Merge pull request #39 from iotamudelta/master

Merge from upstream

.jenkins/pytorch/test.sh

@@ -9,6 +9,11 @@ source "$(dirname "${BASH_SOURCE[0]}")/common.sh"
 
 echo "Testing pytorch"
 
+if [[ "$BUILD_ENVIRONMENT" == *rocm* ]]; then
+  echo "Skipping ROCm tests for now"
+  exit 0
+fi
+
 # JIT C++ extensions require ninja.
 git clone https://github.com/ninja-build/ninja --quiet
 pushd ninja

README.md

@@ -1,4 +1,4 @@
-<p align="center"><img width="40%" src="docs/source/_static/img/pytorch-logo-dark.png" /></p>
+![PyTorch Logo](https://github.com/pytorch/pytorch/blob/master/docs/source/_static/img/pytorch-logo-dark.png)
 
 --------------------------------------------------------------------------------
 
@@ -34,32 +34,14 @@ See also the [ci.pytorch.org HUD](https://ezyang.github.io/pytorch-ci-hud/build/
 
 At a granular level, PyTorch is a library that consists of the following components:
 
-<table>
-<tr>
-    <td><b> torch </b></td>
-    <td> a Tensor library like NumPy, with strong GPU support </td>
-</tr>
-<tr>
-    <td><b> torch.autograd </b></td>
-    <td> a tape-based automatic differentiation library that supports all differentiable Tensor operations in torch </td>
-</tr>
-<tr>
-    <td><b> torch.nn </b></td>
-    <td> a neural networks library deeply integrated with autograd designed for maximum flexibility </td>
-</tr>
-<tr>
-    <td><b> torch.multiprocessing  </b></td>
-    <td> Python multiprocessing, but with magical memory sharing of torch Tensors across processes. Useful for data loading and Hogwild training. </td>
-</tr>
-<tr>
-    <td><b> torch.utils </b></td>
-    <td> DataLoader, Trainer and other utility functions for convenience </td>
-</tr>
-<tr>
-    <td><b> torch.legacy(.nn/.optim) </b></td>
-    <td> legacy code that has been ported over from torch for backward compatibility reasons </td>
-</tr>
-</table>
+| Component | Description |
+| ---- | --- |
+| **torch** | a Tensor library like NumPy, with strong GPU support |
+| **torch.autograd** | a tape-based automatic differentiation library that supports all differentiable Tensor operations in torch |
+| **torch.nn** | a neural networks library deeply integrated with autograd designed for maximum flexibility |
+| **torch.multiprocessing** | Python multiprocessing, but with magical memory sharing of torch Tensors across processes. Useful for data loading and Hogwild training |
+| **torch.utils** | DataLoader, Trainer and other utility functions for convenience |
+| **torch.legacy(.nn/.optim)** | legacy code that has been ported over from torch for backward compatibility reasons |
 
 Usually one uses PyTorch either as:
 
@@ -72,7 +54,7 @@ Elaborating further:
 
 If you use NumPy, then you have used Tensors (a.k.a ndarray).
 
-<p align=center><img width="30%" src="docs/source/_static/img/tensor_illustration.png" /></p>
+![Tensor illustration](https://github.com/pytorch/pytorch/blob/master/docs/source/_static/img/tensor_illustration.png)
 
 PyTorch provides Tensors that can live either on the CPU or the GPU, and accelerate
 compute by a huge amount.
@@ -99,7 +81,7 @@ from several research papers on this topic, as well as current and past work suc
 While this technique is not unique to PyTorch, it's one of the fastest implementations of it to date.
 You get the best of speed and flexibility for your crazy research.
 
-<p align=center><img width="80%" src="docs/source/_static/img/dynamic_graph.gif" /></p>
+![Dynamic graph](https://github.com/pytorch/pytorch/blob/master/docs/source/_static/img/dynamic_graph.gif)
 
 ### Python First
 

aten/src/ATen/Retainable.h

@@ -7,21 +7,52 @@ namespace at {
 // base class for refcounted things, allows for collects of generic
 // refcounted objects that include tensors
 struct Retainable {
-  Retainable(): refcount(1) {}
+  Retainable(): refcount(1), weak_refcount(1) {}
   void retain() {
     ++refcount;
   }
   void release() {
     if(--refcount == 0) {
+      // If we know that this is the last reference then we can skip
+      // all the decrements and release_resources().
+      if (weak_refcount == 1) {
+        delete this;
+      } else {
+        release_resources();
+        weak_release();
+      }
+    }
+  }
+  void weak_retain() {
+    ++weak_refcount;
+  }
+  void weak_release() {
+    if (--weak_refcount == 0) {
       delete this;
     }
   }
-  int use_count() const {
+  bool weak_lock() {
+    for (;;) {
+      auto current_refcount = refcount.load();
+      if (current_refcount == 0) return false;
+      if (refcount.compare_exchange_strong(current_refcount, current_refcount + 1)) break;
+    }
+    return true;
+  }
+  uint32_t use_count() const {
     return refcount.load();
   }
+  uint32_t weak_use_count() const {
+    return weak_refcount.load();
+  }
+
+  virtual void release_resources() {};
   virtual ~Retainable() {}
 private:
-  std::atomic<int> refcount;
+  // INVARIANT: once refcount reaches 0 it can never go up
+  // INVARIANT: weak_refcount = number of weak references + (refcount > 0 ? 1 : 0)
+  std::atomic<uint32_t> refcount;
+  std::atomic<uint32_t> weak_refcount;
 };
 
