More changes for hidden visibility (pytorch#10692)

Summary:
Let's run CI tests to see what fails given the changes that just landed in pytorch#10624

cc mingzhe09088 ezyang Yangqing
Pull Request resolved: pytorch#10692

Reviewed By: mingzhe09088

Differential Revision: D9423617

Pulled By: orionr

fbshipit-source-id: 3bda1f118d13f8dd8e823727c93167cae747d8cf

aten/src/ATen/Device.h

@@ -22,7 +22,7 @@ namespace at {
 /// 1. A negative index represents the current device, a non-negative index
 /// represents a specific, concrete device,
 /// 2. When the device type is CPU, the device index must be zero.
-struct Device {
+struct AT_API Device {
   using Type = at::DeviceType;
 
   /// Constructs a new `Device` from a `DeviceType` and an optional device

aten/src/ATen/Generator.h

@@ -1,10 +1,12 @@
 #pragma once
 
+#include <ATen/ATenGeneral.h>
+
 #include <stdint.h>
 
 namespace at {
 
-struct Generator {
+struct AT_API Generator {
   Generator() {};
   Generator(const Generator& other) = delete;
   Generator(Generator&& other) = delete;

aten/src/ATen/OptionsGuard.h

@@ -13,7 +13,7 @@ struct DefaultTensorOptions {
   /// Returns the current thread local default options.
   /// Defined in OptionsGuard.cpp because we can't use optional in headers, due
   /// to Windows and other compilers.
-  static TensorOptions& get();
+  AT_API static TensorOptions& get();
 
  private:
   /// This is an optional because of compiler bugs that mis-initialize static

aten/src/ATen/function_wrapper.py

@@ -119,7 +119,7 @@ def TypedDict(name, attrs, total=True):  # type: ignore
 
 # add non-virtual declaration to Tensor.h
 TENSOR_METHOD_DECLARATION = CodeTemplate("""\
-AT_API ${return_type} ${api_name}(${method_formals_with_defaults})${const_mark};
+${return_type} ${api_name}(${method_formals_with_defaults})${const_mark};
 """)
 # add non-virtual declaration to Tensor.cpp
 TENSOR_METHOD_DEFINITION = CodeTemplate("""\

aten/src/ATen/templates/Tensor.h

@@ -41,7 +41,7 @@ namespace at {
 //
 // Note that Tensor can also be NULL, i.e. it is not associated with any underlying TensorImpl, and
 // special care must be taken to handle this.
-struct Tensor : public detail::TensorBase {
+struct AT_API Tensor : public detail::TensorBase {
   using TensorBase = detail::TensorBase;
   Tensor() : TensorBase() {}
   Tensor(TensorImpl * self, bool retain) : TensorBase(self, retain) {}
@@ -204,7 +204,7 @@ struct Tensor : public detail::TensorBase {
   friend struct WeakTensor;
 };
 
-struct WeakTensor : public detail::WeakTensorBase {
+struct AT_API WeakTensor : public detail::WeakTensorBase {
   using WeakTensorBase = detail::WeakTensorBase;
   WeakTensor() : WeakTensorBase() {}
   WeakTensor(TensorImpl * self, bool retain) : WeakTensorBase(self, retain) {}

caffe2/contrib/script/compiler.h

@@ -7,7 +7,8 @@ namespace caffe2 {
 namespace script {
 
 struct CompilationUnitImpl;
-struct CompilationUnit {
+
+struct CAFFE2_API CompilationUnit {
   CompilationUnit();
   void define(const std::string& str);
   void defineExtern(const std::string& str, std::unique_ptr<NetDef> netdef);

caffe2/core/blob_stats.h

@@ -41,6 +41,6 @@ namespace BlobStat {
  * Return size in bytes of the blob, if available for a blob of given type.
  * If not available, return 0.
  */
-size_t sizeBytes(const Blob& blob);
+CAFFE2_API size_t sizeBytes(const Blob& blob);
 }
 }

