   IValue output = module->run_method("relu_script", a, b);
 /// \endrst
-TORCH_API std::shared_ptr<script::CompilationUnit> compile(const std::string& source);
+TORCH_API std::shared_ptr<CompilationUnit> compile(const std::string& source);
 
 } // namespace jit
 } // namespace torch

torch/csrc/api/include/torch/serialize.h

@@ -39,7 +39,7 @@ namespace torch {
 template <typename Value, typename... SaveToArgs>
 void save(const Value& value, SaveToArgs&&... args) {
   serialize::OutputArchive archive(
-      std::make_shared<jit::script::CompilationUnit>());
+      std::make_shared<jit::CompilationUnit>());
   archive << value;
   archive.save_to(std::forward<SaveToArgs>(args)...);
 }
@@ -65,7 +65,7 @@ void save(const Value& value, SaveToArgs&&... args) {
 template <typename... SaveToArgs>
 void save(const std::vector<torch::Tensor>& tensor_vec, SaveToArgs&&... args) {
   serialize::OutputArchive archive(
-      std::make_shared<jit::script::CompilationUnit>());
+      std::make_shared<jit::CompilationUnit>());
   for (size_t i = 0; i < tensor_vec.size(); i++) {
     auto& value = tensor_vec[i];
     archive.write(c10::to_string(i), value);

torch/csrc/api/include/torch/serialize/input-archive.h

@@ -18,9 +18,7 @@ class Tensor;
 namespace torch {
 using at::Tensor;
 namespace jit {
-namespace script {
 struct Module;
-} // namespace script
 } // namespace jit
 } // namespace torch
 
@@ -108,7 +106,7 @@ class TORCH_API InputArchive final {
   }
 
  private:
-  jit::script::Module module_;
+  jit::Module module_;
   std::string hierarchy_prefix_;
 };
 } // namespace serialize

torch/csrc/api/include/torch/serialize/output-archive.h

@@ -15,9 +15,7 @@ class Tensor;
 namespace torch {
 using at::Tensor;
 namespace jit {
-namespace script {
 struct Module;
-} // namespace script
 } // namespace jit
 } // namespace torch
 
@@ -25,8 +23,8 @@ namespace torch {
 namespace serialize {
 class TORCH_API OutputArchive final {
  public:
-  explicit OutputArchive(std::shared_ptr<jit::script::CompilationUnit> cu);
+  explicit OutputArchive(std::shared_ptr<jit::CompilationUnit> cu);
-  explicit OutputArchive() : cu_(std::make_shared<jit::script::CompilationUnit>()), module_("__torch__.Module", cu_) {}
+  explicit OutputArchive() : cu_(std::make_shared<jit::CompilationUnit>()), module_("__torch__.Module", cu_) {}
 
   // Move is allowed.
   OutputArchive(OutputArchive&&) = default;
@@ -36,7 +34,7 @@ class TORCH_API OutputArchive final {
   OutputArchive(OutputArchive&) = delete;
   OutputArchive& operator=(OutputArchive&) = delete;
 
-  std::shared_ptr<jit::script::CompilationUnit> compilation_unit() const {
+  std::shared_ptr<jit::CompilationUnit> compilation_unit() const {
     return cu_;
   }
 
@@ -75,8 +73,8 @@ class TORCH_API OutputArchive final {
   }
 
  private:
-  std::shared_ptr<jit::script::CompilationUnit> cu_;
+  std::shared_ptr<jit::CompilationUnit> cu_;
-  jit::script::Module module_;
+  jit::Module module_;
 };
 } // namespace serialize
 } // namespace torch

torch/csrc/api/src/jit.cpp

@@ -9,12 +9,12 @@
 namespace torch {
 namespace jit {
 
-std::shared_ptr<script::CompilationUnit> compile(const std::string& source) {
+std::shared_ptr<CompilationUnit> compile(const std::string& source) {
-  auto module = std::make_shared<script::CompilationUnit>();
+  auto module = std::make_shared<CompilationUnit>();
   module->define(
       c10::nullopt,
       source,
-      script::nativeResolver(),
+      nativeResolver(),
       nullptr);
   return module;
 }

torch/csrc/api/src/serialize/input-archive.cpp

@@ -16,7 +16,7 @@
 namespace torch {
 namespace serialize {
 
-InputArchive::InputArchive() : module_("Module", std::make_shared<jit::script::CompilationUnit>()) {}
+InputArchive::InputArchive() : module_("Module", std::make_shared<jit::CompilationUnit>()) {}
 
 void InputArchive::read(const std::string& key, c10::IValue& ivalue) {
   ivalue = module_.attr(key);
@@ -161,7 +161,7 @@ std::vector<std::string> InputArchive::keys() {
   std::vector<std::string> all_keys;
   all_keys.reserve(module_.named_attributes(/*recurse=*/false).size());
 