 }

aten/src/ATen/TensorBase.h

@@ -5,54 +5,62 @@
 
 namespace at { namespace detail {
 
-// TensorBase is the base class for Tensor which handles the reference counting
-struct TensorBase {
-  TensorBase(): TensorBase(UndefinedTensor::singleton(), false) {}
-  TensorBase(TensorImpl * self, bool retain)
+// TensorBaseImpl is the base class for Tensor which handles the reference counting
+template<bool is_strong>
+struct TensorBaseImpl {
+  TensorBaseImpl(): TensorBaseImpl(UndefinedTensor::singleton(), false) {}
+  TensorBaseImpl(TensorImpl * self, bool should_retain)
   : pImpl(self) {
     if (pImpl == nullptr) {
-      throw std::runtime_error("TensorBase with nullptr not supported");
+      throw std::runtime_error("TensorBaseImpl with nullptr not supported");
+    }
+    if(should_retain && pImpl != UndefinedTensor::singleton()) {
+      retain();
     }
-    if(retain && pImpl != UndefinedTensor::singleton())
-      pImpl->retain();
   }
-  TensorBase(const TensorBase & rhs)
+  TensorBaseImpl(const TensorBaseImpl & rhs)
   : pImpl(rhs.pImpl) {
-    if (pImpl != UndefinedTensor::singleton())
-      pImpl->retain();
+    if (pImpl != UndefinedTensor::singleton()) {
+      retain();
+    }
   }
-  TensorBase(TensorBase && rhs) noexcept
+  TensorBaseImpl(TensorBaseImpl && rhs) noexcept
   : pImpl(rhs.pImpl) {
     rhs.pImpl = UndefinedTensor::singleton();
   }
-  ~TensorBase() {
-    if (pImpl != UndefinedTensor::singleton())
-      pImpl->release();
+  ~TensorBaseImpl() {
+    if (pImpl != UndefinedTensor::singleton()) {
+      release();
+    }
   }
-  TensorBase & operator=(TensorBase && rhs) & {
+  TensorBaseImpl & operator=(TensorBaseImpl && rhs) & {
     rhs.swap(*this);
     return *this;
   }
-  TensorBase & operator=(TensorBase const & rhs) & {
-      //TensorBase ctor retains original rhs.pImpl
-      //then rhs.pImpl is swapped with this->pImpl
-      //finally TensorBase dtor releases rhs.pImpl, which was originally this->pImpl
-      TensorBase(rhs).swap(*this);
-      return *this;
+  TensorBaseImpl & operator=(TensorBaseImpl const & rhs) & {
+    //TensorBaseImpl ctor retains original rhs.pImpl
+    //then rhs.pImpl is swapped with this->pImpl
+    //finally TensorBaseImpl dtor releases rhs.pImpl, which was originally this->pImpl
+    TensorBaseImpl(rhs).swap(*this);
+    return *this;
   }
   int64_t dim() const {
-    return pImpl->dim();
+    if (is_strong) {
+      return pImpl->dim();
+    } else {
+      AT_ERROR("Can't call dim() on a WeakTensor");
+    }
   }
   void reset() {
-    TensorBase().swap(*this);
+    TensorBaseImpl().swap(*this);
   }
   void reset(TensorImpl * rhs) {
-    TensorBase(rhs, true).swap(*this);
+    TensorBaseImpl(rhs, true).swap(*this);
   }
-  void reset(TensorImpl * rhs, bool retain) {
-    TensorBase(rhs, retain).swap(*this );
+  void reset(TensorImpl * rhs, bool should_retain) {
+    TensorBaseImpl(rhs, should_retain).swap(*this );
   }
-  void swap(TensorBase & rhs) {
+  void swap(TensorBaseImpl & rhs) {
     TensorImpl * tmp = pImpl;
     pImpl = rhs.pImpl;
     rhs.pImpl = tmp;
@@ -75,6 +83,26 @@ struct TensorBase {
   //TODO(zach): sort out friend structes
 public:
   TensorImpl * pImpl;
+
+private:
+  void retain() {
+    if (is_strong) {
+      pImpl->retain();
+    } else {
+      pImpl->weak_retain();
+    }
+  }
+
+  void release() {
+    if (is_strong) {
+      pImpl->release();
+    } else {
+      pImpl->weak_release();
+    }
+  }
 };
 