caffe2/core/db.h

@@ -19,7 +19,7 @@ enum Mode { READ, WRITE, NEW };
 /**
  * An abstract class for the cursor of the database while reading.
  */
-class Cursor {
+class CAFFE2_API Cursor {
  public:
   Cursor() { }
   virtual ~Cursor() { }
@@ -58,7 +58,7 @@ class Cursor {
 /**
  * An abstract class for the current database transaction while writing.
  */
-class Transaction {
+class CAFFE2_API Transaction {
  public:
   Transaction() { }
   virtual ~Transaction() { }
@@ -77,7 +77,7 @@ class Transaction {
 /**
  * An abstract class for accessing a database of key-value pairs.
  */
-class DB {
+class CAFFE2_API DB {
  public:
   DB(const string& /*source*/, Mode mode) : mode_(mode) {}
   virtual ~DB() { }
@@ -141,7 +141,7 @@ inline bool DBExists(const string& db_type, const string& full_db_name) {
 /**
  * A reader wrapper for DB that also allows us to serialize it.
  */
-class DBReader {
+class CAFFE2_API DBReader {
  public:
 
   friend class DBReaderSerializer;
@@ -288,7 +288,7 @@ class DBReader {
   AT_DISABLE_COPY_AND_ASSIGN(DBReader);
 };
 
-class DBReaderSerializer : public BlobSerializerBase {
+class CAFFE2_API DBReaderSerializer : public BlobSerializerBase {
  public:
   /**
    * Serializes a DBReader. Note that this blob has to contain DBReader,
@@ -300,7 +300,7 @@ class DBReaderSerializer : public BlobSerializerBase {
       BlobSerializerBase::SerializationAcceptor acceptor) override;
 };
 
-class DBReaderDeserializer : public BlobDeserializerBase {
+class CAFFE2_API DBReaderDeserializer : public BlobDeserializerBase {
  public:
   void Deserialize(const BlobProto& proto, Blob* blob) override;
 };

caffe2/core/logging_is_not_google_glog.h

@@ -27,7 +27,7 @@ const int INFO    = 0;
 const char CAFFE2_SEVERITY_PREFIX[] = "FEWIV";
 
 namespace caffe2 {
-class MessageLogger {
+class CAFFE2_API MessageLogger {
  public:
   MessageLogger(const char *file, int line, int severity);
   ~MessageLogger();
@@ -46,7 +46,7 @@ class MessageLogger {
 // This class is used to explicitly ignore values in the conditional
 // logging macros.  This avoids compiler warnings like "value computed
 // is not used" and "statement has no effect".
-class LoggerVoidify {
+class CAFFE2_API LoggerVoidify {
  public:
   LoggerVoidify() { }
   // This has to be an operator with a precedence lower than << but

caffe2/core/memonger.h

@@ -10,11 +10,11 @@
 namespace caffe2 {
 namespace memonger {
 
-NetDef optimize_inference_net(
+CAFFE2_API NetDef optimize_inference_net(
     const NetDef& net,
     const std::set<string>& static_blobs);
 
-NetDef compute_blob_recycling_for_dag(
+CAFFE2_API NetDef compute_blob_recycling_for_dag(
     const NetDef& net,
     const std::vector<string>& heads,
     const std::vector<int>& op_indices,

caffe2/core/module.h

@@ -23,7 +23,7 @@ namespace caffe2 {
  * different modules. Currently, we only store the name and a simple
  * description of what this module does.
  */
-class ModuleSchema {
+class CAFFE2_API ModuleSchema {
  public:
   ModuleSchema(const char* name, const char* description);
 
@@ -45,12 +45,12 @@ class ModuleSchema {
  *       the reason we do not include ".so" is for cross-platform compatibility
  *       on platforms like mac os.
  */
-const CaffeMap<string, const ModuleSchema*>& CurrentModules();
+CAFFE2_API const CaffeMap<string, const ModuleSchema*>& CurrentModules();
 
 /**
  * @brief Checks whether a module is already present in the current binary.
  */
-bool HasModule(const string& name);
+CAFFE2_API bool HasModule(const string& name);
 