-  for (const torch::jit::script::NameValue& s : module_.named_attributes(/*recurse=*/false)) {
+  for (const torch::jit::NameValue& s : module_.named_attributes(/*recurse=*/false)) {
     all_keys.push_back(s.name);
   }
 

torch/csrc/api/src/serialize/output-archive.cpp

@@ -14,7 +14,7 @@
 
 namespace torch {
 namespace serialize {
-OutputArchive::OutputArchive(std::shared_ptr<jit::script::CompilationUnit> cu)
+OutputArchive::OutputArchive(std::shared_ptr<jit::CompilationUnit> cu)
     : cu_(std::move(cu)),
       module_("__torch__.Module", cu_, /*shouldMangle=*/true) {}
 

torch/csrc/distributed/rpc/py_rref.cpp

@@ -53,7 +53,7 @@ TypePtr tryInferTypeWithTypeHint(
     const py::object& type_hint) {
   // If the py::object to be contained by the RRef is a ScripModule, we enforce
   // users to specify its ModuleInterface type.
-  if (auto module = jit::script::as_module(value)) {
+  if (auto module = jit::as_module(value)) {
     TORCH_CHECK(
         !type_hint.is_none(),
         "The RRef being created contains a ScriptModule, "

torch/csrc/distributed/rpc/python_rpc_handler.cpp

@@ -27,8 +27,8 @@ namespace {
 
 // PythonTypeResolver that inherits from Script::Resolver to
 // support resolving types together with ScriptTypeParser.
-struct PythonTypeResolver : public jit::script::Resolver {
+struct PythonTypeResolver : public jit::Resolver {
-  std::shared_ptr<jit::script::SugaredValue> resolveValue(
+  std::shared_ptr<jit::SugaredValue> resolveValue(
       const std::string& /* unused */,
       torch::jit::Function& /* unused */,
       const jit::SourceRange& /* unused */) override {
@@ -67,7 +67,7 @@ PythonRpcHandler::PythonRpcHandler() {
   pyHandleException_ = getFunction(module, "_handle_exception");
   pyGetQualifiedName_ = py::module::import("torch.jit").attr("_qualified_name");
   jitCompilationUnit_ = torch::jit::get_python_cu();
-  typeParser_ = std::make_shared<jit::script::ScriptTypeParser>(
+  typeParser_ = std::make_shared<jit::ScriptTypeParser>(
       std::make_shared<PythonTypeResolver>());
 }
 
@@ -97,7 +97,7 @@ PythonRpcHandler& PythonRpcHandler::getInstance() {
   return *handler;
 }
 
-std::shared_ptr<torch::jit::script::CompilationUnit> PythonRpcHandler::
+std::shared_ptr<torch::jit::CompilationUnit> PythonRpcHandler::
     jitCompilationUnit() {
   return jitCompilationUnit_;
 }

torch/csrc/distributed/rpc/python_rpc_handler.h

@@ -55,7 +55,7 @@ class PYBIND11_EXPORT PythonRpcHandler {
   // PythonRpcHandler.
   void cleanup();
 
-  std::shared_ptr<torch::jit::script::CompilationUnit> jitCompilationUnit();
+  std::shared_ptr<torch::jit::CompilationUnit> jitCompilationUnit();
 
   // Parse the string to recover the jit_type, this is used for RRef python
   // pickling/unpickling type recovery. The type string inference rule is as
@@ -97,11 +97,11 @@ class PYBIND11_EXPORT PythonRpcHandler {
   // and imported in C++ (see get_python_cu() in
   // csrc/jit/python/pybind_utils.h). We import the compilation unit here only
   // once for less cost and thread safety.
-  std::shared_ptr<torch::jit::script::CompilationUnit> jitCompilationUnit_;
+  std::shared_ptr<torch::jit::CompilationUnit> jitCompilationUnit_;
 
   // jit type parser to parse type_str back to TypePtr for RRef type
   // recovery when pickling and unpickling RRef
-  std::shared_ptr<jit::script::ScriptTypeParser> typeParser_;
+  std::shared_ptr<jit::ScriptTypeParser> typeParser_;
 };
 
