[SYCL] This PR adds the minimum modifications to the Eigen unsupported module required to run it on devices supporting SYCL.

* Abstracting the pointer type so that both SYCL memory and pointer can be captured.
* Converting SYCL virtual pointer to SYCL device memory in Eigen evaluator class.
* Binding SYCL placeholder accessor to command group handler by using bind method in Eigen evaluator node.
* Adding SYCL macro for controlling loop unrolling.
* Modifying the TensorDeviceSycl.h and SYCL executor method to adopt the above changes.

1 files changed, 11 insertions, 34 deletions

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorImagePatch.h b/unsupported/Eigen/CXX11/src/Tensor/TensorImagePatch.h
index 965bd8f1e..5ff67bdae 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorImagePatch.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorImagePatch.h
@@ -154,23 +154,6 @@ class TensorImagePatchOp : public TensorBase<TensorImagePatchOp<Rows, Cols, XprT
                                                            m_padding_left(padding_left), m_padding_right(padding_right),
                                                            m_padding_type(PADDING_VALID), m_padding_value(padding_value) {}
 
-#ifdef EIGEN_USE_SYCL // this is work around for sycl as Eigen could not use c++11 deligate constructor feature
-EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorImagePatchOp(const XprType& expr, DenseIndex patch_rows, DenseIndex patch_cols,
-                                                         DenseIndex row_strides, DenseIndex col_strides,
-                                                         DenseIndex in_row_strides, DenseIndex in_col_strides,
-                                                         DenseIndex row_inflate_strides, DenseIndex col_inflate_strides,
-                                                         bool padding_explicit, DenseIndex padding_top, DenseIndex padding_bottom,
-                                                         DenseIndex padding_left, DenseIndex padding_right, PaddingType padding_type,
-                                                         Scalar padding_value)
-                                                         : m_xpr(expr), m_patch_rows(patch_rows), m_patch_cols(patch_cols),
-                                                         m_row_strides(row_strides), m_col_strides(col_strides),
-                                                         m_in_row_strides(in_row_strides), m_in_col_strides(in_col_strides),
-                                                         m_row_inflate_strides(row_inflate_strides), m_col_inflate_strides(col_inflate_strides),
-                                                         m_padding_explicit(padding_explicit), m_padding_top(padding_top), m_padding_bottom(padding_bottom),
-                                                         m_padding_left(padding_left), m_padding_right(padding_right),
-                                                         m_padding_type(padding_type), m_padding_value(padding_value) {}
-
-#endif
 
     EIGEN_DEVICE_FUNC
     DenseIndex patch_rows() const { return m_patch_rows; }
@@ -242,6 +225,8 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
   typedef typename XprType::CoeffReturnType CoeffReturnType;
   typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
   static const int PacketSize = PacketType<CoeffReturnType, Device>::size;
+  typedef StorageMemory<CoeffReturnType, Device> Storage;
+  typedef typename Storage::Type EvaluatorPointerType;
 
   enum {
     IsAligned         = false,
@@ -256,15 +241,8 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
   typedef internal::TensorBlock<Scalar, Index, NumDims, Layout>
       OutputTensorBlock;
 
-#ifdef __SYCL_DEVICE_ONLY__
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator( const XprType op, const Device& device)
-  #else
-    EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator( const XprType& op, const Device& device)
-  #endif
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator( const XprType& op, const Device& device)
       : m_device(device), m_impl(op.expression(), device)
-#ifdef EIGEN_USE_SYCL
-      , m_op(op)
-#endif
   {
     EIGEN_STATIC_ASSERT((NumDims >= 4), YOU_MADE_A_PROGRAMMING_MISTAKE);
 
@@ -410,7 +388,7 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Dimensions& dimensions() const { return m_dimensions; }
 
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(Scalar* /*data*/) {
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool evalSubExprsIfNeeded(EvaluatorPointerType /*data*/) {
     m_impl.evalSubExprsIfNeeded(NULL);
     return true;
   }
@@ -516,13 +494,15 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
     return packetWithPossibleZero(index);
   }
 
-  EIGEN_DEVICE_FUNC typename Eigen::internal::traits<XprType>::PointerType data() const { return NULL; }
+  EIGEN_DEVICE_FUNC EvaluatorPointerType data() const { return NULL; }
 
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TensorEvaluator<ArgType, Device>& impl() const { return m_impl; }
 
 #ifdef EIGEN_USE_SYCL
-  // Required by SYCL in order to construct the expression tree on the device
-  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const XprType& xpr() const { return m_op; }
+  // binding placeholder accessors to a command group handler for SYCL
+  EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void bind(cl::sycl::handler &cgh) const {
+    m_impl.bind(cgh);
+  }
 #endif
 
   Index rowPaddingTop() const { return m_rowPaddingTop; }
@@ -693,6 +673,7 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketReturnType packetWithPossibleZero(Index index) const
   {
     EIGEN_ALIGN_MAX typename internal::remove_const<CoeffReturnType>::type values[PacketSize];
+    EIGEN_UNROLL_LOOP
     for (int i = 0; i < PacketSize; ++i) {
       values[i] = coeff(index+i);
     }
@@ -744,12 +725,8 @@ struct TensorEvaluator<const TensorImagePatchOp<Rows, Cols, ArgType>, Device>
 
   Scalar m_paddingValue;
 
-  const Device& m_device;
+  const Device EIGEN_DEVICE_REF m_device;
   TensorEvaluator<ArgType, Device> m_impl;
-  #ifdef EIGEN_USE_SYCL
-  // Required for SYCL in order to construct the expression tree on the device
-   XprType m_op;
-   #endif
 };