 /**
  * @brief Load a module.
@@ -60,7 +60,7 @@ bool HasModule(const string& name);
  *       full path option to only experimental modules.
  *   filename: (optional) a filename that serves as a hint to load the module.
  */
-void LoadModule(const string& name, const string& filename="");
+CAFFE2_API void LoadModule(const string& name, const string& filename="");
 
 
 #define CAFFE2_MODULE(name, description)                                    \

caffe2/core/net_async_base.h

@@ -31,7 +31,7 @@ namespace tracing {
 class Tracer;
 }
 
-class AsyncNetBase : public NetBase {
+class CAFFE2_API AsyncNetBase : public NetBase {
  public:
   AsyncNetBase(const std::shared_ptr<const NetDef>& net_def, Workspace* ws);
   ~AsyncNetBase() override;

caffe2/core/net_async_scheduling.h

@@ -5,7 +5,7 @@
 
 namespace caffe2 {
 
-class AsyncSchedulingNet : public AsyncNetBase {
+class CAFFE2_API AsyncSchedulingNet : public AsyncNetBase {
  public:
   AsyncSchedulingNet(
       const std::shared_ptr<const NetDef>& net_def,

caffe2/core/qtensor.h

@@ -14,7 +14,7 @@
 namespace caffe2 {
 
 template <class Context>
-class QTensor {
+class CAFFE2_API QTensor {
  public:
   QTensor() {}
   virtual ~QTensor() {}

caffe2/core/types.h

@@ -50,7 +50,7 @@ CAFFE2_API const TypeMeta& DataTypeToTypeMeta(const TensorProto::DataType& dt);
 static_assert(sizeof(unsigned short) == 2,
               "Short on this platform is not 16 bit.");
 namespace caffe2 {
-typedef struct CAFFE2_ALIGNED(2) __f16 { uint16_t x; } float16;
+typedef struct CAFFE2_API CAFFE2_ALIGNED(2) __f16 { uint16_t x; } float16;
 
 // Helpers to avoid using typeinfo with -rtti
 template <typename T>

caffe2/observers/runcnt_observer.h

@@ -8,7 +8,8 @@
 namespace caffe2 {
 
 class RunCountNetObserver;
-class RunCountOperatorObserver final : public ObserverBase<OperatorBase> {
+
+class CAFFE2_API RunCountOperatorObserver final : public ObserverBase<OperatorBase> {
  public:
   explicit RunCountOperatorObserver(OperatorBase* op) = delete;
   RunCountOperatorObserver(OperatorBase* op, RunCountNetObserver* netObserver);
@@ -25,7 +26,7 @@ class RunCountOperatorObserver final : public ObserverBase<OperatorBase> {
   RunCountNetObserver* netObserver_;
 };
 
-class RunCountNetObserver final : public OperatorAttachingNetObserver<
+class CAFFE2_API RunCountNetObserver final : public OperatorAttachingNetObserver<
                                       RunCountOperatorObserver,
                                       RunCountNetObserver> {
  public:

caffe2/observers/time_observer.h

@@ -13,7 +13,8 @@
 namespace caffe2 {
 
 class TimeObserver;
-class TimeCounter {
+
+class CAFFE2_API TimeCounter {
  public:
   explicit TimeCounter() {}
   inline float average_time() const {
@@ -27,8 +28,8 @@ class TimeCounter {
   int iterations_ = 0;
 };
 
-class TimeOperatorObserver final : public TimeCounter,
-                                   public ObserverBase<OperatorBase> {
+class CAFFE2_API TimeOperatorObserver final : public TimeCounter,
+                                              public ObserverBase<OperatorBase> {
  public:
   explicit TimeOperatorObserver(OperatorBase* subject) = delete;
   explicit TimeOperatorObserver(
@@ -44,7 +45,7 @@ class TimeOperatorObserver final : public TimeCounter,
   void Stop() override;
 };
 