 } // namespace rpc

torch/csrc/jit/api/compilation_unit.h

@@ -24,7 +24,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 struct Def;
 struct ClassDef;
@@ -281,22 +280,25 @@ struct TORCH_API CompilationUnit {
   mutable size_t mangleIndex_ = 0;
 };
 
-} // namespace script
-
 // An owning pointer to a Function. Just a pair of a raw Function ptr and it's
 // owning CU. We need this because pybind requires a ref-counted way to refer to
 // Functions.
 struct StrongFunctionPtr {
   StrongFunctionPtr(
-      std::shared_ptr<script::CompilationUnit> cu,
+      std::shared_ptr<CompilationUnit> cu,
       Function* function)
       : cu_(std::move(cu)), function_(function) {
     TORCH_INTERNAL_ASSERT(cu_);
     TORCH_INTERNAL_ASSERT(function_);
   }
-  std::shared_ptr<script::CompilationUnit> cu_;
+  std::shared_ptr<CompilationUnit> cu_;
   Function* function_;
 };
 
+namespace script {
+// We once had a `script::` namespace that was deleted. This is for backcompat
+// of the public API; new code should not use this type alias.
+using CompilationUnit = ::torch::jit::CompilationUnit;
+}
 } // namespace jit
 } // namespace torch

torch/csrc/jit/api/method.h

@@ -6,7 +6,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 using ObjectPtr = c10::intrusive_ptr<c10::ivalue::Object>;
 
@@ -61,6 +60,11 @@ struct TORCH_API Method {
   Function* function_;
 };
 
-} // namespace script
+namespace script {
+// We once had a `script::` namespace that was deleted. This is for backcompat
+// of the public API; new code should not use this type alias.
+using Method = ::torch::jit::Method;
+}
+
 } // namespace jit
 } // namespace torch

torch/csrc/jit/api/module.cpp

@@ -11,7 +11,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 static ObjectPtr create_module_object(
     c10::QualifiedName class_name,
@@ -389,14 +388,13 @@ void Module::dump(
             << std::endl;
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch
 
 namespace c10 {
 
-torch::jit::script::Module IValue::toModule() const {
+torch::jit::Module IValue::toModule() const {
-  return torch::jit::script::Module(toObject());
+  return torch::jit::Module(toObject());
 }
 bool IValue::isModule() const {
   return isObject() && toObjectRef().type()->is_module();

torch/csrc/jit/api/module.h

@@ -33,7 +33,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 using ::c10::Argument;
 using ::c10::FunctionSchema;
@@ -554,6 +553,11 @@ struct NamedPolicy {
 
 TORCH_API bool& getInlineEverythingMode();
 
-} // namespace script
+namespace script {
+// We once had a `script::` namespace that was deleted. This is for backcompat
+// of the public API; new code should not use this type alias.
+using Module = ::torch::jit::Module;
+}
+
 } // namespace jit
 } // namespace torch

torch/csrc/jit/api/module_save.cpp

@@ -3,7 +3,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 void Module::save(std::ostream& out, const ExtraFilesMap& extra_files) const {
   ExportModule(*this, out, extra_files, false);
@@ -26,6 +25,5 @@ void Module::_save_for_mobile(
   ExportModule(*this, filename, extra_files, true);
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/api/object.cpp

@@ -7,7 +7,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 Object::Object(
     std::shared_ptr<CompilationUnit> cu,
@@ -35,10 +34,9 @@ void Object::define(const std::string& src, const ResolverPtr& resolver) {
   _ivalue()->compilation_unit()->define(
       *type()->name(),
       src,
-      resolver ? resolver : script::nativeResolver(),
+      resolver ? resolver : nativeResolver(),
       &self);
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/api/object.h

@@ -6,7 +6,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 struct Resolver;
 using ResolverPtr = std::shared_ptr<Resolver>;
@@ -132,6 +131,10 @@ struct TORCH_API Object {
   mutable ObjectPtr _ivalue_;
 };
 
-} // namespace script
+namespace script {
+// We once had a `script::` namespace that was deleted. This is for backcompat
+// of the public API; new code should not use this type alias.
+using Object = ::torch::jit::Object;
+}
 } // namespace jit
 } // namespace torch

torch/csrc/jit/docs/serialization.md

@@ -285,7 +285,7 @@ The load process has the following steps:
 
 1. Unpickle `constants.pkl`, which produces a tuple of all tensor constants
    referenced in code.
-2. Unpickle `data.pkl` into the top-level `script::Module` and return it.
+2. Unpickle `data.pkl` into the top-level `Module` and return it.
 