+using TensorBase = TensorBaseImpl<true>;
+using WeakTensorBase = TensorBaseImpl<false>;
+
 }} // namespace at::detail

aten/src/ATen/Utils.h

@@ -12,11 +12,9 @@
 
 #if defined(__clang__)
 #define __ubsan_ignore_float_divide_by_zero__ __attribute__((no_sanitize("float-divide-by-zero")))
-#define __ubsan_ignore_function__ __attribute__((no_sanitize("function")))
 #define __ubsan_ignore_vptr__ __attribute__((no_sanitize("vptr")))
 #else
 #define __ubsan_ignore_float_divide_by_zero__
-#define __ubsan_ignore_function__
 #define __ubsan_ignore_vptr__
 #endif
 

aten/src/ATen/templates/Tensor.h

@@ -13,6 +13,7 @@
 #include "ATen/Utils.h"
 #include "ATen/Device.h"
 #include "ATen/Layout.h"
+#include "ATen/optional.h"
 
 namespace at {
 struct Type;
@@ -42,6 +43,7 @@ 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 {
+  using TensorBase = detail::TensorBase;
   Tensor() : TensorBase() {}
   Tensor(TensorImpl * self, bool retain) : TensorBase(self, retain) {}
   Tensor(const TensorBase & rhs) : TensorBase(rhs) {}
@@ -198,6 +200,46 @@ struct Tensor : public detail::TensorBase {
   auto m(F func, Args&&... params) const -> decltype(func(*this, std::forward<Args>(params)...)) {
     return func(*this, std::forward<Args>(params)...);
   }
+
+  friend struct WeakTensor;
+};
+
+struct WeakTensor : public detail::WeakTensorBase {
+  using WeakTensorBase = detail::WeakTensorBase;
+  WeakTensor() : WeakTensorBase() {}
+  WeakTensor(TensorImpl * self, bool retain) : WeakTensorBase(self, retain) {}
+  WeakTensor(const WeakTensor & rhs) = default;
+  WeakTensor(WeakTensor && rhs) noexcept = default;
+  WeakTensor(const Tensor& t) : WeakTensorBase(t.pImpl, true) {}
+
+  // reimplemented from TensorBase so the return type is WeakTensor rather than TensorBase
+  WeakTensor & operator=(WeakTensor && rhs) & {
+    rhs.swap(*this);
+    return *this;
+  }
+  WeakTensor & operator=(WeakTensor const & rhs) & {
+    //Tensor ctor retains original rhs.pImpl
+    //then rhs.pImpl is swapped with this->pImpl
+    //finally Tensor dtor releases rhs.pImpl, which was originally this->pImpl
+    WeakTensor(rhs).swap(*this);
+    return *this;
+  }
+
+  WeakTensor & operator=(const Tensor& t) {
+    WeakTensor(t.pImpl, true).swap(*this);
+    return *this;
+  }
+
+  // non-retaining
+  TensorImpl * unsafeGetTensorImpl() const {
+    return pImpl;
+  }
+
+  // XXX: this can return undefined tensors
+  // Ideally it would be at::optional<Tensor>, but MSVC is too cool for that
+  Tensor lock() const {
+    return pImpl->weak_lock() ? Tensor(pImpl, false) : Tensor();
+  }
 };
 
 namespace detail {

aten/src/ATen/templates/TensorDerived.cpp

@@ -49,6 +49,11 @@ void * ${Tensor}::unsafeGetTH(bool retain) {
   return tensor;
 }
 
+void ${Tensor}::release_resources() {
+  ${THTensor}_free(${state,} tensor);
+  tensor = nullptr;
+}
+
 ${TensorDenseOrSparse}
 
 }

aten/src/ATen/templates/TensorDerived.h

@@ -23,6 +23,7 @@ struct ${Tensor} final : public TensorImpl {
   virtual Scalar localScalar() override;
   virtual void * unsafeGetTH(bool retain) override;
   virtual std::unique_ptr<Storage> storage() override;
+  virtual void release_resources() override;
   static const char * typeString();
 
 //TODO(zach): sort of friend permissions later so this

aten/src/ATen/test/CMakeLists.txt

@@ -18,7 +18,8 @@ list(APPEND ATen_CPU_TEST_SRCS
   ${CMAKE_CURRENT_SOURCE_DIR}/test_parallel.cpp
   ${CMAKE_CURRENT_SOURCE_DIR}/undefined_tensor_test.cpp
   ${CMAKE_CURRENT_SOURCE_DIR}/verify_api_visibility.cpp
-  ${CMAKE_CURRENT_SOURCE_DIR}/tbb_init_test.cpp)
+  ${CMAKE_CURRENT_SOURCE_DIR}/tbb_init_test.cpp
+  ${CMAKE_CURRENT_SOURCE_DIR}/weakref_test.cpp)
 
 list(APPEND ATen_CUDA_TEST_SRCS
   ${CMAKE_CURRENT_SOURCE_DIR}/integer_divider_test.cu