-class TimeObserver final
+class CAFFE2_API TimeObserver final
     : public TimeCounter,
       public OperatorAttachingNetObserver<TimeOperatorObserver, TimeObserver> {
  public:

caffe2/onnx/backend.h

@@ -25,7 +25,7 @@ using ::ONNX_NAMESPACE::ValueInfoProto;
 
 using ValueInfoMap = std::unordered_map<std::string, ValueInfoProto>;
 
-class ConversionContext {
+class CAFFE2_API ConversionContext {
  public:
   ConversionContext(const ValueInfoMap& value_infos, int opset_version)
       : value_infos_(value_infos), opset_version_(opset_version) {}
@@ -44,15 +44,15 @@ class ConversionContext {
 // \brief This struct holds the converted ops after the onnx->c2 conversion.
 // Notice that for RNN ops, it may create ops in init_net. Hence we have the
 // `init_ops` field.
-struct Caffe2Ops {
+struct CAFFE2_API Caffe2Ops {
   ::google::protobuf::RepeatedPtrField<caffe2::OperatorDef> init_ops;
   ::google::protobuf::RepeatedPtrField<caffe2::OperatorDef> ops;
   ::google::protobuf::RepeatedPtrField<std::string> interface_blobs;
 };
 
 // A convenient class to query attributes of a NodeProto. Note that the
 // NodeProto can not be modified during the query of OnnxAttributes object
-class OnnxAttributes {
+class CAFFE2_API OnnxAttributes {
  public:
   OnnxAttributes(const NodeProto& node);
 
@@ -120,15 +120,15 @@ template <>
 const TensorProto* OnnxAttributes::get(const std::string& key) const;
 
 // convenient class for onnx node
-struct OnnxNode {
+struct CAFFE2_API OnnxNode {
   OnnxNode(const NodeProto& node_in) : node(node_in), attributes(node_in) {}
 
   const NodeProto& node;
 
   OnnxAttributes attributes;
 };
 
-class Caffe2Backend {
+class CAFFE2_API Caffe2Backend {
  public:
   // Since we still have this Python-C++ hybrid flow, we will need to take the
   // DummyName generator from Python as a pointer. In this case, Python env owns

caffe2/onnx/backend_rep.h

@@ -8,7 +8,7 @@
 #include <vector>
 
 namespace caffe2 { namespace onnx {
-class Caffe2BackendRep {
+class CAFFE2_API Caffe2BackendRep {
  public:
   void Run(
       const caffe2::Predictor::TensorVector& inputs,

caffe2/operators/counter_ops.h

@@ -9,7 +9,7 @@
 
 namespace caffe2 {
 template <typename T>
-class Counter {
+class CAFFE2_API Counter {
  public:
   explicit Counter(T count) : count_(count) {}
   bool countDown() {

caffe2/operators/create_scope_op.h

@@ -20,7 +20,7 @@ namespace detail {
  * Keeps track of forward and backward gradient workspaces in stack,
  * reuses previously created workspaces, non-thread safe
  */
-class WorkspaceStack {
+class CAFFE2_API WorkspaceStack {
  public:
   explicit WorkspaceStack() : parent_ws_(nullptr), top_(-1) {}
 

caffe2/operators/rnn/recurrent_network_executor.h

@@ -466,7 +466,7 @@ std::unique_ptr<RecurrentNetworkExecutorBase> createRNNExecutor(
     std::string timestep_blob,
     ArgumentHelper rnn_args);
 
-class ThreadedRecurrentNetworkExecutor : public RecurrentNetworkExecutorBase {
+class CAFFE2_API ThreadedRecurrentNetworkExecutor : public RecurrentNetworkExecutorBase {
  public:
   ThreadedRecurrentNetworkExecutor(
       const NetDef& step_net_def,

caffe2/operators/rnn/recurrent_network_op.h

@@ -46,7 +46,7 @@ struct Link {
   int32_t window{1};
 };
 
-struct ScratchWorkspaces {
+struct CAFFE2_API ScratchWorkspaces {
   std::vector<std::shared_ptr<Workspace>> stepWorkspaces;
   std::shared_ptr<Workspace> sharedBlobsWs = nullptr;
 };