 The unpickling process consists of a single call to unpickle the module
 object contained in `data.pkl`. The `Unpickler` is given a callback that lets it

torch/csrc/jit/frontend/builtin_functions.cpp

@@ -5,7 +5,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 auto scalar_operators_source = CodeTemplate(
     R"SCRIPT(
@@ -81,7 +80,7 @@ struct BuiltinFunctionRegistry {
     std::shared_ptr<CompilationUnit> cu = std::make_shared<CompilationUnit>();
     modules.emplace_back(cu);
     cu->define(
-        c10::nullopt, source, script::nativeResolver(), /*self=*/nullptr);
+        c10::nullopt, source, nativeResolver(), /*self=*/nullptr);
     for (auto& method : cu->get_functions()) {
       builtins_by_name_[Symbol::fromQualString(
                             the_namespace + "::" + method->name())]
@@ -134,6 +133,5 @@ const std::vector<Function*>& getAllBuiltinFunctionsFor(
   return registry.getAllBuiltinFunctionsFor(name);
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/builtin_functions.h

@@ -5,9 +5,7 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 TORCH_API const std::vector<Function*>& getAllBuiltinFunctionsFor(Symbol name);
-}
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/concrete_module_type.cpp

@@ -3,7 +3,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 ClassTypePtr ConcreteModuleTypeBuilder::createTypeFromThis() const {
   auto cu = get_python_cu();
@@ -303,6 +302,5 @@ ConcreteModuleType::getModulesPy() const {
   return ret;
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/concrete_module_type.h

@@ -9,7 +9,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 enum class IterableModuleKind { NONE, LIST, DICT };
 class ConcreteModuleType;
@@ -228,6 +227,5 @@ class VISIBILITY_HIDDEN ConcreteModuleType {
   TypePtr jitType_;
 };
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/convert_to_ssa.cpp

@@ -9,7 +9,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 // At the beginning of the pass the Graph has already undergone type checking,
 // and writes or reads to a variable are emitted as Loads and Stores in the
@@ -328,6 +327,5 @@ void ConvertToSSA(std::shared_ptr<Graph>& graph) {
   TransformExits(graph);
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/convert_to_ssa.h

@@ -8,11 +8,9 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 // Convert a graph with Loads & Stores into SSA form
 TORCH_API void ConvertToSSA(std::shared_ptr<Graph>& graph);
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/edit_distance.cpp

@@ -5,7 +5,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 // computes levenshtein edit distance between two words
 // returns maxEditDistance + 1 if the edit distance exceeds MaxEditDistance
@@ -52,6 +51,5 @@ size_t ComputeEditDistance(
   return result;
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/edit_distance.h

@@ -5,13 +5,11 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 TORCH_API size_t ComputeEditDistance(
     const char* word1,
     const char* word2,
     size_t maxEditDistance);
 
-}
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/error_report.cpp

@@ -5,7 +5,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 // Avoid storing objects with destructor in thread_local for mobile build.
 #ifndef C10_MOBILE
@@ -72,6 +71,5 @@ const char* ErrorReport::what() const noexcept {
   return the_message.c_str();
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/error_report.h

@@ -5,7 +5,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 struct Call {
   std::string fn_name;
@@ -49,6 +48,5 @@ const ErrorReport& operator<<(const ErrorReport& e, const T& t) {
   return e;
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/function_schema_parser.cpp

@@ -22,7 +22,6 @@ using at::TypeKind;
 namespace torch {
 namespace jit {
 
-namespace script {
 namespace {
 struct SchemaParser {
   SchemaParser(const std::string& str)
@@ -290,10 +289,9 @@ struct SchemaParser {
   SchemaTypeParser type_parser;
 };
 } // namespace
-} // namespace script
 
 C10_EXPORT either<OperatorName, FunctionSchema> parseSchemaOrName(const std::string& schemaOrName) {
-  return script::SchemaParser(schemaOrName).parseDeclarations().at(0);
+  return SchemaParser(schemaOrName).parseDeclarations().at(0);
 }
 
