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[jit] kill script namespace (#34515)

Browse Source 
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
This commit is contained in:
Michael Suo
2020-03-11 23:29:34 -07:00
committed by Facebook GitHub Bot
parent cf8b728255
commit c235be42dd
152 changed files with 559 additions and 694 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
android/pytorch_android/generate_test_asset.cpp
View File

@ -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);

2
android/pytorch_android/src/main/cpp/pytorch_jni_jit.cpp
View File

@ -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;";

6
android/pytorch_android/src/main/java/org/pytorch/Module.java
View File

@ -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}.

2
aten/src/ATen/core/function.h
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@ -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;

2
aten/src/ATen/core/ivalue.cpp
View File

@ -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;

8
aten/src/ATen/core/ivalue.h
View File

@ -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_;
};

6
aten/src/ATen/core/ivalue_inl.h
View File

@ -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));

6
aten/src/ATen/core/jit_type.h
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@ -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.

2
binaries/dump_operator_names.cc
View File

@ -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();

8
caffe2/contrib/pytorch/script_module_op.cc
View File

@ -7,8 +7,8 @@
namespace caffe2 {
using torch::jit::IValue;
using torch::jit::script::Method;
using torch::jit::script::Module;
using torch::jit::Method;
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)

10
caffe2/python/pybind_state.cc
View File

@ -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)) {
blob->GetMutable<std::unique_ptr<torch::jit::script::Module>>()->reset(
new torch::jit::script::Module(*module));
if (auto module = torch::jit::as_module(arg)) {
blob->GetMutable<std::unique_ptr<torch::jit::Module>>()->reset(
new torch::jit::Module(*module));
return true;
}
#endif

2
docs/source/jit.rst
View File

@ -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):

4
docs/source/notes/large_scale_deployments.rst
View File

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

6
docs/source/org/pytorch/Module.rst
View File

@ -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
^^^^^^^^^

2
ios/TestApp/TestAppTests/TestAppTests.mm
View File

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

40
test/cpp/jit/test_alias_analysis.cpp
View File

@ -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 ()

2
test/cpp/jit/test_autodiff.cpp
View File

@ -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);

2
test/cpp/jit/test_class_import.cpp
View File

@ -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):

1
test/cpp/jit/test_class_parser.cpp
View File

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

2
test/cpp/jit/test_class_type.cpp
View File

@ -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);

6
test/cpp/jit/test_constant_pooling.cpp
View File

@ -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]()

4
test/cpp/jit/test_custom_operators.cpp
View File

@ -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);

2
test/cpp/jit/test_dce.cpp
View File

@ -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);

10
test/cpp/jit/test_fuser.cpp
View File

@ -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();

1
test/cpp/jit/test_inliner.cpp
View File

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

2
test/cpp/jit/test_interface.cpp
View File

@ -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

4
test/cpp/jit/test_ir.cpp
View File

@ -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(

10
test/cpp/jit/test_irparser.cpp
View File

@ -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);
}

2
test/cpp/jit/test_ivalue.cpp
View File

@ -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);

22
test/cpp/jit/test_lite_interpreter.cpp
View File

@ -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):

12
test/cpp/jit/test_misc.cpp
View File

@ -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",

2
test/cpp/jit/test_module_api.cpp
View File

@ -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);

2
test/cpp/jit/test_peephole_optimize.cpp
View File

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

1
test/cpp/jit/test_save_load.cpp
View File

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

4
test/cpp/jit/test_schema_matching.cpp
View File

@ -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)

62
test/cpp/jit/test_subgraph_matcher.cpp
View File

@ -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)

8
test/cpp/jit/test_subgraph_rewriter.cpp
View File

@ -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);

2
test/cpp/jit/test_utils.cpp
View File

@ -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;

10
test/custom_operator/test_custom_ops.cpp
View File

@ -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);

2
test/mobile/custom_build/predictor.cpp
View File

@ -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();

2
test/test_cpp_api_parity.py
View File

@ -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};

2
torch/csrc/api/include/torch/jit.h
View File

@ -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

4
torch/csrc/api/include/torch/serialize.h
View File

@ -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);

4
torch/csrc/api/include/torch/serialize/input-archive.h
View File

@ -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

12
torch/csrc/api/include/torch/serialize/output-archive.h
View File

@ -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() : cu_(std::make_shared<jit::script::CompilationUnit>()), module_("__torch__.Module", cu_) {}
explicit OutputArchive(std::shared_ptr<jit::CompilationUnit> 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_;
jit::script::Module module_;
std::shared_ptr<jit::CompilationUnit> cu_;
jit::Module module_;
};
} // namespace serialize
} // namespace torch

6
torch/csrc/api/src/jit.cpp
View File

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

4
torch/csrc/api/src/serialize/input-archive.cpp
View File

@ -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);
}

2
torch/csrc/api/src/serialize/output-archive.cpp
View File

@ -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) {}

2
torch/csrc/distributed/rpc/py_rref.cpp
View File

@ -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, "