 C10_EXPORT FunctionSchema parseSchema(const std::string& schema) {

torch/csrc/jit/frontend/ir_emitter.cpp

@@ -30,7 +30,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 using FunctionTable = std::unordered_map<std::string, Function&>;
 using ValueTable = std::unordered_map<std::string, SugaredValuePtr>;
@@ -491,7 +490,7 @@ struct Environment {
     if (!retval) {
       if (auto type = resolver->resolveType(ident, range)) {
         if (auto tuple_type = type->cast<TupleType>()) {
-          retval = std::make_shared<script::NamedTupleConstructor>(tuple_type);
+          retval = std::make_shared<NamedTupleConstructor>(tuple_type);
         }
       }
     }
@@ -503,7 +502,7 @@ struct Environment {
     if (!retval) {
       if (auto type = resolver->resolveType(ident, range)) {
         if (auto class_type = type->cast<ClassType>()) {
-          retval = std::make_shared<script::ClassValue>(class_type);
+          retval = std::make_shared<ClassValue>(class_type);
         }
       }
     }
@@ -3598,7 +3597,7 @@ std::vector<Function*> CompilationUnit::define(
 void runCleanupPasses(std::shared_ptr<Graph>& to_clean) {
   liftClosures(to_clean);
   inlineForkedClosures(to_clean);
-  if (script::getInlineEverythingMode()) {
+  if (getInlineEverythingMode()) {
     Inline(*to_clean);
   }
   // remove any uses of tuples that we inserted that are not needed
@@ -3669,6 +3668,5 @@ void CompilationUnit::define_interface(
   this->register_type(iface);
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/ir_emitter.h

@@ -12,12 +12,10 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 TORCH_API void runCleanupPasses(std::shared_ptr<Graph>& to_clean);
 
 TORCH_API bool meaningfulName(const std::string& name);
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/lexer.cpp

@@ -8,7 +8,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 static const std::unordered_map<int, int> binary_prec = {
     {TK_IF, 1},
@@ -101,6 +100,5 @@ C10_EXPORT SharedParserData& sharedParserData() {
   return data;
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/lexer.h

@@ -16,7 +16,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 // single character tokens are just the character itself '+'
 // multi-character tokens need an entry here
@@ -180,7 +179,7 @@ struct CAFFE2_API SharedParserData {
       return false;
     const char* startptr = str.c_str() + start;
     char* endptr;
-    torch::jit::script::strtod_c(startptr, &endptr);
+    torch::jit::strtod_c(startptr, &endptr);
     *len = endptr - startptr;
     return *len > 0;
   }
@@ -515,6 +514,5 @@ struct Lexer {
   std::vector<Token> next_tokens;
   SharedParserData& shared;
 };
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/mini_environment.h

@@ -5,7 +5,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 // Simple data structure for containing a type T in nested control blocks
 // Should only be used after initial compilation where type checking and
@@ -52,6 +51,5 @@ struct MiniEnvironment {
   std::unordered_map<std::string, T> table;
 };
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/parse_string_literal.h

@@ -5,7 +5,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 inline bool isCharCount(char c, const std::string& str, size_t start, int len) {
   // count checks from [start, start + len)
@@ -87,6 +86,5 @@ inline std::string parseStringLiteral(
   return ret_str;
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/parser.cpp

@@ -7,7 +7,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 Decl mergeTypesFromTypeComment(
     const Decl& decl,
@@ -735,6 +734,5 @@ Expr Parser::parseExp() {
   return pImpl->parseExp();
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/parser.h

@@ -6,7 +6,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 struct Decl;
 struct ParserImpl;
@@ -30,6 +29,5 @@ struct TORCH_API Parser {
   std::unique_ptr<ParserImpl> pImpl;
 };
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/parser_constants.h

@@ -2,8 +2,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 static const char* valid_single_char_tokens = "+-*/%@()[]:,={}><.?!&^|~";
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/resolver.h

@@ -6,7 +6,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 struct Resolver;
 using ResolverPtr = std::shared_ptr<Resolver>;
@@ -65,6 +64,5 @@ struct NativeResolver : public Resolver {
 inline std::shared_ptr<NativeResolver> nativeResolver() {
   return std::make_shared<NativeResolver>();
 }
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/schema_matching.cpp

@@ -6,7 +6,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 static inline TypePtr unwrapOptional(TypePtr opt_type) {
   if (auto unwrap_list_type = opt_type->cast<OptionalType>()) {
@@ -612,6 +611,5 @@ Value* emitBuiltinCall(
   }
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/schema_matching.h

@@ -7,7 +7,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 // try to match a list if inputs and keyword 'attributes' to this schema,
 // if it works return the flat list of positional inputs to the call
@@ -60,6 +59,5 @@ TORCH_API Value* tryConvertToType(
     const TypePtr& concrete_type,
     Value* value,
     bool allow_conversions);
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/schema_type_parser.cpp

@@ -31,7 +31,6 @@ using c10::VarType;
 
 namespace torch {
 namespace jit {
-namespace script {
 
 TypePtr SchemaTypeParser::parseBaseType() {
   static std::unordered_map<std::string, TypePtr> type_map = {
@@ -292,6 +291,5 @@ void SchemaTypeParser::parseList(
     L.expect(end);
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/schema_type_parser.h

@@ -7,7 +7,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 using TypePtr = c10::TypePtr;
 
@@ -33,6 +32,5 @@ struct CAFFE2_API SchemaTypeParser {
   Lexer& L;
   size_t next_id = 0;
 };
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/script_type_parser.cpp

@@ -4,7 +4,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 const std::unordered_map<std::string, TypePtr>& string_to_type_lut();
 namespace {
 
@@ -355,6 +354,5 @@ c10::IValue ScriptTypeParser::parseClassConstant(const Assign& assign) {
   return *default_val.begin();
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/script_type_parser.h

@@ -6,7 +6,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 /**
  * class ScriptTypeParser
@@ -45,6 +44,5 @@ class TORCH_API ScriptTypeParser {
 
   ResolverPtr resolver_ = nullptr;
 };
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/string_to_type.cpp

@@ -2,7 +2,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 using namespace c10;
 const std::unordered_map<std::string, TypePtr>& string_to_type_lut() {
   static std::unordered_map<std::string, TypePtr> map = {
@@ -22,6 +21,5 @@ const std::unordered_map<std::string, TypePtr>& string_to_type_lut() {
       {"tuple", AnyTupleType::get()}};
   return map;
 }
-}
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/strtod.cpp

@@ -76,7 +76,6 @@ double parse_inf_or_nan(const char *p, char **endptr)
 
 namespace torch {
 namespace jit {
-namespace script {
 
 #ifdef _MSC_VER
 C10_EXPORT double strtod_c(const char *nptr, char **endptr)
@@ -265,4 +264,3 @@ C10_EXPORT float strtof_c(const char *nptr, char **endptr)
 
 }
 }
-}

torch/csrc/jit/frontend/strtod.h

@@ -4,11 +4,9 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 CAFFE2_API double strtod_c(const char *nptr, char **endptr);
 CAFFE2_API float strtof_c(const char *nptr, char **endptr);
 
 }
 }
-}

torch/csrc/jit/frontend/sugared_value.cpp

@@ -6,7 +6,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 struct NoneValue : SugaredValue {
   NoneValue() = default;
@@ -623,6 +622,5 @@ std::shared_ptr<BuiltinFunction> BuiltinFunction::tryCreate(
   return nullptr;
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/sugared_value.h

@@ -10,7 +10,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 using SugaredValuePtr = std::shared_ptr<SugaredValue>;
 
@@ -365,7 +364,7 @@ struct FunctionValue : public SugaredValue {
       try {
         callee->ensure_defined();
       } catch (const RecursiveMethodCallError&) {
-        throw script::ErrorReport(loc)
+        throw ErrorReport(loc)
             << " function '" << callee->name() << "' is called recursively. "
             << "Recursive calls are not supported";
       }
@@ -428,7 +427,7 @@ struct MethodValue : public SugaredValue {
         try {
           method->ensure_defined();
         } catch (const RecursiveMethodCallError&) {
-          throw script::ErrorReport(loc)
+          throw ErrorReport(loc)
               << " method '" << method->name() << "' is called recursively. "
               << "Recursive calls are not supported";
         }
@@ -652,6 +651,5 @@ struct SimpleSelf : public Self {
  private:
   ClassTypePtr classType_;
 };
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/tracer.cpp