8
torch/csrc/distributed/rpc/python_rpc_handler.cpp
View File

@ -27,8 +27,8 @@ namespace {
// PythonTypeResolver that inherits from Script::Resolver to
// support resolving types together with ScriptTypeParser.
struct PythonTypeResolver : public jit::script::Resolver {
std::shared_ptr<jit::script::SugaredValue> resolveValue(
struct PythonTypeResolver : public jit::Resolver {
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_;
}

6
torch/csrc/distributed/rpc/python_rpc_handler.h
View File

@ -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

12
torch/csrc/jit/api/compilation_unit.h
View File

@ -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

8
torch/csrc/jit/api/method.h
View File

@ -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

6
torch/csrc/jit/api/module.cpp
View File

@ -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 {
return torch::jit::script::Module(toObject());
torch::jit::Module IValue::toModule() const {
return torch::jit::Module(toObject());
}
bool IValue::isModule() const {
return isObject() && toObjectRef().type()->is_module();

8
torch/csrc/jit/api/module.h
View File

@ -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

2
torch/csrc/jit/api/module_save.cpp
View File

@ -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

4
torch/csrc/jit/api/object.cpp
View File

@ -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

7
torch/csrc/jit/api/object.h
View File

@ -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

2
torch/csrc/jit/docs/serialization.md
View File

@ -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

4
torch/csrc/jit/frontend/builtin_functions.cpp
View File

@ -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

2
torch/csrc/jit/frontend/builtin_functions.h
View File

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

2
torch/csrc/jit/frontend/concrete_module_type.cpp
View File

@ -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

2
torch/csrc/jit/frontend/concrete_module_type.h
View File

@ -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

2
torch/csrc/jit/frontend/convert_to_ssa.cpp
View File

@ -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

2
torch/csrc/jit/frontend/convert_to_ssa.h
View File

@ -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

2
torch/csrc/jit/frontend/edit_distance.cpp
View File

@ -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

2
torch/csrc/jit/frontend/edit_distance.h
View File

@ -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

2
torch/csrc/jit/frontend/error_report.cpp
View File

@ -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

2
torch/csrc/jit/frontend/error_report.h
View File

@ -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

4
torch/csrc/jit/frontend/function_schema_parser.cpp
View File

@ -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) {

8
torch/csrc/jit/frontend/ir_emitter.cpp
View File

@ -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

2
torch/csrc/jit/frontend/ir_emitter.h
View File

@ -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

2
torch/csrc/jit/frontend/lexer.cpp
View File

@ -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

4
torch/csrc/jit/frontend/lexer.h
View File

@ -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

2
torch/csrc/jit/frontend/mini_environment.h
View File

@ -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

2
torch/csrc/jit/frontend/parse_string_literal.h
View File

@ -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

2
torch/csrc/jit/frontend/parser.cpp
View File

@ -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

2
torch/csrc/jit/frontend/parser.h
View File

@ -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

2
torch/csrc/jit/frontend/parser_constants.h
View File

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

2
torch/csrc/jit/frontend/resolver.h
View File

@ -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

2
torch/csrc/jit/frontend/schema_matching.cpp
View File

@ -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

2
torch/csrc/jit/frontend/schema_matching.h
View File

@ -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

2
torch/csrc/jit/frontend/schema_type_parser.cpp
View File

@ -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

2
torch/csrc/jit/frontend/schema_type_parser.h
View File

@ -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

2
torch/csrc/jit/frontend/script_type_parser.cpp
View File

@ -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

2
torch/csrc/jit/frontend/script_type_parser.h
View File

@ -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

2
torch/csrc/jit/frontend/string_to_type.cpp
View File

@ -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

2
torch/csrc/jit/frontend/strtod.cpp
View File

@ -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)
}
}
}

2
torch/csrc/jit/frontend/strtod.h
View File

@ -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);
}
}
}

2
torch/csrc/jit/frontend/sugared_value.cpp
View File

@ -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

6
torch/csrc/jit/frontend/sugared_value.h
View File

@ -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

12
torch/csrc/jit/frontend/tracer.cpp
View File

@ -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);

7
torch/csrc/jit/frontend/tracer.h
View File

@ -21,10 +21,7 @@ namespace jit {
struct Node;
struct Value;
struct Graph;
namespace script {
struct Module;
}
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();

2
torch/csrc/jit/frontend/tree.h
View File

@ -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

8
torch/csrc/jit/frontend/tree_views.h
View File

@ -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>>
: std::iterator_traits<torch::jit::script::TreeList::const_iterator> {};
struct iterator_traits<torch::jit::ListIterator<T>>
: std::iterator_traits<torch::jit::TreeList::const_iterator> {};
} // namespace std

8
torch/csrc/jit/ir/ir.cpp
View File

@ -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()

6
torch/csrc/jit/ir/ir.h
View File

@ -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(

6
torch/csrc/jit/ir/irparser.cpp
View File

@ -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

3
torch/csrc/jit/ir/irparser.h
View File

@ -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

4
torch/csrc/jit/mobile/import.cpp
View File

@ -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;

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