@@ -152,7 +152,7 @@ Value* TracingState::getValue(const IValue& var) {
 
     // Find torchbind classes
     if (isCustomClass(var)) {
-      auto obj = script::Object(var.toObject());
+      auto obj = Object(var.toObject());
       auto qualname = obj.type()->name();
       auto custom_class_type = getCustomClass(qualname->qualifiedName());
       if (custom_class_type) {
@@ -313,14 +313,14 @@ static IValue addInput(const std::shared_ptr<TracingState> & state, const IValue
 static void gatherParametersAndBuffers(
     const std::shared_ptr<TracingState>& state,
     Value* self_value,
-    const script::Module& self,
+    const Module& self,
     const std::string& prefix) {
   Graph& g = *self_value->owningGraph();
 
   state->setValue(self._ivalue(), self_value);
 
   auto self_ty = self.type();
-  for (const script::NameValue& s : self.named_attributes(/*recurse=*/false)) {
+  for (const NameValue& s : self.named_attributes(/*recurse=*/false)) {
     auto qualname = prefix + "." + s.name;
     Value* trace_get_attr = g.insertNode(g.create(prim::TracedAttr))
                                 ->s_(attr::scope, qualname)
@@ -335,7 +335,7 @@ static void gatherParametersAndBuffers(
     }
     if (self_ty->getAttribute(s.name)->is_module()) {
       gatherParametersAndBuffers(
-          state, trace_get_attr, script::Module(s.value.toObject()), qualname);
+          state, trace_get_attr, Module(s.value.toObject()), qualname);
     }
   }
 }
@@ -345,7 +345,7 @@ std::pair<std::shared_ptr<TracingState>, Stack> trace(
     const std::function<Stack(Stack)>& traced_fn,
     std::function<std::string(const Variable&)> var_name_lookup_fn,
     bool force_outplace,
-    script::Module* self) {
+    Module* self) {
   try {
     // Start tracing, treating 'inputs' as inputs to the trace, which can be
     // varied on subsequent invocations of the trace.  Any other variables
@@ -387,7 +387,7 @@ std::pair<std::shared_ptr<TracingState>, Stack> trace(
     }
     setTracingState(nullptr);
 
-    if (script::getInlineEverythingMode()) {
+    if (getInlineEverythingMode()) {
       Inline(*graph);
     }
     FixupTraceScopeBlocks(graph, self);

torch/csrc/jit/frontend/tracer.h

@@ -21,10 +21,7 @@ namespace jit {
 struct Node;
 struct Value;
 struct Graph;
-
+struct Module;
-namespace script {
-  struct Module;
-}
 
 namespace tracer {
 
@@ -210,7 +207,7 @@ TORCH_API std::pair<std::shared_ptr<TracingState>, Stack> trace(
     const std::function<Stack(Stack)>& traced_fn,
     std::function<std::string(const Variable&)> var_name_lookup_fn,
     bool force_outplace = false,
-    script::Module* self = nullptr);
+    Module* self = nullptr);
 
 TORCH_API void abandon();
 

torch/csrc/jit/frontend/tree.h

@@ -11,7 +11,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 // Tree's are used to represent all forms of TC IR, pre- and post- typechecking.
 // Rather than have a full class hierarchy for all TC statements,
@@ -221,6 +220,5 @@ static inline std::ostream& operator<<(std::ostream& out, const TreeRef& t) {
   return out << pretty_tree(t);
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/frontend/tree_views.h

@@ -10,7 +10,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 // clang-format off
 // TreeView provides a statically-typed way to traverse the tree, which should
@@ -813,7 +812,7 @@ struct Const : public Expr {
     // We can't pass in nullptr as the dummy pointer gets dereferenced for
     // Android version of strtod_c().
     char* dummy;
-    return torch::jit::script::strtod_c(
+    return torch::jit::strtod_c(
         subtree(0)->stringValue().c_str(), &dummy);
   }
   const std::string& text() const {
@@ -1045,14 +1044,13 @@ struct Delete : public Stmt {
   }
 };
 
-} // namespace script
 } // namespace jit
 } // namespace torch
 
 namespace std {
 
 template <typename T>
-struct iterator_traits<torch::jit::script::ListIterator<T>>
+struct iterator_traits<torch::jit::ListIterator<T>>
-    : std::iterator_traits<torch::jit::script::TreeList::const_iterator> {};
+    : std::iterator_traits<torch::jit::TreeList::const_iterator> {};
 
 } // namespace std

torch/csrc/jit/ir/ir.cpp

@@ -963,7 +963,7 @@ const Operator& Node::getOperator() const {
   if (maybe)
     return *maybe;
 
-  auto er = script::ErrorReport(sourceRange());
+  auto er = ErrorReport(sourceRange());
   er << "Schema not found for node. File a bug report.\n";
   er << "Node: " << *this << "\n";
   er << "Input types:";
@@ -1491,7 +1491,7 @@ Value* Graph::insert(
     at::ArrayRef<NamedValue> args,
     at::ArrayRef<NamedValue> kwargs,
     const c10::optional<SourceRange>& range) {
-  return script::emitBuiltinCall(
+  return emitBuiltinCall(
       range.value_or(fakeRange()), *this, opname, args, kwargs);
 }
 
@@ -1721,7 +1721,7 @@ Value* Graph::insertToList(Value* v, TypePtr type) {
 
 Value* Graph::insertFunctionCall(
     Function* callee,
-    const script::MatchedSchema& matched) {
+    const MatchedSchema& matched) {
   std::string func_name = callee->name();
   Value* fn_constant = insertNode(create(prim::Constant))
                            ->s_(attr::name, func_name)
@@ -1737,7 +1737,7 @@ Value* Graph::insertFunctionCall(
 
 Value* Graph::insertMethodCall(
     std::string method_name,
-    const script::MatchedSchema& matched) {
+    const MatchedSchema& matched) {
   Value* result = insertNode(create(prim::CallMethod, matched.inputs))
                       ->s_(attr::name, std::move(method_name))
                       ->output()

torch/csrc/jit/ir/ir.h

@@ -73,9 +73,7 @@ using namespace ::c10::aten;
 }
 
 struct Function;
-namespace script {
 struct MatchedSchema;
-} // namespace script
 
 // Graph represents one "function" of computation.
 // It uses a simple ownership model where the graph owns all the nodes inside
@@ -1134,10 +1132,10 @@ struct Graph {
 
   TORCH_API Value* insertFunctionCall(
       Function* callee,
-      const script::MatchedSchema& matched);
+      const MatchedSchema& matched);
   TORCH_API Value* insertMethodCall(
       std::string method_name,
-      const script::MatchedSchema& matched);
+      const MatchedSchema& matched);
 
   // Note: defined in python_ir.cpp and can be used only in python extension
   Node* createPythonOp(

torch/csrc/jit/ir/irparser.cpp

@@ -9,7 +9,6 @@
 
 namespace torch {
 namespace jit {
-namespace script {
 
 struct VarWithType;
 struct ParsedLiteral;
@@ -57,7 +56,7 @@ class IRParser {
 
   Value* findValueInVMap(const std::string& name);
 
-  torch::jit::script::Lexer L;
+  torch::jit::Lexer L;
   torch::jit::Graph* g = nullptr;
   std::unordered_map<std::string, Value*>& vmap;
   SchemaTypeParser type_parser;
@@ -86,7 +85,7 @@ void parseIR(
     const std::string& str,
     torch::jit::Graph* graph,
     std::unordered_map<std::string, Value*>& vmap) {
-  torch::jit::script::IRParser p(str, graph, vmap);
+  torch::jit::IRParser p(str, graph, vmap);
   p.parse();
 }
 
@@ -473,6 +472,5 @@ Value* IRParser::findValueInVMap(const std::string& name) {
   return vmap.at(name);
 }
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/ir/irparser.h

@@ -12,8 +12,6 @@ namespace jit {
 struct Graph;
 struct Value;
 
-namespace script {
-
 // \brief Parse IR from \p STR constructing the corresponding IR in\ GRAPH.
 TORCH_API void parseIR(const std::string& str, torch::jit::Graph* graph);
 
@@ -27,6 +25,5 @@ TORCH_API void parseIR(
     torch::jit::Graph* graph,
     std::unordered_map<std::string, Value*>& vmap);
 
-} // namespace script
 } // namespace jit
 } // namespace torch

torch/csrc/jit/mobile/import.cpp

@@ -125,14 +125,14 @@ class BytecodeDeserializer final {
  private:
   c10::IValue readArchive(const std::string& archive_name,
     std::shared_ptr<mobile::CompilationUnit> mcu);
-  std::shared_ptr<script::CompilationUnit> compilation_unit_;
+  std::shared_ptr<CompilationUnit> compilation_unit_;
   std::unordered_set<std::string> imported_libs_;
   std::unique_ptr<PyTorchStreamReader> reader_;
   c10::optional<at::Device> device_;
 };
 
 BytecodeDeserializer::BytecodeDeserializer(std::unique_ptr<PyTorchStreamReader> reader)
-    : compilation_unit_(std::make_shared<script::CompilationUnit>()), reader_(std::move(reader)) {}
+    : compilation_unit_(std::make_shared<CompilationUnit>()), reader_(std::move(reader)) {}
 
 mobile::Module BytecodeDeserializer::deserialize(c10::optional<at::Device> device) {
   device_ = device;